queue_annotate_aj_part2.json

[{"key": "aj2-000", "text": "NER) at the primary level in the\nsurvey year (1996) was 50% greater for the highest expenditure quintile compared to the lowest\nexpenditure quintile. The inequity is even more pronounced in secondary education (lower secondary\neducation is part of basic education but the survey data does not separate the two), where the NER of\nthe highest quintile was more than 420% higher than the NER of the lowest quintile. The income\ndifferences in enrollment are significantly higher than other countries in Africa. The problem in urban\nareas is access - demand exists among all groups but the rationing of school intake ends up benefiting\nthe better off. Any further expansion of places will help the poorer segments of the population. Thus,\npublic expenditure in basic education is justified both on the public good rationale and also on the\nequity rationale.\n\n\nThe ten-year program proposed by the Government will also result in efficiency gains through lowered\nrepetition and drop out rates. This will result in reducing the average number of years to graduate\nfrom the primary and middle school levels, resulting in large potential savings in recurrent and\ninvestment expenditures in the long-run. The net present value of these public expenditure savings was\nfound to be significantly higher than the net present value of the investment costs required by the\nprogram. This is based on the difference between what the Government would have had to spend in\nthe absence of system reforms to educate the same number of students to the basic education level and\nwhat the Government would spend with systemic reforms. These savings yield an internal rate of over\n\n11% which clearly justifies the investment. This rate of return is actually an understatement for the\nprogram because the benefits do not include benefits from economic development, externalities and\nreduction in enrollment differentials between the poor and the better-off.", "source": "fcv_pads_east_africa", "subset": "annotate_aj_part2", "spans": [{"key": "fcv_pads_east_africa:015820:19:1:0", "start": 272, "end": 283, "surface": "survey data", "probe_tag": "keep", "probe_score": 0.9509, "luna_label": 1, "luna_reason": "Existing survey data supports enrollment inequity analysis despite category limitation."}]}, {"key": "aj2-001", "text": "RIs as well as the strong institutional strengthening that is important for long-term improvement within\nthe system particularly related to pre-primary education and the introduction of early childhood assessments. As\nindicated in Table 2 below, KP1 1 was substantially achieved (90%) for the original targets and surpassed for the revised\ntargets. Much of this success can be attributed to the GEQIP-E support for O-Classes interventions that promoted\nschool readiness. The 2025 Dashboard data showed that school readiness among Grade 1 students increased from\n32.9 percent in 2021 to 45.3 percent in 2025. In addition, ECE rose from 45 percent (2021) to 58 percent (2025).\n\n34. **KPI 2 was not met.** The achievement of this KPI proved problematic throughout implementation because of\nchallenges related to COVID-19, internal conflicts, natural disasters (droughts and floods), increasing refugee\npopulations, and deteriorating economic conditions. However, the fact that the survival rate was largely stable through\nfour years of exogenous factors is a substantial achievement. GEQIP-E resources were instrumental in supporting the\neducation system during these challenging times which was important for just maintaining the survival rates. This\nObjective contributed to institutional strengthening through DLIs 1 and 2 which were directly related to: (i)\nimplementation of a QEAP of preprimary (O-classes) schools; and (ii) performance-based school awards (PBSA) <sup>20</sup> [^20: The PBSA awards were 30,000 birr per school and disbursed directly to schools using the school bank account under the responsibility of the\nschool improvement plan director.] for\n10 percent of schools in each region that have better performance in improving G2/G1 enrollment and survival rate to\nGrade 5. Finally, five of the IRIs were exceeded and one was substantially achieved.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Indicator|Original<br>Baseline<br>2016|Revised<br>Baseline|Original<br>Target|Revised<br>Target<br>2020|Revised<br>Target<", "source": "fcv_pads_east_africa", "subset": "annotate_aj_part2", "spans": [{"key": "fcv_pads_east_africa:000638:22:1:0", "start": 475, "end": 494, "surface": "2025 Dashboard data", "probe_tag": "keep", "probe_score": 0.9629, "luna_label": 1, "luna_reason": "Dashboard data supports reported school-readiness increases from 2021 to 2025."}]}, {"key": "aj2-002", "text": " from one stage to another. It is also driven in part by the curriculum which is geared to\npreparing students for the French baccalaureate examnination and may be contextually difficult for\nDjiboutians from less educated families.\n\n\n**3. Income and Gender Gaps in Enrollment Rates**\n\nEven though the main constraint at present appears to be school places, there is already evidence of\ngender and income gaps which cannot be explained by lack of school places alone. These are\nexpected to become more prominent over time as enrollment rates rise.\n\n\nAccording to the household expenditure survey data, in urban areas, the Net Enrollment Rate in\nPrimary Enrollment is 50% higher for the highest expenditure quintile compared to the lowest\nexpenditure quintile. The inequity is even worse in secondary education (lower secondary education\nis part of basic education but the survey data did not separate the two), where the NER of the highest\nquintile is 420% higher than the NER of the lowest quintile. The problem in urban areas is access demand exists among all groups but the rationing of sets ends up benefiting the better off who live in\nareas where schools have historically been located. Any further expansion of places will help the\npoorer segments of the population more particularly if care is taken to site the schools in areas where\nthe poor live.\n\n\nThere are also significant gender gaps and research indicates that educated mothers play a key role in\nthe country's overall development. There is a shortage of school places and any rationing works to\nthe detriment of girls enrollment. Parents are less willing for their girls to attend school because in\npar., they may view the curriculum as foreign. In addition, despite the fact the education is officially\nfree, poor families still have difficulty paying the cost of books and materials. They prefer to use\ntheir constrained resources for their boys who they feel have a better labor market potential. Finally,\nthe data from the Household Survey, showed that even if girls go to school, their parents pull them\nout at an", "source": "fcv_pads_east_africa", "subset": "annotate_aj_part2", "spans": [{"key": "fcv_pads_east_africa:013071:38:1:1", "start": 870, "end": 881, "surface": "survey data", "probe_tag": "keep", "probe_score": 0.9348, "luna_label": 1, "luna_reason": "Survey data supports reported enrollment-rate comparisons and separation limitation."}, {"key": "fcv_pads_east_africa:013071:38:1:2", "start": 1978, "end": 2008, "surface": "data from the Household Survey", "probe_tag": "keep", "probe_score": 0.9653, "luna_label": 1, "luna_reason": "Household Survey data are cited as showing parents withdraw girls from school."}]}, {"key": "aj2-003", "text": "**The World Bank**\nHousing Finance, Lands, and Sustainable Investments Project (P513352) PROJECT APPRAISAL DOCUMENT\n\n\nthe creation of fiscal space for the debt office. It is estimated that the structure could potentially generate US$70 million\nof net present value savings for GoK, subject to market conditions and confirmation of the second loss tranche coverage.\n\n\n73. **The project is aligned with the goals of the Paris Agreement on mitigation, adaptation and resilience.**\nConsistency with Kenya’s climate strategies is demonstrated by alignment with the updated NDC (targeting a 32 percent\nreduction in greenhouse gas emissions by 2030 relative to business-as-usual), the National Adaptation Plan/NCCAPs, and\nthe Kenya Country Climate and Development Report (CCDR, 2023). The project supports CCDR priorities on climateinformed urbanization, protection of forests and water towers, and expansion of clean energy access, and leverages\nKenya’s emerging green finance framework.\n\n\n74. **All project components are consistent with the mitigation, adaptation, and resilience goals of the Paris**\n**Agreement.** Across components, the project is expected to do no harm to the climate agenda and does not support\nactivities that contradict Kenya’s decarbonization pathway, presenting a low risk of carbon lock-in when compared to\nfeasible lower-carbon alternatives. Residual risks are mitigated through eligibility criteria, strengthened systems (including\nfinancial intermediaries, Environment and Social Management Systems, and climate risk management), and data-driven\nincentives such as sustainability-linked KPIs.\n\n\n75. **Gender analysis.** Kenyan women face persistent gaps in property ownership that constrain access to housing\nfinance. The Kenya Demographic and Health Survey 2022 shows that 33 percent of women versus 45 percent of men own\na house, and 27 percent versus 34 percent own land, among adults aged 15–49. <sup>26</sup> Among homeowners, women are", "source": "fcv_pads_east_africa", "subset": "annotate_aj_part2", "spans": [{"key": "fcv_pads_east_africa:001129:34:0:0", "start": 1747, "end": 1787, "surface": "Kenya Demographic and Health Survey 2022", "probe_tag": "keep", "probe_score": 0.9618, "luna_label": 1, "luna_reason": "Survey provides cited gender-disaggregated property ownership findings."}]}, {"key": "aj2-004", "text": " from one stage to another. It is also driven in part by the curriculum which is geared to\npreparing students for the French baccalaureate examnination and may be contextually difficult for\nDjiboutians from less educated families.\n\n\n**3. Income and Gender Gaps in Enrollment Rates**\n\nEven though the main constraint at present appears to be school places, there is already evidence of\ngender and income gaps which cannot be explained by lack of school places alone. These are\nexpected to become more prominent over time as enrollment rates rise.\n\n\nAccording to the household expenditure survey data, in urban areas, the Net Enrollment Rate in\nPrimary Enrollment is 50% higher for the highest expenditure quintile compared to the lowest\nexpenditure quintile. The inequity is even worse in secondary education (lower secondary education\nis part of basic education but the survey data did not separate the two), where the NER of the highest\nquintile is 420% higher than the NER of the lowest quintile. The problem in urban areas is access demand exists among all groups but the rationing of sets ends up benefiting the better off who live in\nareas where schools have historically been located. Any further expansion of places will help the\npoorer segments of the population more particularly if care is taken to site the schools in areas where\nthe poor live.\n\n\nThere are also significant gender gaps and research indicates that educated mothers play a key role in\nthe country's overall development. There is a shortage of school places and any rationing works to\nthe detriment of girls enrollment. Parents are less willing for their girls to attend school because in\npar., they may view the curriculum as foreign. In addition, despite the fact the education is officially\nfree, poor families still have difficulty paying the cost of books and materials. They prefer to use\ntheir constrained resources for their boys who they feel have a better labor market potential. Finally,\nthe data from the Household Survey, showed that even if girls go to school, their parents pull them\nout at an", "source": "fcv_pads_east_africa", "subset": "annotate_aj_part2", "spans": [{"key": "fcv_pads_east_africa:014933:38:1:2", "start": 1978, "end": 2008, "surface": "data from the Household Survey", "probe_tag": "keep", "probe_score": 0.9653, "luna_label": 1, "luna_reason": "Household survey data supports a concrete finding about girls’ school withdrawal."}]}, {"key": "aj2-005", "text": " from one stage to another. It is also driven in part by the curriculum which is geared to\npreparing students for the French baccalaureate examnination and may be contextually difficult for\nDjiboutians from less educated families.\n\n\n**3. Income and Gender Gaps in Enrollment Rates**\n\nEven though the main constraint at present appears to be school places, there is already evidence of\ngender and income gaps which cannot be explained by lack of school places alone. These are\nexpected to become more prominent over time as enrollment rates rise.\n\n\nAccording to the household expenditure survey data, in urban areas, the Net Enrollment Rate in\nPrimary Enrollment is 50% higher for the highest expenditure quintile compared to the lowest\nexpenditure quintile. The inequity is even worse in secondary education (lower secondary education\nis part of basic education but the survey data did not separate the two), where the NER of the highest\nquintile is 420% higher than the NER of the lowest quintile. The problem in urban areas is access demand exists among all groups but the rationing of sets ends up benefiting the better off who live in\nareas where schools have historically been located. Any further expansion of places will help the\npoorer segments of the population more particularly if care is taken to site the schools in areas where\nthe poor live.\n\n\nThere are also significant gender gaps and research indicates that educated mothers play a key role in\nthe country's overall development. There is a shortage of school places and any rationing works to\nthe detriment of girls enrollment. Parents are less willing for their girls to attend school because in\npar., they may view the curriculum as foreign. In addition, despite the fact the education is officially\nfree, poor families still have difficulty paying the cost of books and materials. They prefer to use\ntheir constrained resources for their boys who they feel have a better labor market potential. Finally,\nthe data from the Household Survey, showed that even if girls go to school, their parents pull them\nout at an", "source": "fcv_pads_east_africa", "subset": "annotate_aj_part2", "spans": [{"key": "fcv_pads_east_africa:009841:38:1:1", "start": 870, "end": 881, "surface": "survey data", "probe_tag": "keep", "probe_score": 0.9348, "luna_label": 1, "luna_reason": "Existing survey data supports enrollment-rate comparisons and identifies an aggregation limitation."}, {"key": "fcv_pads_east_africa:009841:38:1:2", "start": 1978, "end": 2008, "surface": "data from the Household Survey", "probe_tag": "keep", "probe_score": 0.9653, "luna_label": 1, "luna_reason": "Household Survey data supports a concrete finding about girls’ school attendance."}]}, {"key": "aj2-006", "text": " and Completion<br>of Baseline Socio-<br>Economic Information<br>(OP4.12)|Management assessed as satisfactory in the Quarterly<br>Monitoring Report:<br> <br>Improvements in outcome indicators, as measured from<br>findings of the updated (2010) socio-economic survey,<br>indicating benefits received by project affected persons<br>(PAPs) from CDAP programs; and continued monitoring<br>of impacts recorded in the monitoring and evaluation<br>(M&E) database<br> <br>Improvements in reporting in BEL’s Quarterly<br>Environment and Social Monitoring, including database<br>on household surveys|<br>**_Completed_**<br>**_Completed_** <br>|\n|Sharing of Project Benefits<br>(OP4.12)| <br>Management has followed up with BEL on progress in<br>delivery of services in Naminya resettlement site and<br>directly affected villages. Provision of water supply<br>services and market stalls is complete. Construction of<br>electricity distribution network is in progress; connection<br>of households to power grid has been initiated|**_Ongoing_**~~**_4_**~~|\n|**Environment Assessment and Mitigation Measures**<br>|**Environment Assessment and Mitigation Measures**<br>|**Environment Assessment and Mitigation Measures**<br>|\n|Environment Management<br>Plan and Kalagala Offset<br>(OP4.01)|• <br>Management assessed as satisfactory BEL’s ongoing<br>afforestation activities<br>• <br>Management confirmed that the SMP for the Kalagala<br>Offset, which", "source": "fcv_pads_east_africa", "subset": "annotate_aj_part2", "spans": [{"key": "fcv_pads_east_africa:015431:8:1:0", "start": 245, "end": 266, "surface": "socio-economic survey", "probe_tag": "confusion", "probe_score": 0.6179, "luna_label": 1, "luna_reason": "Updated 2010 survey findings measure project outcomes and reported benefits."}]}, {"key": "aj2-007", "text": "peoples (IPs) from governance structures and rights recognition. Access restrictions\nin protected areas or land use changes could lead to community displacement.\nStakeholder engagement, including with VMGs/Minority and Marginalized\nCommunities (MMGs) may be limited. If ecosystem service benefits aren’t fairly\ndistributed, VMGs/MMGs may be left out, exacerbating inequalities and causing\nsocial tensions. Undervaluing traditional knowledge through modern governance\ncould lead to cultural identity loss. Resource competition could intensify, causing\nsocial/community conflicts with external stakeholders. Promoting climate-resilient\nlandscapes might disrupt existing economic activities and impact living standards.\nData privacy concerns and potential misuse of information related to land use and\ncommunity activities also exist; and **Component** **2** . Livelihood restoration activities\nmay disrupt livelihoods, and increase inequalities. Increased management of\nprotected areas may, disrupt livelihoods, exclude VMGs /MCs and affect\nimplementation.\n\n\n**2** **E&S Capacity Assessment Methodology**\n\nAs stated in 1.3 above, the aim of the PIEs’ E&S capacity assessment was to\ndetermine each institution’s capacity to comply with national and World Bank’s E&S\nrequirements. Thereafter, and guided by the findings, develop an E&S capacity\nbuilding strategy for the PIEs during project implementation.\n\nIn undertaking the capacity assessment, the following tools and methods were used:\n\n**2.1** **Desk Reviews and Analysis**\n\nThe desk review and analysis covered publicly available secondary data on the PIEs;\nnational E&S and World Bank’s E&S framework requirements; and developed\nEnvironmental and Social instruments such as the Environmental and Social\nCommitment Plan (ESCP), Environmental and Social Management Framework\n(ESMF), Environmental and Social Review Summary (ESRS), Labour Management\nProcedures (LMP), Security Management Plan (SMP)", "source": "fcv_pads_east_africa", "subset": "annotate_aj_part2", "spans": [{"key": "fcv_pads_east_africa:005567:6:0:0", "start": 1583, "end": 1609, "surface": "secondary data on the PIEs", "probe_tag": "confusion", "probe_score": 0.3557, "luna_label": 1, "luna_reason": "Publicly available secondary data was used in the desk review and analysis."}]}, {"key": "aj2-008", "text": "\nexecution of: (i) PAP census survey, (ii) a socio-economic project preparation and with the\nsurvey, and (iii) a valuation covering all affected assets. involvement of potentially displaced\n\npeople, including (a) the results of a\n\nTo conduct socio-economic baseline survey and census survey covering (i) current\nassessment, a range of tools and data gathering techniques occupants of the affected area to\nused in the field are summarized below. establish a basis for the design of the\n\n\n\n\n  - **_Household Socio-Economic Surveys_**\nThe surveys provided a detailed socio-economic profile\nof the PAPs. The socio-economic surveys were\nundertaken using a structured questionnaire to identify the\ncharacteristics of the potentially affected population\nensuring that all the different categories and groups of\npeople to be affected by the proposed project are captured\nand consulted.\n\n\n\nThe findings of socioeconomic studies\nto be conducted in the early stages of\nproject preparation and with the\ninvolvement of potentially displaced\npeople, including (a) the results of a\ncensus survey covering (i) current\noccupants of the affected area to\nestablish a basis for the design of the\nresettlement program and to exclude\nsubsequent inflows of people from\neligibility for compensation and\nresettlement assistance; (ii) standard\ncharacteristics of displaced\nhouseholds, including a description of\nproduction systems, labor, and\nhousehold organization; and baseline\ninformation on livelihoods (and\nstandards of living (including health\nstatus) of the displaced population; (iii)\nthe magnitude of the expected loss-total or partial--of assets, and the\nextent of displacement, physical or\neconomic Para 6, Annex A, OP 4.12.\n\n\n\nPage | 26", "source": "fcv_pads_east_africa", "subset": "annotate_aj_part2", "spans": [{"key": "fcv_pads_east_africa:006940:25:1:0", "start": 19, "end": 36, "surface": "PAP census survey", "probe_tag": "confusion", "probe_score": 0.6676, "luna_label": 0, "luna_reason": "Survey execution indicates project data collection rather than reuse of existing data."}, {"key": "fcv_pads_east_africa:006940:25:1:1", "start": 242, "end": 290, "surface": "socio-economic baseline survey and census survey", "probe_tag": "confusion", "probe_score": 0.7823, "luna_label": 0, "luna_reason": "The sentence plans to conduct these surveys, so the data does not yet exist."}]}, {"key": "aj2-009", "text": "* Popular Benchmarks\n**children.**\n\n\n**Project** **Development** **Outcome** **/** **Impact** **Project reports:** **(from** **Objective** **to Goal)**\n**Objective:** **Indicators:**\n**Assist** **war affected** - Improved social capital and - Initial Social Assessment - Communities in the NSAP\n**communities** **to restore** organizational development; (to establish indicators and target areas are assisted to\n**infrastructure,** **services** **and** - Increased access to and use methodologies for social ensure a reduced risk of\n**build** **local** **capacity for** of social and economic capital and organizational conflict\n**collective** **action.** Priority infrastructure and services development)\nwill be given to areas not - Proportion of NSAP - Annual social assessments; - NACSA complements and\npreviously serviced by investments targeted to newly - NaCSA M&E data; extends the work of other\ngovernment, newly accessible accessible areas, & areas - M&E data of relevant line agencies and rninistries\nand the most vulnerable previously not served, and mninistries; in support of the PRSP's\npopulation groups within those vulnerable people within these - Beneficiary Assessment poverty reduction and\nareas. areas; (BAs) biannually; decentralization objectives\n\n                  - Proportion of sub-projects                   - Participatory evaluation\nthat reflect priorities of reports for a random sample of                   - NACSA is fully integrated\ntargeted communities and assisted conmmunities; into national planning and\nbeneficiaries; and                  - Technical audits resource allocation\n\n                  - Proportion of sub-projects frameworks (such as the\noperative 24emonths after National Recovery Strategy,\ncorpletion. the PRSP, and", "source": "fcv_pads_east_africa", "subset": "annotate_aj_part2", "spans": [{"key": "fcv_pads_east_africa:016347:29:1:0", "start": 862, "end": 876, "surface": "NaCSA M&E data", "probe_tag": "confusion", "probe_score": 0.2118, "luna_label": 0, "luna_reason": "Names project monitoring data without showing an analyzed finding or substantive decision use."}]}, {"key": "aj2-010", "text": "Disbursement forecast\n\n\n\nContract number\n*Contract subject\nAwardee\n*Launching date\n-Expected delivery date\n-Non objection date\n*Expected date of final delivery\n*Bidder nationality\n*Contract allocation (general account, budget, loan\ncategory, geographic area)\n*List of contracts\nManagement of financial -Standard financial statements (balance sheet;\naccounts statement of sources and uses of funds/income\nstatement, ...)\n*LACI reports for the project duration\nFixed Assets management -Inventory of Fixed Assets (type, quantity, valuation,\ndate of service, etc.)\n\n\n\nSupplier\nAccounting category ; budgetary and accounting\nallocation of fixed assets\n\n\n\nLocation\nDepreciation\n-Disposal of Fixed assets\n\n\n\n**Module** Functions\nSorting parameters Project ID and currency used\n\n                  - Fiscal years\nCurrency\nDecentralized data entry locations\n\n\n\nChart of accounts, managerial reports, geographic\nareas of intervention, etc.\n\n\n\n\n                - Books of accounts\nDonors\n\n                 - Contracts\nCategories of disbursement\nUser Management Data storage ; restitution ; correction; cleaning; etc.\n\n                - Import/export of data to other Tempro modules\n\n\n\nIt is expected that the application would be modified to differentiate the operations from the\nprojects, as well as funding sources to allow for reporting in financial and accounting terms of the\nproject objectives and activities. The concept should allow for proper monitoring of the project\nduring the life of the credit, namely: (i) chart of accounts; (ii) by category, component, and subcomponent; (iii) by geography (type of establishment, site and district); (iv) by category of\nexpenses; and (v) in local and foreign currency. Reporting of multi-level data is planned, which\n**wiU** bring about a more dynamic approach to the management of the project, and which should", "source": "fcv_pads_east_africa", "subset": "annotate_aj_part2", "spans": [{"key": "fcv_pads_east_africa:012423:51:0:0", "start": 1720, "end": 1736, "surface": "multi-level data", "probe_tag": "confusion", "probe_score": 0.4274, "luna_label": 0, "luna_reason": "Planned reporting activity, not use of existing data."}]}, {"key": "aj2-011", "text": "RAP Report for Murang’a Water Supply November 2014\n\n\n- To identify the PAPs in terms of the different entitlements in relation to land\nowners and asset owners;\n\n- To prepare a socio-economic profile of PAPs;\n\n- To assess incomes and identify productive activities;\n\n- To identify possible vulnerable groups.\n\nData collected from the household survey included:\n\n- Sources of income and occupation of the Project Affected Persons.\n\n- Marital status of the PAPs and the number of household members who would be\naffected by the project.\n\n- Levels of education of the household head and other members of the household.\n\n- Employment status of PAPs.\n\n#### (b) Key informant interviews\n\n\nOne-on-one interviews with county and national government agencies and institutions\nin the project area were undertaken i.e. from Kangema, Kiharu, Kandara, Kigumo and\nMurang’a South Sub-Counties. These interviews were conducted to augment and\nconfirm data and information obtained using the other tools and methodologies.\n\nThe main objectives of the above exercise were to:\n\n- Introduce the consultancy team and the scope of work;\n\n- Obtain more information about the project area;\n\n- Obtain views of the local area administration on the project;\n\n- Collect baseline information from the project area;\n\n- Organise for a public sensitization meeting.\n\n#### (c) Data analysis\n\nMicrosoft Excel was used for data entry and analysis. Data collected from the household\nsurvey was triangulated with information from site surveys, observations by the\nsociologist and key informant interviews.\n\n1.7.4 Land and Asset Valuation\n\nThe Land and asset survey was conducted from 18 October to 9 December 2014 to\nestablish the land, structures, hedges, crops and trees of the PAPs that would be\naffected by the construction of the water project. The valuer was guided by respective\n\n\n7", "source": "fcv_pads_east_africa", "subset": "annotate_aj_part2", "spans": [{"key": "fcv_pads_east_africa:016432:19:0:0", "start": 333, "end": 349, "surface": "household survey", "probe_tag": "confusion", "probe_score": 0.6189, "luna_label": 1, "luna_reason": "Past household survey data provide concrete socioeconomic findings about affected persons."}, {"key": "fcv_pads_east_africa:016432:19:0:1", "start": 1490, "end": 1502, "surface": "site surveys", "probe_tag": "confusion", "probe_score": 0.6064, "luna_label": 1, "luna_reason": "Existing site survey information was used to triangulate household survey data."}]}, {"key": "aj2-012", "text": ">|SheepI Goat : Donkey<br> <br> <br>|BeeHive<br>|\n|. FartaSide<br>|2.713.64<br>|4.88<br>|3.88<br>! 1.62<br> <br>|3.88<br>! 1.62<br> <br>|7 <br>|\n|EbinatSide|2.512.66|3.84|4.4|1.88|4.1|\n\n\n\nSource: Household Survey. 2008\n\n\n3.3. Vulnerable Groups\n\n\nAs per the policy and legal framework of the Government and major donor\n\nagencies like the World Bank, vulnerable groups, like the elderly, women\nhousehold heads and those with physical and emotional impairment. are\nexpected to have special support to address part of their problems during the\nrelocation and resettlement process. These landless households are also\nexpected to have special support. The house to house survey result shows that\nabout six percent of the household heads are falling within the category of\nvulnerable groups. Those aged ones (65 and plus) and women headed who\nlost more than 25% of their land are also taken as vulnerable groups.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Table 3.3: Vulnerability Status amongst PAPs I Vulnerability Type|Col2|Col3|Col4|Col5|Col6|Col7|\n|---|---|---|---|---|---|---|\n|i <br>Woreda<br> <br>~~I ~~<br>Vulnerability Type<br>I <br>Old Age( 65+)<br>Hearing<br>~~I ~~Sight<br>Amputee<br>landless<br>1 household<br>Impair", "source": "fcv_pads_east_africa", "subset": "annotate_aj_part2", "spans": [{"key": "fcv_pads_east_africa:011334:18:2:1", "start": 650, "end": 671, "surface": "house to house survey", "probe_tag": "confusion", "probe_score": 0.5725, "luna_label": 1, "luna_reason": "Survey result supports the stated six-percent vulnerability finding."}]}, {"key": "aj2-013", "text": "The World Bank\n\nKenya Water Security and Climate Resilience Project (P117635) ICR DOCUMENT\n\n\n<mark>disbursement rate, with 65 percent of the funds disbursed in the second half, reflecting compressed implementation</mark>\n<mark>timelines.</mark>\n\n\n47. <mark>Based on the above discussion, Efficiency of the project is rated Modest.</mark>\n\n\n**D.** **JUSTIFICATION OF OVERALL OUTCOME RATING**\n\n\n_Rating: Moderately Satisfactory_\n\n\n48. <mark>Applying the World Bank’s split rating evaluation methodology for the selected restructuring phases, the project’s</mark>\n<mark>overall outcome is rated Moderately Satisfactory (see Table 4). Feedback from 450 end beneficiaries in ICR M&E surveys,</mark>\n<mark>including water institution staff, consistently reflected satisfaction with the project’s accomplishments. Although initial</mark>\n<mark>challenges stemmed from an ambitious design, limited preparedness, and slower disbursement in the first half, these</mark>\n<mark>obstacles were progressively overcome. The project resulted in a mid-project turnaround that delivered tangible outcomes</mark>\n<mark>relative to ambitious targets across institutions, water sub-sector and regions spread over western and eastern of Kenya</mark>\n<mark>including flood protection infrastructure, Mombasa’s water supply network, 78% completion of LNISP-1 irrigation scheme</mark>\n<mark>with clear completion strategy from GoK, watershed management, FFEWS, and a strengthened investment pipeline.</mark>\n\n\n49. <mark>The project maintained strong alignment with Kenya’s national development priorities and the World Bank CPFs.</mark>\n<mark>By closure, all allocated funds had been effectively disbursed, while over 158,000 direct beneficiaries experienced</mark", "source": "fcv_pads_east_africa", "subset": "annotate_aj_part2", "spans": [{"key": "fcv_pads_east_africa:005823:22:0:0", "start": 670, "end": 685, "surface": "ICR M&E surveys", "probe_tag": "confusion", "probe_score": 0.7853, "luna_label": 1, "luna_reason": "Survey feedback from 450 beneficiaries supports the project's outcome rating."}]}, {"key": "aj2-014", "text": "**2.3 Monitoring and Evaluation (M&E) Design, Implementation and Utilization**\n\nICR Rating: Moderately Satisfactory _._\n\n**_M&E design._** M&E design underestimated the complexity of measuring improvements of local\ngovernment staff capacity and the improvement of university capacity to support LG. Successful\nsteps were taken to remedy the initial M&E problems—including an assessment involving 578\nfield interviews with project beneficiaries and key informants—but the resulting evaluation\ninformation only became available late in the implementation period (M&E design was also\ndiscussed in section 7.1).\n\n**_M&E implementation._** The experiences with monitoring versus evaluation are examined\nseparately:\n\n\n  - _Monitoring_ . Monitoring of outcomes of individual activities was done comprehensively\nthroughout the project, despite delay in development of a computerized monitoring\nsystem. There was extensive reporting of participant satisfaction with project-funded\ncourses. Various grant-funded efforts (such as research and curriculum development)\nwere divided into phases. Each phase had an _ex ante_ review by I@MAK.COM; each\nfunded phase had an _ex post_ review before the next phase was funded. Curricula\nunderwent extensive reviews by faculty organizations before approvals of reforms and\ninnovations. Normal academic processes assured acceptable performance of the projectfunded students taking academic courses, as well as for those doing project-funded\nresearch. Similarly, those teaching short courses received feedback from the participant\nsurveys. I@MAK.COM emphasized a traditional approach to overall program\nmanagement rather than approaches based on quantitative and qualitative M&E data.\nI@MAK.COM monitored large portions of the program carefully, especially those\ninvolving grant-funded activities.\n\n\n  - _Evaluation._ The evaluation was ultimately reasonably successful but came late in the\nproject. There were two failed initial attempts to produce baselines using consulting\nfirms. In both cases, the firms were selected using standard Bank procurement\nprocedures", "source": "fcv_pads_east_africa", "subset": "annotate_aj_part2", "spans": [{"key": "fcv_pads_east_africa:019669:15:0:0", "start": 1546, "end": 1565, "surface": "participant\nsurveys", "probe_tag": "confusion", "probe_score": 0.563, "luna_label": 1, "luna_reason": "Participant surveys provided feedback used to assess short-course teaching."}, {"key": "fcv_pads_east_africa:019669:15:0:1", "start": 1702, "end": 1710, "surface": "M&E data", "probe_tag": "confusion", "probe_score": 0.1046, "luna_label": 0, "luna_reason": "Generic M&E data is mentioned without an attributed finding or concrete analytical use."}]}, {"key": "aj2-015", "text": "OCHA Office of Commission for Humanitarian <sup>Assistance</sup>\nPAMC Project Approval and Monitoring Committee\nPETS Public Expenditure Tracking Survey\nPOM Project Operational Manual\nPPA Participatory Poverty Assessment\nQER Quality Enhancement Review\nRUF Revolutionary United Front\nSAPA Social Action and Poverty Alleviation <sup>Program</sup>\nSHARP Sierra Leone HIV/AIDS Response Project\nSLRA Sierra Leone Roads Authority\nSOCAT Social Capital Assessment Tool\nSPP Strategic Planning and Action Process\nTEP Training and Employment Program\nTSS Transitional Support Strategy\nUNAMSIL United Nations Mission for Sierra <sup>Leone</sup>\nUNHCR United Nations High Commission for <sup>Refugees</sup>\nUNICEF United Nations Children's Fund\nUNOPS United National Operations Support\n\n\nVice President: Mr. Callisto Madavo\nCountry Director: Mr. Mats Karlsson\nSector Manager: Mr. Alexandre Abrantes\nTask Team Leader/Task Manager: Ms. Eileen Murray", "source": "fcv_pads_east_africa", "subset": "annotate_aj_part2", "spans": [{"key": "fcv_pads_east_africa:014306:2:0:0", "start": 112, "end": 151, "surface": "PETS Public Expenditure Tracking Survey", "probe_tag": "confusion", "probe_score": 0.0633, "luna_label": 0, "luna_reason": "Survey is merely listed in a glossary without evidence of data use."}]}, {"key": "aj2-016", "text": "The World Bank\n\n\n\n\n\nReport No: ISR3705\n\n\n\n\n\n\n\n\n|Col1|Col2|Col3|Comments|Col5|Refers to part of Northern<br>Corridor road in good<br>condition. IRI is less than 3.0<br>for the two road sections<br>reconstructed. Construction<br>works for the other two road<br>sections nearing completion.<br>Contract awarded for two<br>more contracts, but progress<br>has been slow. Construction<br>on other two road contracts<br>has commenced.|80% of Northern Corridor in<br>good condition|\n|---|---|---|---|---|---|---|\n|Roads rehabilitated, Non-rural||Kilometers|Value|0.00|200.00|381.00|\n|Roads rehabilitated, Non-rural||Kilometers|Date|16-Dec-2004|09-Jun-2011|31-Dec-2012|\n|Roads rehabilitated, Non-rural||Kilometers|Comments||Over 200 km already<br>reconstructed and in use||\n|Road users and local persons surveyed aware<br>of/making use of ACT and other facilities for<br>HIV/AIDs campaign along the Northern<br>Corridor||Percentage|Value|0.00|0.00|70.00|\n|Road users and local persons surveyed aware<br>of/making use of ACT and other facilities for<br>HIV/AIDs campaign along the Northern<br>Corridor||Percentage|Date|16-Dec-2004|30-Dec-2010|31-Dec-2012|\n|Road users and local persons surveyed aware", "source": "fcv_pads_east_africa", "subset": "annotate_aj_part2", "spans": [{"key": "fcv_pads_east_africa:018302:6:0:0", "start": 766, "end": 803, "surface": "Road users and local persons surveyed", "probe_tag": "confusion", "probe_score": 0.5792, "luna_label": 0, "luna_reason": "Standalone table indicator fragment, not an independently used data source."}]}, {"key": "aj2-017", "text": "* Popular Benchmarks\n**children.**\n\n\n**Project** **Development** **Outcome** **/** **Impact** **Project reports:** **(from** **Objective** **to Goal)**\n**Objective:** **Indicators:**\n**Assist** **war affected** - Improved social capital and - Initial Social Assessment - Communities in the NSAP\n**communities** **to restore** organizational development; (to establish indicators and target areas are assisted to\n**infrastructure,** **services** **and** - Increased access to and use methodologies for social ensure a reduced risk of\n**build** **local** **capacity for** of social and economic capital and organizational conflict\n**collective** **action.** Priority infrastructure and services development)\nwill be given to areas not - Proportion of NSAP - Annual social assessments; - NACSA complements and\npreviously serviced by investments targeted to newly - NaCSA M&E data; extends the work of other\ngovernment, newly accessible accessible areas, & areas - M&E data of relevant line agencies and rninistries\nand the most vulnerable previously not served, and mninistries; in support of the PRSP's\npopulation groups within those vulnerable people within these - Beneficiary Assessment poverty reduction and\nareas. areas; (BAs) biannually; decentralization objectives\n\n                  - Proportion of sub-projects                   - Participatory evaluation\nthat reflect priorities of reports for a random sample of                   - NACSA is fully integrated\ntargeted communities and assisted conmmunities; into national planning and\nbeneficiaries; and                  - Technical audits resource allocation\n\n                  - Proportion of sub-projects frameworks (such as the\noperative 24emonths after National Recovery Strategy,\ncorpletion. the PRSP, and", "source": "fcv_pads_east_africa", "subset": "annotate_aj_part2", "spans": [{"key": "fcv_pads_east_africa:010417:29:1:0", "start": 862, "end": 876, "surface": "NaCSA M&E data", "probe_tag": "confusion", "probe_score": 0.2118, "luna_label": 0, "luna_reason": "Planned project monitoring data source, not evidence of already-used data."}, {"key": "fcv_pads_east_africa:010417:29:1:1", "start": 961, "end": 969, "surface": "M&E data", "probe_tag": "confusion", "probe_score": 0.1144, "luna_label": 1, "luna_reason": "Existing ministry monitoring data are declared as a project-reporting source."}]}, {"key": "aj2-018", "text": "INTERNATIONAL **DEVELOPMENT** ASSOCIATION\n\n\nCERTIFICATE\n\n\n**I** hereby certify that the foregoing is a true copy\n\nof the original in the archives of the International\n\nDevelopment Association.\n\n\n**Fb-SECUTARY**", "source": "fcv_pads_east_africa", "subset": "annotate_aj_part2", "spans": [{"key": "fcv_pads_east_africa:012627:6:0:0", "start": 137, "end": 191, "surface": "archives of the International\n\nDevelopment Association", "probe_tag": "confusion", "probe_score": 0.4516, "luna_label": 0, "luna_reason": "Archival provenance in a certification, not a cited or analyzed data resource."}]}, {"key": "aj2-019", "text": ". Over 80 percent of the population lives in rural areas, and agriculture is their main source of livelihood. It is one of\nthe world's poorest countries. In 2009/10 per capita GDP at current market price was estimated to be US$ 377.\n\nInstability remains a permanent feature in the volatile Horn of Africa. Tensions with Eritrea and instability in Somalia continue.\nEthiopia is subject to terms of trade shocks from international food and fuel prices and to large domestic weather-related shocks, as\nthe current East Africa drought demonstrates. Out of estimated 10m people in need of humanitarian assistance in the Horn of\nAfrica, 4.5 million are in Ethiopia mostly in southern regions close to Somali boarder. Ethiopian exports are dominated by\nagricultural commodities, which account for about 85 percent of total export earnings. Coffee is the most important permanent crop.\nEthiopia has one of the largest livestock herd in Africa, estimated at over 80 million.\n\nPoverty is widespread in the country. Ethiopia was ranked 157 out of 177 nations in the Human Development Index (HDI) of the\nUnited Nations Development Program (UNDP), based on 2010 data. However, during 2004-10 Ethiopia registered strong economic\nprogress with annual average GDP growth of 11% according to official estimates (7-8% according to IMF estimates), although\ncurrent inflation is close to 36% (December 2011). Despite a strong trade performance in recent months (partially due to credit\nrestrictions on imports) the external position continues to be vulnerable as progress in export diversification has been limited.\n\n**Sectoral and Institutional Context**", "source": "fcv_pads_east_africa", "subset": "annotate_aj_part2", "spans": [{"key": "fcv_pads_east_africa:013821:0:1:1", "start": 1144, "end": 1153, "surface": "2010 data", "probe_tag": "confusion", "probe_score": 0.4475, "luna_label": 1, "luna_reason": "UNDP data underpins the cited Human Development Index ranking."}]}, {"key": "aj2-020", "text": " proposed for the\nUganda health voucher project are not unreasonable.\n\n**�����** **�����������������������������������������������������**\nThis would be the first GPOBA voucher scheme. Voucher schemes are similar to health\ninsurance projects in many ways. In OBA-type health insurance projects “money follows\nthe patient” which means that patients choose a service provider of their liking. Copayments, in analogy to the voucher fee, are common in health insurances. Voucher\nschemes as the one proposed are compatible with health insurance projects and might be\ninstrumental in the build-up of cost-efficient and stable health insurance programs.\nMbarara, Kiruhura, Isingiro and Ibanda. The pilot was officially launched on 29th July\n2006 and will run until September 2007.\nProject results to date include:\n\n�� Over 20 treatment facilities accredited with 15 OBA STD Treatment Centers currently\nactive\n\n�� Service providers (SPs) trained in clinical diagnosis, laboratory diagnostic techniques and\nthe treatment of STDs\n\n�� Social marketing activities conducted to promote voucher distribution points and OBA\ntreatment sites, e.g. community sensitization sessions and radio talk shows\n\n\n7 Incremental benefit means the portion of the benefits of reduction of low birth weight cases (US$ 97.50) that\nare above the benefits of productivity loss (US$ 54.91). The result (US$ 42.59) can safely be attributed to\nbenefits not explained by productivity loss.\n8 Based on Demographic Health Survey and Islam, Gerdtham\n9 Data for maternal mortality based on World Health Report; WHO 2003, other data are conservative\nestimates.\n\n\n8", "source": "fcv_pads_east_africa", "subset": "annotate_aj_part2", "spans": [{"key": "fcv_pads_east_africa:014180:13:2:0", "start": 1463, "end": 1488, "surface": "Demographic Health Survey", "probe_tag": "confusion", "probe_score": 0.7823, "luna_label": 1, "luna_reason": "Survey is cited as the basis for the reported analysis."}, {"key": "fcv_pads_east_africa:014180:13:2:1", "start": 1511, "end": 1538, "surface": "Data for maternal mortality", "probe_tag": "confusion", "probe_score": 0.8031, "luna_label": 1, "luna_reason": "Existing maternal mortality data are identified as based on the World Health Report."}]}, {"key": "aj2-021", "text": "*1** **1.** Carring out an assessment of maintenance needs and the upgrading of\n\na road financing study\n2. Carrying out transport and poverty observatories in order to assess the\npoverty impact of the road investments\n**I**\n**3.** Carrying studies to support the preparation of the next phase of the\nRSDP and the Rural Road Access Program.\n#### **I**", "source": "fcv_pads_east_africa", "subset": "annotate_aj_part2", "spans": [{"key": "fcv_pads_east_africa:013459:5:2:0", "start": 120, "end": 155, "surface": "transport and poverty observatories", "probe_tag": "confusion", "probe_score": 0.3186, "luna_label": 0, "luna_reason": "The project plans to carry out observatories, producing data rather than using existing data."}]}, {"key": "aj2-022", "text": "7\n\n\nThis confirms that the Recipient is authorizing such persons to accept Secure Identification\nCredentials (SIDC) and to deliver the Applications and supporting documents to the Association by\nelectronic means. In full recognition that the Association shall rely upon such representations and\nwarranties, including without limitation, the representations and warranties contained in the _Terms and_\n_Conditions of Use of Secure Identification Credentials in connection with Use of Electronic Means to_\n_Process Applications and Supporting Documentation_ ( “ Terms and Conditions of Use of SIDC ” ), the\nRecipient represents and warrants to the Association that it will cause such persons to abide by those terms\nand conditions.\n\n\nThis Authorization replaces and supersedes any Authorization currently in the Association records\nwith respect to this Agreement.\n\n\n[Name], [position] Specimen Signature: ____________________\n\n[Name], [position] Specimen Signature: ____________________\n\n[Name], [position] Specimen Signature: ____________________\n\n\nYours truly,\n\n\n/ signed /\n\n\n______________", "source": "fcv_pads_east_africa", "subset": "annotate_aj_part2", "spans": [{"key": "fcv_pads_east_africa:000986:6:0:0", "start": 810, "end": 829, "surface": "Association records", "probe_tag": "confusion", "probe_score": 0.4157, "luna_label": 0, "luna_reason": "Routine administrative records mentioned for authorization, not substantive data use."}]}, {"key": "aj2-023", "text": "report should include budget allocation and expenditure data that should be consistent with the KPI\nreport.\n\n39. While the KPI data has quality issues particularly related with the comprehensiveness of\nthe data capture, the practice if encouraging. It is understood, the system building effort is a process\nthat passes through obstacles and challenges and the end result cannot be achieved in one go. The\neffort requires continuous engagement and resource. The aim is to streamline the thinking and\nnecessity of collecting data and measuring performance of procurement through KPIs. In the past\nnone of the regulatory bodies considered this to be their basic duty, instead investing all their time\non audit and trainings. The regulatory bodies are now putting great effort in the endeavor. It requires\ncollecting and entering data at each stage of procurement process for each item. The envisaged\ncapacity and streamlining of the system take time to reach a dependable stage. The initial aim was\nto make the exercise be a catalyst and eye opener for the regulatory bodies to improve the oversight\nsystem and achieve higher. And the exercise has fulfilled this objective. The below figures indicate\nthe results of the two indicators using data collected the past three years (EFY 2010-2012).\n\nTable 8: Average Bid Process Period [days]\n\n\n\n\n\n\n\n\n\nAmhara 51 52 44\nOromia 85 76 100\nSNNP 36 66 42\nTigray 52 47 59\n\nFigure 1: Share of Open Bid\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n14", "source": "fcv_pads_east_africa", "subset": "annotate_aj_part2", "spans": [{"key": "fcv_pads_east_africa:013439:13:0:1", "start": 123, "end": 131, "surface": "KPI data", "probe_tag": "confusion", "probe_score": 0.6392, "luna_label": 0, "luna_reason": "Generic KPI data is criticized, without an attributed finding tied to the span."}, {"key": "fcv_pads_east_africa:013439:13:0:2", "start": 1238, "end": 1273, "surface": "data collected the past three years", "probe_tag": "confusion", "probe_score": 0.5362, "luna_label": 1, "luna_reason": "Existing data support indicator results and tables for the past three years."}]}, {"key": "aj2-024", "text": "**_Leased Assets_** _as specified under paragraph 5.10_ of the Procurement\nRegulations: Leasing may be used for those contracts identified in the\nProcurement Plan tables.\n\n\n**_Procurement of Second Hand Goods_** _as specified under paragraph 5.11_ of\nthe Procurement Regulations – is allowed for those contracts identified in the\nProcurement Plan tables.\n\n\n**_Domestic preference_** _as specified under paragraph 5.51_ of the Procurement\nRegulations **_(Goods and Works)_** .\n\n\nGoods: is applicable for those contracts identified in the Procurement Plan\ntables;\n\n\nWorks: is applicable for those contracts identified in the Procurement Plan\ntables\n\n\n**Hands-on Expanded Implementation Support (HEIS)** _as specified under_\n_paragraphs 3.10 and 3.11_ of the Procurement Regulations is Applicable. _Not_\n_Applicable._\n\n\n**Other Relevant Procurement Information.**\n\n\n_Not Applicable._", "source": "fcv_pads_east_africa", "subset": "annotate_aj_part2", "spans": [{"key": "fcv_pads_east_africa:003085:1:0:0", "start": 146, "end": 169, "surface": "Procurement Plan tables", "probe_tag": "drop", "probe_score": 0.0249, "luna_label": 0, "luna_reason": "Routine procurement administration document, not substantive data use."}]}, {"key": "aj2-025", "text": "Public Disclosure Copy\n\n\n**The World Bank** Implementation Status & Results Report\nWater Management and Development Project (P123204)\n\n\nPHINDIRITBL\n\n\n New household sewer connections and improved latrines constructed under the project (Number, Custom)\n\n\nBaseline Actual (Previous) Actual (Current) End Target\n\n\nValue 2540.00 -- -- 4892.00\n\n\nDate 30-Jun-2012 -- -- 30-Dec-2018\n\n\nOverall Comments\n\n\n**Data on Financial Performance**\n\n\n**Disbursements (by loan)**\n\n\nProject Loan/Credit/TF Status Currency Original Revised Cancelled Disbursed Undisbursed Disbursed\n\n\nP123204 IDA-51270 Effective XDR 87.10 87.10 0.00 21.00 66.10 24%\n\n\n**Key Dates (by loan)**\n\n\nProject Loan/Credit/TF Status Approval Date Signing Date Effectiveness Date Orig. Closing Date Rev. Closing Date\n\n\nP123204 IDA-51270 Effective 26-Jun-2012 22-May-2013 12-Aug-2013 31-Dec-2018 31-Dec-2018\n\n\n**Cumulative Disbursements**\n\n\n12/28/2015 Page 7 of 8\n\nPublic Disclosure Copy", "source": "fcv_pads_east_africa", "subset": "annotate_aj_part2", "spans": [{"key": "fcv_pads_east_africa:010597:6:0:0", "start": 400, "end": 429, "surface": "Data on Financial Performance", "probe_tag": "drop", "probe_score": 0.0158, "luna_label": 0, "luna_reason": "Standalone table heading introducing project financial figures"}]}, {"key": "aj2-026", "text": "satisfied two or more rainy seasons; - Progress reports submitted\n2b.3 100% of houses benefit by implementing partners;\nmarginalized population                 - Beneficiary assessments\ngroups (female headed                 - NaCSA M&E data\nhouseholds, disabled and their\nfamilies); and\n2b.4 100% of beneficiaries\nwere selected by beneficiary\ncommunities.\n\n\n**3.** Proiect Management and\nInnovative Activities - NaCSA administrative data - Qualified implementing\n\n                                  - Capacity building event partners available to provide\n**3(a)** **Capacities of** assessments; capacity building and IEC\n**communities,** **chiefdomns,** **and** 3a.1 At least 5 successful - Participatory project activities at all levels;\n**district authorities to select,** capacity building events completion reviews; - A qualified full-time M&E\n**implement and maintain** carried out each year; - IDA supervision missions specialist is provided to\n**projects established** **and** NaCSA by another donor\n**strengthened** agency\n\n**3(b)** **Information, Education** 3b. 1 At least 40% of HHs are - Beneficiary assessments; - Non-NSAP activities\n**and Communication** aware of program; - NaCSA adrninistrative data; undertaken by NaCSA do not\n3b.2 At least 60%of chlefdom                  - IDA aide-memoires and detract from NaCSA ability to\nand district governments project status reports; and implement project.\naware of NSAP coverage,\ntargeting, methodology, and\nresults; and\n3b.3 At least 30% of general\npublic aware of NSAP                  - Public opinion survey\nprogram and results.\n\n\n**3(c)** **Performance** **of** 3c.1 M&E reports used for - NaCSA", "source": "fcv_pads_east_africa", "subset": "annotate_aj_part2", "spans": [{"key": "fcv_pads_east_africa:015753:31:0:0", "start": 226, "end": 240, "surface": "NaCSA M&E data", "probe_tag": "drop", "probe_score": 0.0279, "luna_label": 0, "luna_reason": "Names project M&E data without showing substantive analytical use"}, {"key": "fcv_pads_east_africa:015753:31:0:2", "start": 1188, "end": 1214, "surface": "NaCSA adrninistrative data", "probe_tag": "confusion", "probe_score": 0.4274, "luna_label": 0, "luna_reason": "Listed as planned monitoring verification, without evidence of actual data use."}]}, {"key": "aj2-027", "text": " capita -O 2 -0 5 Lower-middle-income _group_\nESports of goods and servic\"s\n\n\n**STRUCTURE ofthe ECONOMY**\n\n**1979** **1989** **1998** **1999** **Growth rates of output and Investment ()**\n_{%I ol GOP)_\nAgriculture 3.4 _.._ **_2._**\nIndustry 21.0 O.Manufacturing 5.6 **_-2_** **_94_** _as_ _se_ _s_\nServices **75.6** 6\n\nPrivate consumption **-r.**\nGeneral government consumplion **G**\nImports of goods and services\n\n\n\n**1979-89** **1989-99** **1998** **1999**\n_(average annual orowth)_\nAgriculture\n\n\n\nIndustry\n\n\n\nManufacturing\nServices\n\n\n\nPrivate consumption\nGenerai government consumption\nGross domestic investment\nImports of goods and services\nGross national product 1 7 **1.4**\n\n\nNote. 1999 data are preliminary estimates.\nThis table was produced from the Development Economics central database.\n\nThe diamonds show four kev midicators in the country (in bold) compared with its income-group average. 11 data are missing, Ihe diamond will", "source": "fcv_pads_east_africa", "subset": "annotate_aj_part2", "spans": [{"key": "fcv_pads_east_africa:010150:62:2:0", "start": 688, "end": 697, "surface": "1999 data", "probe_tag": "drop", "probe_score": 0.0227, "luna_label": 0, "luna_reason": "Generic data phrase lacks an attributed finding or demonstrated analytical use."}]}, {"key": "aj2-028", "text": "|Percentage|Value|0.00|20.00|100.00|\n|National SLM planning framework||Percentage|Date|03-Jan-2011|30-Jan-2013|30-Jun-2015|\n|National SLM planning framework||Percentage|Comments|No Framework exists|Task Force already in place<br>and drafting of report in<br>progress||\n\n\n\n**<u>Data on Financial Performance (as of 25-Jul-2011)</u>**\n\n\n**<u>Financial Agreement(s) Key Dates</u>**\n\n|Project|Ln/Cr/Tf|Status|Approval Date|Signing Date|Effectiveness Date|Original Closing Date|Revised Closing Date|\n|---|---|---|---|---|---|---|---|\n|P088600|TF-91616|Effective|17-Nov-2010|17-Nov-2010|17-Nov-2010|31-Dec-2015|31-Dec-2015|\n\n\n\n**<u>Disbursements (in Millions)</u>**\n\n|Project|Ln/Cr/Tf|Status|Currency|Original|Revised|Cancelled|Disbursed|Undisbursed|% Disbursed|\n|---|---|---|---|---|---|---|---|---|---|\n|P088600|TF-91616|Effective|USD|10.00|10.00|0.00|1.87|<br> 8.13|19.00|\n\n\n\n**<u>Disbursement Graph", "source": "fcv_pads_east_africa", "subset": "annotate_aj_part2", "spans": [{"key": "fcv_pads_east_africa:017990:2:1:0", "start": 277, "end": 306, "surface": "Data on Financial Performance", "probe_tag": "drop", "probe_score": 0.0397, "luna_label": 0, "luna_reason": "Standalone table heading, not a substantive data-use mention."}]}, {"key": "aj2-029", "text": "**Domestic preference** as specified under paragraph 5.51 of the Procurement Regulations **(Goods**\n**and Works)** .\n\n\nGoods: is applicable for those contracts identified in the Procurement Plan tables;\n\n\nWorks: is applicable for those contracts identified in the Procurement Plan tables\n\n\n**Other Relevant Procurement Information.**\n\n\n**Not Applicable**", "source": "fcv_pads_east_africa", "subset": "annotate_aj_part2", "spans": [{"key": "sample:fcv_pads_east_africa:015244:1:0:0", "start": 178, "end": 201, "surface": "Procurement Plan tables", "probe_tag": "drop", "probe_score": 0.0004, "luna_label": 0, "luna_reason": null}, {"key": "sample:fcv_pads_east_africa:015244:1:0:1", "start": 264, "end": 287, "surface": "Procurement Plan tables", "probe_tag": "drop", "probe_score": 0.0002, "luna_label": 0, "luna_reason": null}]}, {"key": "aj2-030", "text": "|KE-MOH-46134-NC-RFQ /<br>Accomodation on full board<br>basis for141 pax for 21 days<br>during the training for<br>research assistants for the<br>KHFA/SDI Survey at<br>approximately 9,000 kshs<br>per person per day|IDA / 53670|Col3|Post|Direct Selection|Direct|Col7|Col8|0.00|Pending<br>Implementati<br>on|Col11|Col12|Col13|Col14|2018-02-01|Col16|2018-02-06|Col18|Col19|Col20|Col21|Col22|Col23|Col24|2018-03-13|Col26|2018-09-09|Col28|\n|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n|KE-MOH-65434-NC-RFQ /<br>designing and printing of<br>service charters in kiswahili<br>and vernacular as per<br>specifications including cost<br>of transporting the service<br>charters to the respective<br>sixteen county headquarters.<br>|IDA / 53670||Post|Request for<br>Quotations|Limited<br>|", "source": "fcv_pads_east_africa", "subset": "annotate_aj_part2", "spans": [{"key": "fcv_pads_east_africa:018870:3:0:0", "start": 146, "end": 161, "surface": "KHFA/SDI Survey", "probe_tag": "drop", "probe_score": 0.0204, "luna_label": 0, "luna_reason": "Project procurement supports training for a planned survey; no existing data use is shown."}]}, {"key": "aj2-031", "text": " capita -O 2 -0 5 Lower-middle-income _group_\nESports of goods and servic\"s\n\n\n**STRUCTURE ofthe ECONOMY**\n\n**1979** **1989** **1998** **1999** **Growth rates of output and Investment ()**\n_{%I ol GOP)_\nAgriculture 3.4 _.._ **_2._**\nIndustry 21.0 O.Manufacturing 5.6 **_-2_** **_94_** _as_ _se_ _s_\nServices **75.6** 6\n\nPrivate consumption **-r.**\nGeneral government consumplion **G**\nImports of goods and services\n\n\n\n**1979-89** **1989-99** **1998** **1999**\n_(average annual orowth)_\nAgriculture\n\n\n\nIndustry\n\n\n\nManufacturing\nServices\n\n\n\nPrivate consumption\nGenerai government consumption\nGross domestic investment\nImports of goods and services\nGross national product 1 7 **1.4**\n\n\nNote. 1999 data are preliminary estimates.\nThis table was produced from the Development Economics central database.\n\nThe diamonds show four kev midicators in the country (in bold) compared with its income-group average. 11 data are missing, Ihe diamond will", "source": "fcv_pads_east_africa", "subset": "annotate_aj_part2", "spans": [{"key": "fcv_pads_east_africa:017114:62:2:0", "start": 688, "end": 697, "surface": "1999 data", "probe_tag": "drop", "probe_score": 0.0227, "luna_label": 0, "luna_reason": "Generic date-qualified data lacks an attributed finding or demonstrated analytical use."}]}, {"key": "aj2-032", "text": " capita -O 2 -0 5 Lower-middle-income _group_\nESports of goods and servic\"s\n\n\n**STRUCTURE ofthe ECONOMY**\n\n**1979** **1989** **1998** **1999** **Growth rates of output and Investment ()**\n_{%I ol GOP)_\nAgriculture 3.4 _.._ **_2._**\nIndustry 21.0 O.Manufacturing 5.6 **_-2_** **_94_** _as_ _se_ _s_\nServices **75.6** 6\n\nPrivate consumption **-r.**\nGeneral government consumplion **G**\nImports of goods and services\n\n\n\n**1979-89** **1989-99** **1998** **1999**\n_(average annual orowth)_\nAgriculture\n\n\n\nIndustry\n\n\n\nManufacturing\nServices\n\n\n\nPrivate consumption\nGenerai government consumption\nGross domestic investment\nImports of goods and services\nGross national product 1 7 **1.4**\n\n\nNote. 1999 data are preliminary estimates.\nThis table was produced from the Development Economics central database.\n\nThe diamonds show four kev midicators in the country (in bold) compared with its income-group average. 11 data are missing, Ihe diamond will", "source": "fcv_pads_east_africa", "subset": "annotate_aj_part2", "spans": [{"key": "fcv_pads_east_africa:008672:62:2:0", "start": 688, "end": 697, "surface": "1999 data", "probe_tag": "drop", "probe_score": 0.0227, "luna_label": 0, "luna_reason": "Generic data phrase states preliminary status without an attributed finding."}, {"key": "fcv_pads_east_africa:008672:62:2:1", "start": 758, "end": 796, "surface": "Development Economics central database", "probe_tag": "keep", "probe_score": 0.9824, "luna_label": 1, "luna_reason": "Named database provides data underlying the presented economic table."}]}, {"key": "aj2-033", "text": "2. Broader social capital building outcome: Capacity building interventions for implementing\npartners and local authorities would include conflict resolution training, and emphasize sub-project\ndesign and supervision processes which build social capital and mutual accountability between\ncommunities and the array of support organizations and institutions.\n\n\n3. Intra-community equity outcomes: To address intra-community equity issues in a more\nsystematic manner, NaCSA would revise its Operations Manual to enhance procedures for community\nneeds identification and sub-project selection. The enhanced guidelines would include, inter alia, a\nrequirement for implementing partners to fill out a Community Assessment Form. This would include\ninformation on community population (by gender and age group), basic infrastructure, main income\ngenerating activities, housing, organization, forms and levels of outside assistance, and particularly\nvulnerable groups.\n\n6.5 How will the project monitor performance in terms of social development outcomes?\n\nA Social Assessment is under preparation. It is being designed so as to ensure that the project\nresponds to social development concerns by identifying the opportunities, constraints and social risks\n\n\n\ninherent in the project and translating these ideas into practical design and implementation measures.\nThe World Bank's Social Capital Assessment Tool (SOCAT) and instruments for analyzing local\ninstitutions will be used in the Social Assessment. Subsequent iterative rounds of social analysis using\nsimple locally adapted variants of these tools would continue during the duration of the project to collect\nand analyze data on social development issues. These would include associational memberships and\ntrust, the process of creation and destruction of social capital and data on groups and networks,\n\n\n\nsubjective well-being, political engagement, sociability, community activities, cohesion and\ncommunication. The Assessment would thus provide baseline data on social issues, recommend and\n\n\n\napply social capital measurement tools, and provide a framework for continuing social analysis\nthroughout the project.\n\n\n\n7. Safeguard Policies:\n7.1 Are any of the following safeguard policies triggered by the prcect?\n\n     - '& **~** P19 ~ f _-", "source": "fcv_pads_east_africa", "subset": "annotate_aj_part2", "spans": [{"key": "fcv_pads_east_africa:009754:24:0:0", "start": 1670, "end": 1703, "surface": "data on social development issues", "probe_tag": "drop", "probe_score": 0.0226, "luna_label": 0, "luna_reason": "Project plans to collect and analyze this data during implementation."}]}, {"key": "aj2-034", "text": "Public Disclosure Copy\n\n\n**The World Bank** Implementation Status & Results Report\nKenya Urban Water and Sanitation OBA Fund for Low Income Areas (P132979)\n\n\nPHINDIRITBL\n\n\n Improved community water points constructed or rehabilitated under the project (Number, Core)\n\n\nBaseline Actual (Previous) Actual (Current) End Target\n\n\nValue 0.00 -- 58.00 140.00\n\n\nDate 15-May-2014 -- 30-Jun-2015 31-Dec-2017\n\n\nPHINDIRITBL\n\n\n Number of public toilets constructed under the project (Number, Custom)\n\n\nBaseline Actual (Previous) Actual (Current) End Target\n\n\nValue 0.00 -- -- 30.00\n\n\nDate 15-May-2014 -- -- 31-Dec-2017\n\n\nOverall Comments\nData recorded in first OVR for Muranga South (interim verification)\n\n\n**Data on Financial Performance**\n\n\n**Disbursements (by loan)**\n\n\nProject Loan/Credit/TF Status Currency Original Revised Cancelled Disbursed Undisbursed Disbursed\n\n\nP132979 TF-16395 Effective USD 11.84 11.84 0.00 1.00 10.84 8%\n\n\n**Key Dates (by loan)**\n\n\nProject Loan/Credit/TF Status Approval Date Signing Date Effectiveness Date Orig. Closing Date Rev. Closing Date\n\n\nP132979 TF-16395 Effective 05-Sep-2014 05-Sep-2014 03-Dec-2014 30-Jun-2018 30-Jun-2018\n\n\n**Cumulative Disbursements**\n\n\n10/22/2015 Page 5 of 6\n\nPublic Disclosure Copy", "source": "fcv_pads_east_africa", "subset": "annotate_aj_part2", "spans": [{"key": "fcv_pads_east_africa:015061:4:0:1", "start": 700, "end": 729, "surface": "Data on Financial Performance", "probe_tag": "drop", "probe_score": 0.0285, "luna_label": 0, "luna_reason": "Standalone table heading, not an independently cited data resource."}]}, {"key": "aj2-035", "text": " capita -O 2 -0 5 Lower-middle-income _group_\nESports of goods and servic\"s\n\n\n**STRUCTURE ofthe ECONOMY**\n\n**1979** **1989** **1998** **1999** **Growth rates of output and Investment ()**\n_{%I ol GOP)_\nAgriculture 3.4 _.._ **_2._**\nIndustry 21.0 O.Manufacturing 5.6 **_-2_** **_94_** _as_ _se_ _s_\nServices **75.6** 6\n\nPrivate consumption **-r.**\nGeneral government consumplion **G**\nImports of goods and services\n\n\n\n**1979-89** **1989-99** **1998** **1999**\n_(average annual orowth)_\nAgriculture\n\n\n\nIndustry\n\n\n\nManufacturing\nServices\n\n\n\nPrivate consumption\nGenerai government consumption\nGross domestic investment\nImports of goods and services\nGross national product 1 7 **1.4**\n\n\nNote. 1999 data are preliminary estimates.\nThis table was produced from the Development Economics central database.\n\nThe diamonds show four kev midicators in the country (in bold) compared with its income-group average. 11 data are missing, Ihe diamond will", "source": "fcv_pads_east_africa", "subset": "annotate_aj_part2", "spans": [{"key": "fcv_pads_east_africa:013667:62:2:0", "start": 688, "end": 697, "surface": "1999 data", "probe_tag": "drop", "probe_score": 0.0227, "luna_label": 0, "luna_reason": "Generic date-qualified data mention lacks an attributed finding or demonstrated analytical use."}, {"key": "fcv_pads_east_africa:013667:62:2:1", "start": 758, "end": 796, "surface": "Development Economics central database", "probe_tag": "keep", "probe_score": 0.9824, "luna_label": 1, "luna_reason": "Named database cited as the source of the table’s economic data."}]}, {"key": "aj2-036", "text": "s. Most cardholders are in\nthe middle of the wealth distribution, with a significant minority at the top. Anecdotal\nevidence about implementation suggests that individuals are only required to present\nevidence of caste certification, domicile and birth registration for verification by the local\nauthorities (MODE, 2000); <sup>9</sup> [^9: We did not carry out field research hence it is difficult to confirm exactly what is required. See\nhttp://faridabad.nic.in/Administration/women&.htm#ABAD] in practice, the BPL card may not always be requested for\nparticipation in the program. Due to the lack of data for NFHS-1 and 2 and these other\nissues, we are not able to rely on the BPL cardholder information.\n\n\nFor Haryana, the Planning Commission released rural/urban poverty headcount ratios of\n28%/16% in 1993-1994 and 8%/10% in 1999-2000. However, subject to concerns that\nthese figures were not comparable, for 2004-5, the Commission released two sets of\nnumbers based on both methodologies. The 2004-5 figures are either 14%/15%\n(comparable to 1993-1994) or 9%/11% (approximately but not precisely comparable to\n1999-2000). On the other hand, Deaton (2003) computes considerably lower estimates of\n17% /11% for the rural/urban sector in 1993-4 and 6% / 5% in 1999-2000. Since our\nprimary objective is to capture those most likely to receive ABAD benefits, rather than\n\n\n8 Below-poverty line (BPL) censuses were conducted in 1992, 1997 and 2002. The 1992 BPL census\nidentified BPL on the basis of self-reported income. The 1997 BPL first screened out the ‘visibly non-poor’\non the basis of asset ownership and annual income. A household was then declared poor if their per capita\nconsumption expenditure was less than the official rupee poverty line adopted by the Planning\nCommission. The identification formula was changed for the 2002 BPL census, using a proxy for means\ntesting based on", "source": "general_prwp", "subset": "annotate_aj_part2", "spans": [{"key": "prwp:004055:8:1:2", "start": 1453, "end": 1468, "surface": "1992 BPL census", "probe_tag": "keep", "probe_score": 0.9473, "luna_label": 1, "luna_reason": "Named existing census with documented poverty-identification methodology."}]}, {"key": "aj2-037", "text": "ratio of non-performing loans to total loans, the ratio of equity to capital, and the return over\n\n\nassets. _S_ stands for systemic risk; it is a matrix that includes measures of country and exchange\n\n\nrate risks. The former is captured by the spread on Argentine and, separately, Uruguayan\n\n\nsovereign bonds over comparable U.S. bonds, as expressed in Argentina’s Emerging Market\n\n\nBond Index Plus or EMBI+ and the Uruguay Bond Index or UBI, respectively. Exchange rate\n\n\nrisk (or more precisely the currency premium) is measured by the 12-month forward (NDF)\n\n\nexchange rate relative to the spot exchange rate for Argentina. For Uruguay, we use the spread of\n\n\nthe average interest rate on peso time deposits (with maturity of more than one month and less\n\n\nthan six months, in the top private banks) relative to the rate on similar dollar deposits. _E_ stands\n\n\nfor exposure and is a matrix that includes indicators of individual banks’ exposure to systemic\n\n\nrisks. More precisely, we use the share of government debt (bonds and loans) over total bank\n\n\nassets as a proxy for exposure to “country” (sovereign default) risk. For exposure to exchange\n\n\nrate risk, we use the ratio of dollar loans over bank capital for Argentina and the ratio of dollars\n\n\nloans over assets for Uruguay. <sup>12</sup> [^12: The traditional way of measuring exchange rate risk is the difference between dollar assets and liabilities.\nHowever, here we are more interested in the embedded credit risk that arises from the dollar loans that banks often\ngrant to debtors without dollar incomes. For Uruguay, we examine the ratio of dollar loans to assets, since equity\nturned negative for some banks during the crisis period.] All regressions control for bank specific effects, α _i_ ..\n\n\nBank fundamentals and the indicators of bank exposure to systemic risks are lagged for\n\n\ntwo reasons. First, in both countries, balance sheet data are released to the public by bank\n\n\nregulators with a delay of three to", "source": "general_prwp", "subset": "annotate_aj_part2", "spans": [{"key": "prwp:002694:14:0:0", "start": 365, "end": 398, "surface": "Emerging Market\n\n\nBond Index Plus", "probe_tag": "keep", "probe_score": 0.9269, "luna_label": 1, "luna_reason": "Named bond index measures sovereign spread and country risk."}]}, {"key": "aj2-038", "text": "3.2.1 Macro stabilization variables\n\n\nWe include the log of _government consumption_ as a share of GDP, _lkg_, calculated\nas the log of csh_g from the PWT 10.0. This variable is supposed to capture growthreducing effects through distortionary taxation (Afonso and Furceri 2010) or public\ndebt issuance. The negative association with growth is motivated by the fact that\nwe include the positive effects that government consumption may have on growth\nseparately, for example, through spending on infrastructure. As our model describes\nlong-run growth, it is also important not to conflate the short-term positive stimulus\neffect that increased government consumption can have during economic\ndownturns. <sup>7</sup> [^7: For similar reasons, we also do not include fiscal deficit variables, which are highly cyclical and hence tend\nto smooth out over the five-year averages.]\n\n\n_Inflation_ is measured as the log change of _v_c/q_c_ (household consumption in\ncurrent national prices/household consumption in constant national 2017 prices)\nfrom the national accounts module of the PWT 10.0, which has greater availability\nthan inflation data from the World Bank’s World Development Indicators (WDI). <sup>8</sup> [^8: We add 1 to this variable to avoid negative numbers, which cannot be translated into logs.]\n\n\nThe _real exchange rate_, _lrer_, is calculated as the log of the GDP price level (in PPP)\nover the nominal exchange rate: _pl_gdpo/xr_, both taken from the PWT 10.0. Since\n_xr_ is measured as national currency/US$, an increase in _lrer_ reflects a real\nappreciation, which is expected to have a negative effect on output and growth\nthrough various channels (e.g., Rapetti 2019; Levy-Yeyati, Sturzenegger, and\nGluzmann 2013). <sup>9</sup>\n\n\n3.2.2 Financial variables\n\n\nTo measure countries’ _financial development_, we use the log of domestic credit to\nthe private sector", "source": "general_prwp", "subset": "annotate_aj_part2", "spans": [{"key": "sample:prwp:000876:9:0:0", "start": 151, "end": 159, "surface": "PWT 10.0", "probe_tag": "keep", "probe_score": 0.9579, "luna_label": 1, "luna_reason": null}, {"key": "sample:prwp:000876:9:0:1", "start": 1078, "end": 1086, "surface": "PWT 10.0", "probe_tag": "keep", "probe_score": 0.9981, "luna_label": 1, "luna_reason": null}, {"key": "sample:prwp:000876:9:0:2", "start": 1124, "end": 1138, "surface": "inflation data", "probe_tag": "keep", "probe_score": 0.9634, "luna_label": 1, "luna_reason": null}, {"key": "sample:prwp:000876:9:0:3", "start": 1161, "end": 1189, "surface": "World Development Indicators", "probe_tag": "keep", "probe_score": 0.9877, "luna_label": 0, "luna_reason": null}, {"key": "sample:prwp:000876:9:0:4", "start": 1466, "end": 1474, "surface": "PWT 10.0", "probe_tag": "keep", "probe_score": 0.9981, "luna_label": 1, "luna_reason": null}]}, {"key": "aj2-039", "text": "_  _iED_ (2.2)\n\n\n_k_ _k_\n(Here <sup></sup> _i_ <sup>for</sup> <sup>_k=D_</sup> <sup>,</sup> <sup>_ED_</sup> <sup>are zero-mean regression error terms and</sup>  _k_,  are parameters.) Thus\n\n\nequation (2.1) minus (2.2) gives how the overall participation rate varies with _H_ . The regression\n\n\ncoefficient of demand for MGNREGS (based on the NSS responses) on the state poverty rate is\n\n\n0.583 (st. error=0.189), meaning that a ten percentage point increase in the poverty rate comes\n\n\nwith about a 6 percentage point increase in the share of rural households demanding MGNREGS\n\n\nwork, on average. The regression coefficient of _ED_ on _H_ is 0.434 (st.error=0.097). The net effect\n\n###### (the estimate of  D   ED ) is 0.149, but it is not significantly different from zero\n\n\n(st.error=0.293). Statistically, the two opposing effects can be said to cancel each other out,\n\n11 Note that this third reason for the direct effect of poverty is not consistent with a model of public decision making\nbased on standard utilitarian calculus. For then one would expect the policy weight on accommodating the demand\nfor work to be higher in states with a higher share of poor people who need that work more than the non-poor.\n\n\n7", "source": "general_prwp", "subset": "annotate_aj_part2", "spans": [{"key": "prwp:005178:8:1:0", "start": 347, "end": 360, "surface": "NSS responses", "probe_tag": "keep", "probe_score": 0.9321, "luna_label": 1, "luna_reason": "NSS responses underpin the reported regression coefficient and poverty-rate finding."}]}, {"key": "aj2-040", "text": "I market organization rating below or above the median<br>across countries. BTI market organization is based on responses to the question: “To what level have the fundamentals of<br>market-based competition developed?” The figure shows average values in 30 percentiles of log(labor productivity)—that is,|<br>_Sources:_ Authors’ calculations based on the most recent Enterprise Surveys COVID-19 Follow-up Surveys and Enterprise<br>Surveys for 23 countries in Europe and Central Asia; Bertelsmann Stiftung Transformation Index (BTI) 2020.<br>_Note:_ Low or high market competition is defined as having a BTI market organization rating below or above the median<br>across countries. BTI market organization is based on responses to the question: “To what level have the fundamentals of<br>market-based competition developed?” The figure shows average values in 30 percentiles of log(labor productivity)—that is,|\n\n\n20", "source": "general_prwp", "subset": "annotate_aj_part2", "spans": [{"key": "prwp:000186:21:2:1", "start": 484, "end": 525, "surface": "Bertelsmann Stiftung Transformation Index", "probe_tag": "keep", "probe_score": 0.9207, "luna_label": 1, "luna_reason": "Named index cited as a source for authors’ calculations and figure."}]}, {"key": "aj2-041", "text": ". changes\nin _Mi2_ for all _i_ importers) and would make us stray from this paper’s objective. Leaving this question to\nfuture research, our concern remains with bilateral trade; MR is only relevant for our efforts to calculate\nthe bilateral comparative static effects correctly.\n\n#### **4. Data and estimation**\n\n\nWe use the same data as Baier & Bergstrand (2007), <sup>11</sup> [^11: We thank Scott Baier and Jeff Bergstrand for facilitating our use of the data.\n12The analyses covers the period from 1960 till 2000 and a total of 119 new agreements have been implemented\nsince 2000, with about 50% of them being S-S and 40% being N-S agreements.] which come from various sources: nominal\nbilateral trade flows for 96 trading partners and at 5 year intervals from 1960 till 2000 come from the\nInternational Monetary Fund's Direction of Trade Statistics; nominal GDPs are from the World Bank's\nWorld Development Indicators (2003); bilateral distances, language and adjacency dummy variables\nwere compiled from the CIA Factbook; and the FTA dummy variable was calculated using appendices in\nLawrence (1996) and Frankel (1997) as well as various websites detailed in the Data Appendix. It includes\nfull FTAs and customs unions but not partial agreements. 10% of them are between Northern countries,\n31% between Northern and Southern countries and 49% between countries from the South. A list of the\ntrade agreements analyzed, including a classification of them into North-North, North-South and SouthSouth FTAs is detailed in the Data Appendix together with a table containing the 96 potential trading\npartners. <sup>12</sup>\n\n\nOur estimation approach draws on that of Baier & Bergstrand (2007) but instead of having only one\ndummy for the FTA, we split agreements into those between two Northern countries, between two\nSouthern countries and between a Northern country and a Southern country. The criteria to classify\n\n10 For example, countries 1 and 2 can be Chile", "source": "general_prwp", "subset": "annotate_aj_part2", "spans": [{"key": "sample:prwp:004808:11:1:0", "start": 825, "end": 854, "surface": "Direction of Trade Statistics", "probe_tag": "keep", "probe_score": 0.9917, "luna_label": 1, "luna_reason": "Provides bilateral trade-flow data used in the paper’s estimation."}, {"key": "sample:prwp:004808:11:1:1", "start": 895, "end": 923, "surface": "World Development Indicators", "probe_tag": "keep", "probe_score": 0.9824, "luna_label": 1, "luna_reason": null}, {"key": "sample:prwp:004808:11:1:2", "start": 1015, "end": 1027, "surface": "CIA Factbook", "probe_tag": "keep", "probe_score": 0.9904, "luna_label": 1, "luna_reason": null}]}, {"key": "aj2-042", "text": " as measured\n\nby log of GDP per capita (when the outcome variable is WGI).\n\nSince we do not have all the country-year observations for these control variables (except for\n\nthe WGI), we impute for the missing observations with the nearest available values. The\n\npercentage of missing values ranges from 1 percent (agriculture, forestry, and fishing added values\n\nas a share of GDP) to more than 25 percent (gross primary school enrollment). We focus on the\n\nresulting balanced panel data for 159 countries with data for the SPI, WGI, and other control\n\nvariables between 2016 and 2022. The main reason that most countries do not have an overall SPI\n\nscore in 2016 is due to data unavailability from Open Data Watch’s Open Data Inventory (ODIN),\n\nwhich was used for the SPI measures of data openness and geospatial information. The other\n\nreasons are missing human capital index scores or trade data. As such, Equation (5) is our preferred\n\nmodel for analysis but Equation (6) can offer useful robustness checks.\n\nIt is important to emphasize that these econometric models are unlikely to allow us to identify\n\nthe causal impacts of the SPI on GDP growth or governance (which is beyond the scope of analysis\n\nin this paper). Yet, these models can help shed exploratory, useful insights on the correlational\n\nrelationship between a country’s statistical performance and its economic growth and governance.\n\n\n22", "source": "general_prwp", "subset": "annotate_aj_part2", "spans": [{"key": "prwp:001471:23:1:2", "start": 887, "end": 897, "surface": "trade data", "probe_tag": "confusion", "probe_score": 0.6449, "luna_label": 0, "luna_reason": "States missing data availability without an analyzed finding or substitute use."}]}, {"key": "aj2-043", "text": "- Ideally there should be one, clearly identified, central location where consumers of financial\nservices and products can go when they have complaints or inquiries.\n\n  - The central complaints office should have a toll-free telephone line so that in case of a dispute,\nanyone from anywhere in the country can obtain information about financial services and\nconsumers’ legal rights.\n\n  - Consumers should be able to submit their complaints by email, by postal mail, or by visiting the\npremises of the complaints office.\n\n  - Statistics on consumer complaints should be analyzed and published—and used to identify future\nimprovements in the financial consumer protection framework.\n\n  - Policy-makers should consider alternatives to courts, such as a financial ombudsman office, that\ncan take and enforce decisions regarding consumer claims for small amounts of money.\n\n  - A financial ombudsman office may be set up under a professional association or as an\nindependent statutory ombudsman.\n\n\n**Financial Literacy & Education**\n\n\n  - The impact of different techniques of delivering financial education on financial literacy and on\nconsumer behavior is evolving. Programs to improve financial education should be rigorously\ntested and evaluated.\n\n  - Financial education for consumers should be focused on “teachable moments.”\n\n  - Middle and high-income countries should have national strategies on financial education and\nfinancial literacy. Low-income countries should develop financial education programs according\nto the country’s level of institutional capacity.\n\n  - The first step is to conduct a national survey of financial literacy, to be used as baseline. Followup surveys of financial literacy should be conducted every three to five years.\n\n  - Qualitative monitoring of consumer protection should be conducted, e.g. using “mystery\nshoppers”.\n\n  - Global surveys should be conducted of legal and regulatory frameworks for financial consumer\nprotection, levels of financial literacy, and patterns of financial consumer behavior.\n\n\n5", "source": "general_prwp", "subset": "annotate_aj_part2", "spans": [{"key": "prwp:004516:11:0:1", "start": 1605, "end": 1642, "surface": "national survey of financial literacy", "probe_tag": "confusion", "probe_score": 0.457, "luna_label": 0, "luna_reason": "Survey is planned for future baseline data collection."}]}, {"key": "aj2-044", "text": "**The demography of youth in developing countries**\n\n**and its economic implications**\n\n\n**David Lam**\n**November 2005**\n\n\n**Appendix**\n\n\n**Appendix A. Assumptions used in the United Nations Population Projections**\n\n\n(taken from http://esa.un.org/unpp/index.asp?panel=4 on October 31, 2005)\n\n\n**ASSUMPTIONS UNDERLYING THE RESULTS OF THE** **_2004 REVISION OF WORLD_**\n\n\n**_POPULATION PROSPECTS_**\n\n\nThe future population of each country is projected from an estimated population for 1 July 2005. Because\n\n\nactual population data for 2005 are not yet available, the 2005 estimate is based upon the most recent population\n\n\ndata available for each country, derived usually from a census or population register, updated to 2005 using all\n\n\navailable data on fertility, mortality and international migration. In cases where very recent data are not\n\n\navailable, estimated demographic trends are short term projections from the most recent available data.\n\n\nPopulation data from all sources are evaluated for completeness, accuracy and consistency, and adjusted where\n\n\nnecessary.\n\n\nTo project population until 2050, the United Nations Population Division applies assumptions regarding\n\n\nfuture trends in fertility, mortality, and migration. Because future trends cannot be known with certainty, a\n\n\nnumber of projection variants are produced.\n\n\nThe _2004 Revision_ includes six projection variants. The results for four are available on the web. These\n\n\nfour variants differ among themselves with respect to the assumptions made regarding the future course of\n\n\nfertility.\n\n\nTo describe the different projection variants, the assumptions made regarding fertility, mortality and\n\n\ninternational migration are described first.\n\n\n**A. Fertility assumptions: Convergence toward total fertility below replacement**\n\n\n41", "source": "general_prwp", "subset": "annotate_aj_part2", "spans": [{"key": "prwp:003235:40:0:0", "start": 514, "end": 529, "surface": "population data", "probe_tag": "confusion", "probe_score": 0.7809, "luna_label": 1, "luna_reason": "Unavailable 2005 data motivate estimates based on the most recent available population data."}, {"key": "prwp:003235:40:0:2", "start": 679, "end": 708, "surface": "census or population register", "probe_tag": "confusion", "probe_score": 0.5321, "luna_label": 1, "luna_reason": "Existing population sources underpin the 2005 population estimate."}]}, {"key": "aj2-045", "text": " bags of maize harvested by the survey respondent’s household in the 2010/11 season.\n\n- The variable _bags increase_ quantifies the increase in the aforementioned variable between the 2009/10 and 2010/11 seasons.\n\n- The variable _bags/h_ quantifies the numbers of bags of maize harvested per hectare by the survey respondent’s household in the 2010-11\n\nseason.\n\n- The variable _bags/h increase_ quantifies the increase in the aforementioned variable between the 2009/10 and 2010/11 seasons. This is the\n\nregistered outcome variable.\n\n- _Damage_ variables are dummies that are coded to 1 if the household reported a damage of this type to its farming plot during the 2010/11\n\nseason, and 0 otherwise. Specifications (2), (4)), (6), and (8) use these as control variables.\n\n- To adjust for the spatial correlation of regression residuals, standard errors were clustered at the distributor level. Robust standard errors in\n\nare brackets.\n\n- ** denotes p<0.05; *** denotes p<0.01.\n\n\nSource: Author’s analysis based on data described in the text.\n\n\n34", "source": "general_prwp", "subset": "annotate_aj_part2", "spans": [{"key": "prwp:006777:35:2:0", "start": 1014, "end": 1040, "surface": "data described in the text", "probe_tag": "confusion", "probe_score": 0.4274, "luna_label": 1, "luna_reason": "Data are cited as the basis of the author’s analysis."}]}, {"key": "aj2-046", "text": "the risk before completion. The ATTs we estimate are 4 percentage points for events and\n10 percentage points for fatalities, and both are statistically significant. We conclude from\nthis and the earlier results that violence is reduced by about 5 to 10 percentage points with\nthe completion of a project.\n\nThe dynamics of the effect are extremely interesting. Violence drops fast after completion\nand finds its minimum in the year after completion. It then rebounds, and the point estimate\nis close to 0 three years after completion. This suggests that road rehabilitation does not\nhave a lasting effect on violence in our sample but only reduce violence for a few years. This\neffect is very closely aligned with the decay factor we estimated from the remote sensing\nwhich reinforces the idea that road degradation might indeed significantly enable violence.\n\n\nFigure 12: Roads and Events: PreMDiD\n\n\n**Notes** : Figure shows the effect of road completion at year 0 compared to a control group that is matched by violence\n\nprediction in year -1.\n\n\nFigure 13: Roads and Fatalities: PreMDiD\n\n\n**Notes** : Figure shows the effect of road completion at year 0 compared to a control group that is matched by violence\n\nprediction in year -1.\n\n\n23", "source": "general_prwp", "subset": "annotate_aj_part2", "spans": [{"key": "prwp:001238:24:0:0", "start": 752, "end": 766, "surface": "remote sensing", "probe_tag": "confusion", "probe_score": 0.6245, "luna_label": 1, "luna_reason": "Remote sensing data informed the estimated decay factor supporting the violence analysis."}]}, {"key": "aj2-047", "text": "were about 9 percent higher in the Bureau of Economic Analysis data relative to the data of the Bureau of\nLabor Statistics. In addition, they find that the two data series consistently grew apart from 1992 to 2000. As\nunderlined by Garner and Short (2001), the reason for this mismatch may be that respondents in both cases\nhave mistaken and biased ideas about the market values of their dwellings or that the reported rental equivalence\nvalues are likely to be capturing variations in housing and neighborhood quality that hedonic approaches do\nnot capture. Corradin, Fillat, and Vergara-Alert 2017 make an argument that is similar to the latter point.\nMoreover, owners may express above-market evaluations of their dwellings because of a special attachment for\nspecific features of their homes, especially if they designed or built the homes. Heston and Nakamura (2009)\ncall this the owner pride factor. Van der Cruijsen, Jansen, and van Rooij (2018) provide a review of possible\nbehavioral reasons beyond the bias of homeowner valuations. They compare the self-assessed homeowner\nvaluations with appraisals of the same housing administrated by the municipality to which the housing belongs\nfor tax purposes. They find that the median respondent overestimates the true value by 11 percent.\n\n\nSometimes, the same survey supplies enough information to check the accuracy of homeowner selfassessments. Van der Cruijsen, Jansen, and van Rooij (2018) and Gao and Liang (2019) compare the two sets\nof values reported by respondents in, respectively, the DNB Household Survey in the Netherlands and the\nChina Household Finance Survey: the self-assessed current value and the purchase price for the same dwelling,\nwhich is updated using an evaluation of the fluctuations in housing prices in the same neighborhood or region\nover time. Both contributions find that households systematically overestimate their home values. Benítez-Silva\net al. (2015) exploit the longitudinal panel structures of the Health and Retirement Study and the American\nHousing Survey", "source": "general_prwp", "subset": "annotate_aj_part2", "spans": [{"key": "prwp:000383:6:0:0", "start": 35, "end": 67, "surface": "Bureau of Economic Analysis data", "probe_tag": "keep", "probe_score": 0.9688, "luna_label": 1, "luna_reason": "Named BEA data series compared with BLS data in an analysis."}, {"key": "prwp:000383:6:0:3", "start": 1598, "end": 1628, "surface": "China Household Finance Survey", "probe_tag": "confusion", "probe_score": 0.7658, "luna_label": 1, "luna_reason": "Survey values are compared and linked to systematic household overestimation findings."}]}, {"key": "aj2-048", "text": "characteristics in order to improve the precision of estimates (Section 5.1), but also in\n\n\norder to minimize a systematic tendency to overstate poverty in truly non-poor\n\n\ncommunities and understate poverty in truly poor communities.\n\n\n<u>5.4 Correlation</u>\n\n\nA further way to consider the reliability of the small area estimates is to examine\n\n\nthe correlation between the predictions and the true values. Table 6 shows simple pearson\n\n\nand spearman rank correlations between true and predicted values. Each cell shows the\n\n\ncorrelation between predicted welfare and true welfare across the 20 target populations.\n\n\nRows represent alternative pseudosurveys and columns indicate alternative welfare\n\n\nmeasures. Correlations (both pearson and rank) are positive and reasonably high for\n\n\nmean consumption and the two poverty measures (headcount rate and squared poverty\n\n\ngap). In the case of inequality the correlations are much lower – presumably because the\n\n\ntarget populations vary very little in terms of true inequality. Indeed, households in the\n\n\nPROGRESA communities are more homogeneous than those within a stratum in a typical\n\n\npoverty mapping application. All the communities in the PROGRESA sample were\n\n\nselected for the program because they were poor and rural, based on indicators in the\n\n\n1990 and 1995 censuses. Consequently, the households are more similar to one another\n\n\nthan the households in an entire stratum of a country. This high level of homogeneity\n\n\nacross households (and target populations) is a somewhat unusual feature of this\n\n\nempirical application. However, it might be expected to present a particularly difficult\n\n\nsetting in which to implement the small-area estimation methodology and therefore does\n\n\nprovide a useful (conservative) setting in which to gauge the methodology’s performance.\n\n\n**6. Discussion**\n\n\nThe results presented here offer a rough test of the ELL methodology and point to\n\n\nsome tentative conclusions that may inform future applications of the ELL welfare\n\n\nmapping method. In terms of the predictive power of the method, the results provide\n\n\nstrong evidence that ELL estimates have important information content.", "source": "general_prwp", "subset": "annotate_aj_part2", "spans": [{"key": "prwp:003366:17:0:0", "start": 1309, "end": 1331, "surface": "1990 and 1995 censuses", "probe_tag": "confusion", "probe_score": 0.7735, "luna_label": 1, "luna_reason": "Census indicators were used to select poor rural communities."}]}, {"key": "aj2-049", "text": " Survey|2008|World Bank (2008)<br>|2007<br>|Primary and secondary<br>level|\n|Liberia|Core Welfare<br>Indicators<br>Questionnaire|2007|World Bank (2010)|2007/2008|Primary and secondary<br>level|\n|Paraguay|Permanent<br>Household Survey|2003<br>to<br>2010|Ministry of Education<br>Ministry of Health<br>Ministry of Finance<br>Preliminary results of BOOST in Paraguay|2004<br> <br>2009|Education:<br>Regions<br>Preschool/primary/<br>   secondary<br>Health:<br>Regions<br>Type of center|\n|Tajikistan|Tajikistan Living<br>Standards Survey|2003<br>2007<br>2009|Preliminary results of BOOST in Tajikistan|2009|Regions|\n|Thailand|Household Socio-<br>Economic Survey|2008|Local Administrative Organization Survey<br>Ministry of Education<br>Comptroller General’s Department<br>ONESQA (2010)|2008|Regions<br>Primary/secondary|\n|Zambia|Living Conditions<br>Monitoring Survey|2010|Ministry of Finance and National Planning<br>Ministry of Education Statistical Bulletins|2009<br>|Primary/secondary<br>Provinces|\n\n\n_Source_ : Author’s compilation.\n_Note_ : Data for enrollment come from the household surveys in the case of Côte d’Ivoire and Tajikistan.\n\n\n\n\n\nThe average public unitary benefits to children enrolled in public school vary in this country\n\n\nsample from US$6.9 in Liberia (for primary education) to US$531 in Paraguay (for secondary education).\n\n\nAs expected, differences are also large in terms of the", "source": "general_prwp", "subset": "annotate_aj_part2", "spans": [{"key": "prwp:005639:14:1:5", "start": 767, "end": 773, "surface": "ONESQA", "probe_tag": "confusion", "probe_score": 0.5375, "luna_label": 1, "luna_reason": "Named 2010 source cited in the table's Thailand education data row."}]}, {"key": "aj2-050", "text": " to divergences in the survey methodology: Among other things, WHS data are only available for the\n_first_ health care seeking response if the _youngest_ child under 5 in the household suffered an ARI, whereas DHS and MICS ARI\ntreatment data come from _all_ health care seeking responses of _all_ children under 5 with an ARI in a household. The HEFPI\ndatabase therefore does not include ARI treatment data from the WHS.\n29 For antenatal care, the MICS 2 antenatal care visit data only refer to visits to a _specific provider_, whereas all later MICS waves\nand all DHSs do not impose this limitation. For all DHSs and all MICSs from 2002 onwards, a bed net is considered treated if it\na) is a long-lasting treated net, b) a pre-treated net that was purchased or soaked in insecticides less than 12 months ago, or c) a\nnon-pre-treated net which was soaked in insecticides less than 12 months ago. By contrast, data limitations in the MICS 2 wave\n(collected before 2002) restrict our definition of treated nets to those _ever_ treated. For antenatal care, the MICS 2 antenatal care\nvisit data only refer to visits to a specific list of providers, whereas all later MICS waves and all DHSs do not impose this\nlimitation. WHS measles immunization data are only available for the _younges_ t child in the household, whereas our DHS and\nMICS measles immunization data come from _all_ children under 5 in a household.", "source": "general_prwp", "subset": "annotate_aj_part2", "spans": [{"key": "prwp:007497:27:1:1", "start": 346, "end": 360, "surface": "HEFPI\ndatabase", "probe_tag": "keep", "probe_score": 0.9446, "luna_label": 0, "luna_reason": "Names a database but shows no analytical use of its data."}, {"key": "prwp:007497:27:1:3", "start": 1218, "end": 1247, "surface": "WHS measles immunization data", "probe_tag": "confusion", "probe_score": 0.4038, "luna_label": 1, "luna_reason": "WHS data support a concrete comparison of measles immunization coverage limitations."}]}, {"key": "aj2-051", "text": " using log transformation as\n\nin (1) while investment, international trade openness and natural resource rent are measured in\n\npercentage to GDP. Investment and international trade data are valued in constant prices. The\n\nlog transformation is meant to eliminates, at least partially, the strong asymmetry in inflation\n\ndistribution and to some to smooth time trend in the data set.\n\n\nPage | 15", "source": "general_prwp", "subset": "annotate_aj_part2", "spans": [{"key": "prwp:001708:16:1:0", "start": 161, "end": 185, "surface": "international trade data", "probe_tag": "confusion", "probe_score": 0.5436, "luna_label": 0, "luna_reason": "Generic data phrase describes measurement treatment without an attributed finding."}]}, {"key": "aj2-052", "text": "**5.2 Women’s land rights and inheritance**\n\n\nA more direct test of the extent to which Rwanda‟s policy of actively increasing women‟s rights to land\n\n\nhad the desired impact is to assess the extent to which LTR helped to increase female land ownership.\n\n\nHowever, a key provision of the legislation is that legally married women are entitled to equal ownership\n\n\nrights over household parcels. 76 percent of couples in our sample have a marriage certificate, in line with\n\n\nlegal provisions requiring registration of marriages at the local commune. Table 7, which presents\n\n\nregressions for an indicator of land ownership and the share of land owned by females, illustrates that\n\n\nLTR has dramatically changed women‟s rights over land by helping to create documentary evidence of\n\n\nsuch rights. While the first four columns, based on the full sample, show little change in female land\n\n\nownership rights, columns 5 and 6 which restrict the sample to cohabitating/married couples, reveal a\n\n\nlarge program impact. The first row shows that, for women in this group who are not legally married,\n\n\nLTR results in a small but statistically significant reduction (by 8 percentage points) of the probability of\n\nhaving documented land ownership. <sup>10</sup> [^10: While our questionnaire did not elicit information on disputed claims, it would in principle be straightforward to use the dispute register to\nexplore how many of these were able to register disputed claims and how many of these had actually been resolved.] However, for women who are part of a union formalized through a\n\n\nmarriage certificate, the effect of the program is overwhelmingly positive—they are 17 percentage points\n\n\nmore likely to be regarded as joint land owners after LTR than before. The final column displays results\n\n\nwith the share of the land owned by women as the dependent variable which point to a positive but not\n\n\nstatistically significant effect, regardless of the presence of a certificate.\n\n\nAs many past land adjudication efforts failed to tackle inheritance issues, it is of interest to", "source": "general_prwp", "subset": "annotate_aj_part2", "spans": [{"key": "prwp:004942:15:0:0", "start": 1383, "end": 1399, "surface": "dispute register", "probe_tag": "confusion", "probe_score": 0.4832, "luna_label": 0, "luna_reason": "Potential future use is proposed, not actual analysis of the register."}]}, {"key": "aj2-053", "text": "###### **S4 Trends in Woreda-Level Outcome Variables Over Time**\n\nThis section shows trends in outcomes variables over time. Trends are shown across different groupings of\n\n\nWoredas, where Woredas are grouped by baseline levels of nighttime lights into dark Woredas (Woredas with\n\n\nno positive nighttime lights), and those with low, medium, and high baseline levels of nighttime lights (we\n\n\nuse 3-quantiles of the maximum value of nighttime lights across Woredas with some positive nighttime lights\n\n\nto form the low, medium, and high groups).\n\n\nFigure S4 shows average trends over time. Woredas across all groupings saw growth in nighttime lights\n\n\nand urban land; in addition, all followed a general pattern of increasing then decreasing cropland area. The\n\n\nfigure shows a sharp increase in nighttime lights among Woredas with a maximum nighttime value of 0\n\n\nat baseline. This increase is due to a difference in the underlying nighttime lights data; from 1992-2013,\n\n\nDMSP-OLS data is used; and from 2014 onwards, simulated DMSP-OLS data is used, which captures more\n\n\nlow-level light.\n\n\nFigure S5 shows the distribution in growth rates in outcome variables from 1992 to 2016. The figure\n\n\nshows that most Woredas saw growth in nighttime lights; while many Woredas saw growth in Urban area,\n\n\na notable proportion saw no change in urban area. In addition, most Woredas saw no change in Cropland\n\n\narea. Among Woredas that did see change in cropland, Woredas were roughly equally split in seeing growth\n\n\nor a reduction in cropland, except for Woredas with high initial nighttime lights, where Woredas tended to\n\n\nsee a reduction in cropland.\n\n\nS5", "source": "general_prwp", "subset": "annotate_aj_part2", "spans": [{"key": "prwp:000842:39:0:0", "start": 932, "end": 953, "surface": "nighttime lights data", "probe_tag": "confusion", "probe_score": 0.5772, "luna_label": 1, "luna_reason": "Underlying data explain observed nighttime-lights trend differences."}, {"key": "prwp:000842:39:0:2", "start": 973, "end": 986, "surface": "DMSP-OLS data", "probe_tag": "confusion", "probe_score": 0.5345, "luna_label": 1, "luna_reason": "Named nighttime-lights data used to analyze trends across Woredas."}]}, {"key": "aj2-054", "text": " majority public primary schools in Indonesia. (The data on 120\nJunior Secondary schools is not used in this paper.) Indonesia spans across 1,700 more or less inhabited islands\nand is the world’s fourth most populous country, and the distance from the most western school in the sample,\non mainland Sumatra, to the most eastern, on one of the remote islands of the South Moluccas, roughly spans\nthe distance between San Francisco and New York. See also De Ree, Al-Samarrai, and Iskandar (2012), Chang,\nShaeffer, Al-Samarrai, Ragatz, De Ree, and Stevenson (2013) and World Bank (2015), for analysis based on\nthe same data. For more information on the data and the experiment see De Ree, Muralidharan, Pradhan,\nand Rogers (2015) and World Bank (2015).\n\n\n3", "source": "general_prwp", "subset": "annotate_aj_part2", "spans": [{"key": "prwp:006598:4:1:0", "start": 52, "end": 88, "surface": "data on 120\nJunior Secondary schools", "probe_tag": "confusion", "probe_score": 0.7669, "luna_label": 0, "luna_reason": "The sentence explicitly says this existing data is not used in the paper."}]}, {"key": "aj2-055", "text": "- _Technical and management limitations._ Webster et al. (1998) stress more than any\nother study the importance of modern technology and skills for both managers\nand workers.\n\n  - _Public attitudes._ A 1999 survey carried out by MPDF revealed how the public\nopinion toward private enterprises is highly negative <sup>_39_</sup> [^39: MPDF (1999). Report on Survey of Attitudes toward the Private Sector in Vietnam.] . According to private\nsector analysts there is a need for a shift from an attitude of reluctance and control\nto one of active support and encouragement.\n\n\n**Are Key Obstacles to Further Private Sector Development Changing?**\n\n64. In the past few years the government took a number of steps to reduce the\nconstraints to business activities in Vietnam and create a more conducive environment for\nprivate enterprise. The question is however whether these measures have led to real\nchanges in perceived business obstacles. In this survey enterprises were asked to list the\nthree most important obstacles to their business development. The results were compared\nwith the reported obstacles in the 1997 NIAS-survey in order to identify changes in\nperceptions over the past few years <sup>40</sup> [^40: The NIAS survey was carried out with small private manufacturers (<100 employees) in 5 provinces (Hanoi, Ha\nTay, Haiphong, Ho Chi Minh and Long An). The results of the 1997 survey were compared with a subset of our\nsurvey. For the purpose of comparison we only analyzed the obstacles for the small manufacturing companies in the\nsample.] .\n\n_65._ The broad nature of the obstacles to private sector development has remained\nmore or less the same but there seems to be a shift in the relative importance of certain\nobstacles. Table 6.1 compares the reported main obstacle in both surveys.\n\n_66._ Capital remains the most important constraint for more than one third of the\nenterprises. Market constraints (limited market demand and too much competition) were\nreported as the main", "source": "general_prwp", "subset": "annotate_aj_part2", "spans": [{"key": "prwp:002480:34:0:1", "start": 357, "end": 413, "surface": "Survey of Attitudes toward the Private Sector in Vietnam", "probe_tag": "confusion", "probe_score": 0.7782, "luna_label": 1, "luna_reason": "Named survey report cited as the source for findings on public attitudes."}]}, {"key": "aj2-056", "text": "Box 1. Child anthropometry data issues \n \nAs an important caveat, available estimates of child undernutrition rates, including the statistics \ndiscussed in this review, may be biased due to missing or invalid child anthropometry data. Thus, \nthe results of any analysis—whether of patterns, trends, or correlates—may be artifacts of the \ndata rather than real phenomena.  \n \nMissing data can take four forms: (a) the survey was not conducted because the intended \nhousehold was unavailable, (b) the survey was not conducted because the intended household \nrefused to participate in the survey, (c) the intended household participated in the survey but \nrefused child anthropometry measurement, or (d) the child anthropometry measurements were \ninvalid. Not all household surveys perform fielding or statistical adjustments for the different \nforms of missing data. Furthermore, not all household survey reports present comprehensive, \ndetailed information on the extent of missing data.  \n \nBased on statistics we could extract from household survey reports and nutrition studies, the \nmissing data problem seems severe, especially in certain parts of the country. For example, in \nthe 2011 NNS, household survey nonresponse rates (that is, missing data forms (a) and (b) \ndivided by the original household sample size) are as high as 9% in Balochistan and 16% in \nKPK. In the 2012–13 DHS, the rate of missing or invalid anthropometry data (that is, missing \ndata forms (c) and (d) divided by the number of eligible children in surveyed households) is 19%. \nIn the same survey, for Balochistan, 20% of eligible children in surveyed households have \nmissing anthropometry data, and 59% of children who were measured have invalid \nanthropometry data.  \n \nIn terms of other evidence, Arif et al. (2014) note that the 2010 Pakistan Panel Household Survey \n(PPHS), which covered 16 districts across the four provinces, failed to gather height and weight \ndata for about one-third", "source": "general_prwp", "subset": "annotate_aj_part2", "spans": [{"key": "prwp:007038:6:0:4", "start": 1186, "end": 1194, "surface": "2011 NNS", "probe_tag": "confusion", "probe_score": 0.7498, "luna_label": 1, "luna_reason": "Named survey supports reported household nonresponse rates."}, {"key": "prwp:007038:6:0:5", "start": 1377, "end": 1388, "surface": "2012–13 DHS", "probe_tag": "confusion", "probe_score": 0.4139, "luna_label": 1, "luna_reason": "DHS survey data support the reported 19% missing or invalid anthropometry rate."}]}, {"key": "aj2-057", "text": " of influx often is not driven by the city but by national and international\nfactors, the city still needs to recognize and prepare for these changes.\n\nWhat does a Mayor need to know to measure the performance of a city? Mayors, residents,\nbusinesses, and financial institutions all desire information on a city’s performance. There are\nmany ways to measure city performance. At both national and international levels,\nmethodologies have been developed by many agencies and public bodies. This commendable\neffort has yielded important results. However, much work is still needed to make these\nmeasurements standardized, consistent, and comparable. Only then can the indicators be used as\nbenchmarks and comparators across countries and over time.\n\n## **4. Experience with Indicators**\n\n\n**4.1 The World Bank and City Indicators**\n\nThe World Bank recognizes the growing importance of cities and their role in globalization,\ndecentralization and urbanization, which have characterized the last 50 years. Many questions can\nonly be answered with city level data. Unfortunately, much of the research conducted by the\nWorld Bank has been limited due to the lack of reliable disaggregated data that are comparable\nacross cities and over time.\n\n\n9 The level of health, education, and social services provision varies considerably across cities. In many\ncountries these services are provided by state/provincial or national agencies, however in all cities the most\nimmediate impacts of the quality these services are experienced. Cities typically provide services directly\nor indirectly through concessions or management contracts. Canadian cities do not generally provide health\nand education services.\n\n8", "source": "general_prwp", "subset": "annotate_aj_part2", "spans": [{"key": "prwp:003327:7:1:1", "start": 1169, "end": 1187, "surface": "disaggregated data", "probe_tag": "confusion", "probe_score": 0.3054, "luna_label": 1, "luna_reason": "Data availability limitation is explicitly cited as constraining World Bank research."}]}, {"key": "aj2-058", "text": " standard difference indifference methodology, which controls for common (additive) time trends and preprogram differences between the two groups. In this interpretation,  2 and  3 are\nestimates of short and medium-term program effects respectively. For each of these\noutcomes, we estimate Equation (1), controlling for _X_, a vector of household level\nbackground characteristics such as urban location, religious affiliation, BPL and SC/OBC\nstatus across waves. We also include relevant individual characteristics, notably\neducation, number of children at the time of the program introduction and age in\nquadratic form. In this and all other specifications going forward, we use robust standard\nerrors clustered at the primary sampling unit, and apply the NFHS state-sample weights.\nFor discrete outcomes, we use probit regression and report marginal effects; for\ncontinuous outcomes, we report OLS estimates. The complete regression results are\nreported in Appendix Table A.\n\nFor eligible women, the program positively and significantly affects the ratio of living\ndaughters to living sons--and the effect becomes larger in the medium-term (Table 3,\nColumn 1). In terms of fertility preferences, we observe mixed results: first, a smaller,\ninsignificant negative, then eventually positive impact on the ratio of ideal daughters to\nideal sons. We see a similar effect on the likelihood of a woman expressing the desire for\nat least one daughter (Table 3, Columns 2 and 3). These findings are suggestive of a\npositive change in women’s preferences for girls, but not conclusively so.\n\nOur results are consistent with the MODE evaluation report (MODE, 2000) which\nshowed that 70% of beneficiaries reported positive behavioral changes among their\nfamily members, but only 2% felt that actual discrimination against girls would decrease.\nNote also that the total number of ideal children appears to have fallen both in the short\nand medium term but not significantly so. (Table 3, Column 4).\n\n**4.", "source": "general_prwp", "subset": "annotate_aj_part2", "spans": [{"key": "prwp:004055:12:1:0", "start": 759, "end": 763, "surface": "NFHS", "probe_tag": "confusion", "probe_score": 0.6502, "luna_label": 1, "luna_reason": "NFHS weights are applied in regression analysis as an existing survey-data input."}]}, {"key": "aj2-059", "text": " that individual incomes follow an autoregressive lognormal process with individual fixed\n\n\neffects. We show that the limited information embodied in the time-series of these aggregate moments\n\n\nis sufficient to place bounds on the extent of mobility in the income distribution, even though we do not\n\n\nobserve income dynamics at the individual level. An empirical application using data from the PSID\n\n\nconfirms that these bounds generally contain the point estimates that are obtained using the record-level\n\n\npanel data, and moreover are reasonably tight. Encouraged by these findings, we apply our methodology\n\n\nto two large cross-country datasets, namely the WID (including mostly high income countries) and the\n\n\nWorld Bank’s PovcalNet (including mostly developing countries). Some of the cross-country patterns we\n\n\nobserve in estimates of mobility seem quite plausible given our priors. For example, among the high\n\n\nincome countries, the Scandinavian countries and much of Europe show relatively high levels of income\n\n\npersistence, while the United States, Singapore and Taiwan rank among the countries with low levels of\n\n\nincome persistence. When comparing estimates between the WID and PovcalNet, our estimates suggest\n\n\n24", "source": "general_prwp", "subset": "annotate_aj_part2", "spans": [{"key": "prwp:007100:25:1:0", "start": 397, "end": 401, "surface": "PSID", "probe_tag": "keep", "probe_score": 0.9514, "luna_label": 1, "luna_reason": "PSID data support empirical mobility estimates and validate the methodology's bounds."}, {"key": "prwp:007100:25:1:4", "start": 732, "end": 741, "surface": "PovcalNet", "probe_tag": "confusion", "probe_score": 0.8743, "luna_label": 1, "luna_reason": "Named dataset used for cross-country mobility estimates and comparative analysis."}]}, {"key": "aj2-060", "text": "ues of �: To better understand the type of nonlinearity involved Figure 1 plots the\n\ntime pro…le of the transition function, F (zt), over the range of zt.\n\n#### 3 Structural identi…cation and data\n\n\nThis paper uses a unique quarterly dataset from Malaysia to identify government\n\nconsumption and government spending shocks. The data runs from 1981:1 till\n\n2010:4. The identi…cation scheme is based on a generalised version of reduced form\n\nmodels in, amongst many others, Fatás and Mihov (2001), Blanchard and Perotti\n\n(2002), Perotti (2005), Cimadomo, Hauptmeier and Kirchner (2010), Corsetti,\n\nMeier and Müller (2010), Auerbach and Gorodnichenko (2010, 2011) and Bach\nmann and Sims (2011). The identi…cation approach is based on a recursive iden\nti…cation scheme that aims to identify …scal policy shocks on their timings within\n\nthe system.\n\n\nAs in Blanchard and Perotti (2002) the basic model is computed using quarterly\ndata and is composed of Xt = [Gt; Tt; Yt]: The variable Gt represents government\nspending shocks. Just as output multipliers for government purchases may dif\nfer according to the regime in which they occur, they can also di¤er for di¤erent\ncomponents of government spending. <sup>11</sup> Leeper, Walker and Yang (2009), for ex\nample, have shown how the short-run multiplier for government investment shocks\n\nare smaller than those for government consumption innovations, but are more\ne¤ective in the longer-term. <sup>12</sup> Two types of government spending shocks are identi…ed: consumption and investment. <sup>13</sup> The government consumption de…nitions\n\nfollow Perotti (", "source": "general_prwp", "subset": "annotate_aj_part2", "spans": [{"key": "prwp:005157:9:0:1", "start": 915, "end": 929, "surface": "quarterly\ndata", "probe_tag": "drop", "probe_score": 0.0376, "luna_label": 1, "luna_reason": "Quarterly data are explicitly used as inputs to compute the model."}]}, {"key": "aj2-061", "text": "<u>Switzerland-Italian</u> <sup>~~2~~</sup> <u>6.8</u> <u>5.3</u> <u>5.4</u>\n\nItaly <sup>2</sup> 4.7 3.4 4.0\n\nChile <sup>1</sup> 9.3 6.9 10.0\n\nNuevo Leon <sup>1</sup> 13.4 11.4 14.8\n\nKorea <sup>2</sup> 7.2 6.5 6.9\n\n**Bermuda** <sup>**2**</sup> 8.3 5.0 5.2\n\n_Mean_ _6.7_ _5.5_ _5.3_\n\n<u>1: Using IALS</u>\n\n\n2. Using ALL\n\n\nThe two sets of estimates (using estimated coefficients β1 and δ1) suggest that the cross-country\n\n\naverage of the component of the return to schooling associated with skills acquired outside school is\n\n\nabout 70-80 percent of the gross return; that is, about 70-80 percent of what the labor market rewards\n\n\nin schooling is its non-literacy component (with the set of estimates associated with estimated\n\n\ncoefficient δ1, on average slightly lower); however, there is significant heterogeneity and a\n\n\ndichotomy between the two subgroups of countries – the educationally advanced and the less\n\n\neducationally advanced.\n\n\nIn Table 2, we divide the 14 countries in two groups of 7 after ranking the countries by average\n\n\nachievement score. We see that there is a strong negative association between country achievement\n\n\nscore and dispersion of score. Chile, Slovenia and Italy rank at the bottom in average score and at the\n\n\ntop in score dispersion; the opposite is the case for countries such as", "source": "general_prwp", "subset": "annotate_aj_part2", "spans": [{"key": "prwp:005823:15:0:0", "start": 295, "end": 299, "surface": "IALS", "probe_tag": "drop", "probe_score": 0.0338, "luna_label": 1, "luna_reason": "Named survey used for cross-country skills and returns analysis."}]}, {"key": "aj2-062", "text": " Table 1 below summarizes the average\n\nmeasurements found in recent LSMS-ISA surveys. <sup>4</sup> The SR-GPS difference observed in Nigeria is\n\n\nconsiderably larger than in the four other LSMS surveys listed.\n\n\n<<< TABLE 1 HERE >>>\n\n\n3 While the differences observed in Nigeria are quite large nationwide, particular states and enumerators see\nsignificantly larger divergences. The two states with the highest discrepancy in measurements are Osun and Ondo\n(10,469% and 11,534%, respectively). Within those two states, three particular interviewers contribute to the\nmajority of the difference suggesting that the problem may be largely the product of human error such as incorrect\nuse of the GPS device or inaccurate recording of self-reported and/or GPS figures.\n4 One important difference between the GHS-Panel and the other LSMS-ISA surveys presented here is that in the\nGHS-Panel farmers are allowed to use nonstandard area units when estimating plot size while all the other surveys\nonly allow farmers to report in standard units (acres, square meters, or hectares). This may partially explain why the\nself-reported/GPS difference is so much large in Nigeria.", "source": "general_prwp", "subset": "annotate_aj_part2", "spans": [{"key": "sample:prwp:001776:8:1:0", "start": 68, "end": 84, "surface": "LSMS-ISA surveys", "probe_tag": "confusion", "probe_score": 0.6001, "luna_label": 1, "luna_reason": null}, {"key": "sample:prwp:001776:8:1:1", "start": 804, "end": 813, "surface": "GHS-Panel", "probe_tag": "drop", "probe_score": 0.0, "luna_label": 1, "luna_reason": null}, {"key": "sample:prwp:001776:8:1:2", "start": 875, "end": 884, "surface": "GHS-Panel", "probe_tag": "drop", "probe_score": 0.0051, "luna_label": 1, "luna_reason": null}]}, {"key": "aj2-063", "text": " night, (negatively coded)<br>likelihood to spend an afternoon waiting for a medical exam, likelihood to<br>take a  boda boda if the driver is unknown, likelihood to engage in<br>unprotected sex, (negatively coded) likelihood to invest in a safe business<br>accepting low profits, likelihood to invest into a business that has high profits<br>but  equal  chance  of  failing,  likelihood  to  take  a  loan  if  there  were  no<br>restrictions, experimental data on number of times the more risky lottery<br>was chosen|\n|7|Trust index|Standardized weighted average of 13 trust items: trust to people in<br>general, trust that people are helpful, (negatively coded) belief that people<br>seek their own advantage, willingness to lend money, willingness to lend<br>possessions, trust in family, trust in friends, trust in neighbors, trust in<br>police, trust in NGO, trust in elders, trust in local government, trust in state<br>government, experimental data on amount send to the WB in trust game<br>and amount send to another player in the trust game|\n|8|Crime and violence<br", "source": "general_prwp", "subset": "annotate_aj_part2", "spans": [{"key": "prwp:000120:25:1:1", "start": 445, "end": 462, "surface": "experimental data", "probe_tag": "drop", "probe_score": 0.0461, "luna_label": 0, "luna_reason": "Generic data phrase merely defines an index component without an attributed finding."}]}, {"key": "aj2-064", "text": "Monsen, K., de Montjoye, Y.-A., Iqbal, A. M., Hadiuzzaman, K. N., Lu, X., Wetter,\n\n\nE., Tatem, A. J., and Bengtsson, L. (2017). Mapping poverty using mobile phone and satellite\n\n\ndata. _Journal_ _of_ _The_ _Royal_ _Society_ _Interface_, 14(127):20160690.\n\n\n34", "source": "general_prwp", "subset": "annotate_aj_part2", "spans": [{"key": "prwp:001019:35:2:0", "start": 150, "end": 183, "surface": "mobile phone and satellite\n\n\ndata", "probe_tag": "drop", "probe_score": 0.0321, "luna_label": 0, "luna_reason": "Span is part of a bibliography title, not an analyzed data-use mention."}]}, {"key": "aj2-065", "text": " sector in each country is then the sum of all utilities’ subsidies in that country.\n\n\nNine countries represented in the IBNET database are estimated to have a negative subsidy. Most of these\nare developed countries, where efficiency may be pushed beyond the level assumed in the Chilean\nmodel. <sup>24</sup> Where this is the case, subsidies are assumed to be zero.\n\n\n**3.10 Estimating the subsidies for countries not in IBNET**\n\n\nTo extrapolate subsidy estimates to countries not included in the database, we first separate out China\nand India, while the remaining countries are grouped into four clusters—high income, upper middle\nincome, lower middle income, and low income—based upon the World Bank’s country classifications by\nincome for fiscal year 2019. Next, for water and sanitation separately, we calculate an average subsidy\nper person served for countries with representation in IBNET, disaggregated into the four clusters (see\nAppendix B). Then, for countries not in the IBNET database, we multiply the per person subsidy for its\ncluster by the total population served by the respective service (estimated by multiplying the country’s\ncoverage rate <sup>25</sup> [^25: Water and/or sanitation coverage data from the World Health Organization/United Nations Children’s Fund for 3 countries\n(Austria, Isle of Man, and Micronesia), in addition to the 6 previously cited with partial IBNET data, were incomplete, and were\nthus supplemented by additional data and estimates. Refer to Appendix B for details.] and its total population). Since the main drivers for these estimates are the unit cost in\nthe asset base calculations, the results presented in the report assume a +/-10 percent variation in the\nunit asset base estimates.\n\n\n22 China and India were not extrapolated due to low proportional representation in IBNET and a general lack of data availability.\n\n23 Water and/or sanitation coverage data for 6 countries (Bahrain, Fiji, Indonesia,", "source": "general_prwp", "subset": "annotate_aj_part2", "spans": [{"key": "sample:prwp:000381:14:2:0", "start": 121, "end": 135, "surface": "IBNET database", "probe_tag": "confusion", "probe_score": 0.8305, "luna_label": 1, "luna_reason": null}, {"key": "sample:prwp:000381:14:2:1", "start": 1183, "end": 1220, "surface": "Water and/or sanitation coverage data", "probe_tag": "confusion", "probe_score": 0.7404, "luna_label": 1, "luna_reason": null}, {"key": "sample:prwp:000381:14:2:2", "start": 1877, "end": 1914, "surface": "Water and/or sanitation coverage data", "probe_tag": "drop", "probe_score": 0.0375, "luna_label": 1, "luna_reason": null}]}, {"key": "aj2-066", "text": "|<br>34.6|<br>-|3.03|<br>35|\n|<br>**2007**<br>|-|<br>22.7|2.85|<br>42|\n|<br>**2008**<br>|<br>38.1|<br>-|2.74|<br>-|\n|<br>**2009**<br>|-|<br>-|2.57|<br>64|\n|<br>**2010**<br>|<br>34.7|<br>-|2.50|<br>73|\n|<br>**2011**<br>|34.0|<br>-|2.47|<br>83|\n|<br>**2012**|<br>-|<br>-|2.04|<br>82|\n\n\n<u>ANC data source: Swaziland Country Report on Monitoring the Political Declaration on HIV/AIDS 2012</u>\n\n<u>National DHS and AIS data source: Swaziland DHS 2006-2007</u>\n\n**Tanzania**\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Col1|Prevalence among females 15-24 (%)|Col3|Spectrum estimates|Col5|\n|---|---|---|---|---|\n|<br> <br>|<br>**National Antenatal Sentinel**<br>**Surveillance Surveys**|<br>**National Demographic and**<br>**Health or AIDS Impact Surveys**|<br>**Incidence in**<br>**adults 15-49 (%)**", "source": "general_prwp", "subset": "annotate_aj_part2", "spans": [{"key": "prwp:006140:63:2:1", "start": 593, "end": 620, "surface": "National Antenatal Sentinel", "probe_tag": "drop", "probe_score": 0.0356, "luna_label": 0, "luna_reason": "Standalone table header naming a survey category, not a data-use mention."}]}, {"key": "aj2-067", "text": "Learning from Developing Country Power Market Experiences: The Case of Philippines\n\n\n  - Congestion management\n\n  - Coordinate the operation of ancillary services\n\n  - Accountability of system operations\n\n\nUnder the WESM Rules, the Market Operator shall, generally and non‐restrictively:\n\n\n  - Administer the operation of the WESM in accordance with the WESM Rules;\n\n  - Allocate resources to enable it to operate and administer the WESM on a non‐profit basis;\n\n  - Determine the dispatch schedule of all facilities in accordance with the WESM Rules. Such\nschedule shall be submitted to the System Operator;\n\n  - Monitor daily trading activities in the market;\n\n  - Oversee transaction billing and settlement procedures; and\n\n  - Maintain and publish a register of all WESM Participants and update and publish the register.\n\n\n_4.1.2.2_ _Governance of the wholesale market_\nThe governance of the Philippines wholesale market is illustrated in Figure 4‐3.\n\n\nFigure 4‐3 Governance structure of the Philippine power market.\n\n\nSource: (Fe Villamejor‐Mendoza, 2008)\n\n\nThe Philippine Electricity Market Board (PEM Board) governs the PEMC. The PEM Board is chaired by the\nSecretary of Energy, and is a 15‐member body consisting of an equitable representation from the different\nsegments of the power supply chain (generation, distribution and electric cooperatives, supply,\ntransmission, and the market operator) and independent members (independent of the power sector and\nthe government). The PEM Board provides the policies and guidelines of the WESM contained in the\nImplementing Rules and Regulations of the Act, WESM Rules, and such other relevant laws, rules and\nregulations.\n\n\nLooking at the composition of the PEM Board, there would still be that question of independence which\nis quite a important issue to ensure power market competition. Indeed, the PEM Board, being chaired by\nthe Secretary of Energy, is open to government intervention. This vulnerability should be addressed if\noperation of the WESM is turned over to the independent market", "source": "general_prwp", "subset": "annotate_aj_part2", "spans": [{"key": "prwp:007627:23:0:0", "start": 753, "end": 786, "surface": "register of all WESM Participants", "probe_tag": "drop", "probe_score": 0.0302, "luna_label": 0, "luna_reason": "Names a participant register without showing its data used for analysis or decisions."}]}, {"key": "aj2-068", "text": " census in the past 10 years, one or more agricultural censuses in\nthe past 10 years, three or more health surveys in the past 10 years, and has a complete vital registration\nsystem.\n\nThe statistical methodology dimension measures a country’s ability to adhere to internationally\nrecommended standards and methods. This aspect assesses guidelines and procedures used to compile\nmacroeconomic statistics and for social data reporting and estimation practices. This dimension measures\n\n\n7", "source": "general_prwp", "subset": "annotate_aj_part2", "spans": [{"key": "prwp:000773:8:2:0", "start": 42, "end": 63, "surface": "agricultural censuses", "probe_tag": "drop", "probe_score": 0.0461, "luna_label": 1, "luna_reason": "Existing agricultural censuses are cited as a country statistical-capacity measure."}]}, {"key": "aj2-069", "text": "**iii.** **Additional functions**\n\nSeveral additional functions can enhance a DMS’s contribution to sound debt management\npractices. The most important are portfolio and risk analysis; future borrowing planning; resource\nmobilization; systems integration; and Straight Through Processing (STP).\n\n\n**Conducting portfolio and risk analyses**\n\nData analytics capacity significantly increases the usefulness of a DMS, making it more than a data\ntracking tool. Important abilities include computing risk indicators for public and publiclyguaranteed debt portfolios and conducting scenario analyses for different exchange rates, interest\nrates or indices, and default rates for guarantees.\n\nA DMS that embeds risk models, _e.g._, supporting historical variance/covariance or stochastic\nanalyses and Monte Carlo simulations, further strengthens a DMO’s analysis capacity.\n\n\n**Box 1. System and data security**\n\nFor any software solution, access controls and system security are critical to protecting data and\nreducing operational risk (see Box 1). Security controls and protocols that personalize access to\ninformation should also be in place to mitigate human mistakes and data loss. A DMS can deliver\nthese functions through providing an appropriate level of business continuity; meeting industrystandard internal control, audit and regulatory requirements; and storing historical data for\nreference purposes.\n\nA DMS with a database housed on a DMO’s hardware can enhance data privacy and related\nprocedures so long as it is not connected to the Internet. Many sovereigns believe this approach\nhelps protect sensitive information on their debt portfolio such as bids in government securities\nauctions and the lenders’ identities.\n\nAt the same time, storing information on local databases might expose a DMO to increased\noperational risk. System malfunctions, deficient equipment, or changing technologies may make\nthis option problematic. For some DMOs, a database that is stored on an external server or\ncloud-based service might be a better solution because these are professionally managed services\nthat should have the proper safeguards in place.\n\n\n**", "source": "general_prwp", "subset": "annotate_aj_part2", "spans": [{"key": "prwp:007468:13:0:0", "start": 1366, "end": 1381, "surface": "historical data", "probe_tag": "drop", "probe_score": 0.0162, "luna_label": 0, "luna_reason": "Data is mentioned as stored for reference, without shown analytical use."}]}, {"key": "aj2-070", "text": " costs for SSN–plus programs, compared to 18 percent of the\ntotal cost for L&J programs, which tend to be more complex, with multiple program components.\n\n**_Component Dosage and Adequacy_** <sup>**_35_**</sup> [^35: Adequacy is calculated as cost ($ 2011 PPP) of a component (e.g., grant size) divided by average annual per capita\nconsumption ($ 2011 PPP) of the bottom 20 percent of households in the relevant country.]\n\n\nThe following analysis explores component dosage and adequacy for those programs that provided\ndisaggregated data on underlying components. The sample of programs varies across different\ninterventions, and components reported by three or fewer programs are not included.\n\nCash grants (for productive investments) are provided more often, of higher value, and in more\ninstallments, in L&J programs than in SSN-plus programs. The average grant size for L&J\nprograms it is $416 (PPP 2011), <sup>36</sup> [^36: This data set excludes the project in Burkina Faso, which, by design, provides a substantially higher grant to youth\nselected through business plan competitions to create small business and microenterprises, rather than for selfemployment.] as compared to $222 (PPP 2011) for SSN–plus programs. Fewer\nSSN–plus programs provide any cash grants to their beneficiaries compared to L&J programs.\nThis may be because L&J programs aim to improve productive outcomes, while SSN-plus\ninitiatives primarily aim to improve consumption and, for a subset of beneficiaries, their productive\noutcomes as well. In addition, L&J programs tend to provide cash grants in two installments, which\n\n\n33 Delivery and staff costs refers to (1) cost of implementing certain components such as savings groups and training,\nand (2) the human resource cost of administering other components such as grants, inputs and cash transfers.\n34 Both government-led and NGO-led programs incur higher delivery-led", "source": "general_prwp", "subset": "annotate_aj_part2", "spans": [{"key": "prwp:000078:22:1:0", "start": 519, "end": 537, "surface": "disaggregated data", "probe_tag": "drop", "probe_score": 0.0441, "luna_label": 1, "luna_reason": "Analysis uses existing disaggregated component data to examine program adequacy."}]}, {"key": "aj2-071", "text": "#### **Risk Sharing and Internal Migration**\n\nJoachim De Weerdt <sup>*</sup>\n\n\nKalle Hirvonen <sup>**</sup>\n\n\nJEL codes: O12, O15, O17, R23\n\n\nKeywords: internal migration, risk, insurance, institutions, Africa, tracking data\n\n\nSector board: POV (Poverty Reduction)\n\n- EDI, Tanzania, ** University of Sussex, UK\n\nAcknowledgements: The fieldwork was primarily funded by the Rockwool\nFoundation and the World Bank, with additional funds provided by AFD, IRD and\nAIRD through the “Health Risks and Migration” grant of the William and Flora\nHewlett Foundation. Kalle Hirvonen gratefully acknowledges the financial support\nfrom the Economic and Social Research Council [grant number ES/I900934/1], the\nFinnish Cultural Foundation and Yrjö Jahnsson Foundation. Stefan Dercon was\ninstrumental in conceptualising this paper and alerted us to the beauty of contrasting\nfull and partial insurance through Equations (1) and (4). We further thank Kathleen\nBeegle, Marcel Fafchamps, Markus Goldstein, Flore Gubert, Cynthia Kinnan, Andy\nMcKay, Imran Rasul, Barry Reilly and seminar and conference participants at\nBREAD, CSAE, LICOS, NEUDC, Sussex University, Paris School of Economics,\nFUNDP and UNU-WIDER for useful comments. The usual disclaimer applies. For\nmore information, contact Joachim De Weerdt (j.deweerdt@edi-africa.com) or Kalle\nHirvonen (k.v.hirvonen@sussex.ac.uk).", "source": "general_prwp", "subset": "annotate_aj_part2", "spans": [{"key": "prwp:005580:2:0:0", "start": 211, "end": 224, "surface": "tracking data", "probe_tag": "drop", "probe_score": 0.0142, "luna_label": 0, "luna_reason": "Keyword-only mention; no evidence that tracking data is used or analyzed."}]}, {"key": "aj2-072", "text": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n\n\n\n\n\n\n\nmuch of the heterogeneity inside of these\ngroups. Every two years, GUS publishes\ninformation about the average wages in\n128 occupational groups, with the latest\ndata for October 2022 (GUS, 2024a).\nWhen ZUS data is aggregated into these\noccupational groups with the assumption\nthat wage structure remains the same as in\nOctober 2022, the rate at which Ukrainian\n\n\n\n\n\n\n\n**The occupational progress of**\n**Ukrainian refugees as compared to the**\n**host population may be faster than**\n**the nine main occupational groups**\n**above suggest.** What is particularly\nstriking is the similar pace of progress of\nUkrainian refugees and pre-war Ukrainians\nin the nine main occupational groups\npresented above. However, it conceals\n\n\n\n**Chart 12. Ukrainian refugee wages relative to Polish citizens in the same employee-cells**\nEmployee cells are divided by poviat, sex, age group, and main occupational group\n\n\n20\n\n\n2022 Q2 2024 Q2\n\n\nNote: Data are based on average social security contributions bases in employee-cells, each cell for a specific poviat, sex, age group, and main\noccupational group. All data are for the 01XX ZUS insurance code (employees). Data for Q2 2022 encompass 6945 employee-cells of Ukrainian\nrefugees joined with likewise cells for Polish citizens, while for Q2 2024 13477 such cells. Ukrainian refugees have been identified by PESEL UKR and\nUkrainian citizenship, Poles by Polish citizenship.\n\nSource: Deloitte own elaboration based on ZUS data.\n\n\n\nrefugees move to better-paid occupations\nbecomes clearer. Between June 30, 2022,\nand June 30, 2024, Ukrainian refugees\ngained an estimated 7% in earnings having\nshifted towards better paid occupations,\npre-war Ukrainians 5%, non-Ukrainian\nforeigners 4%, and Polish citizens 1%.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n**Ukrainian refugees have been slowly**\n**", "source": "jad_paddy_docs", "subset": "annotate_aj_part2", "spans": [{"key": "sample:jad_paddy_docs:000001:8:0:0", "start": 284, "end": 292, "surface": "ZUS data", "probe_tag": "keep", "probe_score": 0.9435, "luna_label": 1, "luna_reason": null}, {"key": "sample:jad_paddy_docs:000001:8:0:1", "start": 1534, "end": 1542, "surface": "ZUS data", "probe_tag": "keep", "probe_score": 0.9933, "luna_label": 1, "luna_reason": null}]}, {"key": "aj2-073", "text": "HIGH EMPLOYMENT RATES, BUT LOW WAGES: A POVERTY ASSESSMENT OF UKRAINIAN REFUGEES IN NEIGHBORING COUNTRIES\n\n\n**<u>HOUSEHOLD INCOME DISTRIBUTION BY SOURCE AND POVERTY CATEGORY</u>**\n\n\n\nEmployment Family support Social\nprotection\n(host country)\n\n\n\nOld age\npension\n(Ukraine)\n\n\n12%\n\n\n67%\n\n\n\nSocial\nprotection\n(Ukraine)\n\n\n35%\n\n\n\nHumanitarian\ncash\n\n\n8%\n\n\n\n13%\n\n\n\n23%\n\n\n\n6%\n\n\n\nOther\n\n\n5%\n\n\n3%\n\n\n\n3%\n\n\n5%\n\n\n\nBelow the poverty line\n\n\nBelow the poverty line after housing\n\ncost correction\n\n\nAbove the poverty line after housing\n\ncost correction\n\n\nSource: Survey data, SAG estimates\n\n\n\n26%\n\n\n\n88%\n\n\n\n**Higher employment earnings were the main driver behind the drop in poverty rates from**\n**2023**\n\n\nThe mean monthly equivalized household income <sup>12</sup> [^12: Household disposable income adjusted for size, as per Eurostat’s methodology] of Ukrainian refugees across the seven countries surveyed\nin both rounds increased by 38% from last year, to an equivalent of EUR 763. This increase was much higher\nthan the 4% rise in the regional poverty threshold over the same time.\n\n\nApproximately 90% of the increase in refugee household income can be attributed to higher employment\nearnings, driven by a combination of rising employment rates and wage growth. A significantly smaller, though\nstill notable, contribution came from increased financial support from families in Ukraine, although this finding\nmay partially be an artifact of adjustments to the survey questionnaire <sup>13</sup> .\n\n\n**<u>WEIGHTED AVERAGE MONTHLY EQUIVALIZED INCOME EVOLUTION, EUR</u>**\n\n\n800\n\n\n600\n\n\n400\n\n\n200\n\n\n\n0\n\n\n\nFamily\nsupport\n\n\n\nHost country\n\nsocial\nprotection\n\n\n\nUkraine\n\nsocial\nprotection\n\n(inc.\npensions)\n\n\n\nHumanitarian\n\ncash\n\n\n\nEquivalized\n\n\n\nEmployment\n\nincome\n\n\n\nOther Equivalized\n\n\n\nincome\n\n\n\n2024\n\n\n\nincome\n\n\n\n2023\n\n\n\nNote: Only includes data from the 7 countries surveyed in both rounds (Bulgaria, Czech Republic, Hungary, Republic of Moldova, Poland, Romania, and\nSlovakia)\n\n\nSource", "source": "jad_paddy_docs", "subset": "annotate_aj_part2", "spans": [{"key": "sample:jad_paddy_docs:000010:8:0:0", "start": 544, "end": 555, "surface": "Survey data", "probe_tag": "keep", "probe_score": 0.9981, "luna_label": 1, "luna_reason": null}, {"key": "sample:jad_paddy_docs:000010:8:0:1", "start": 1824, "end": 1873, "surface": "data from the 7 countries surveyed in both rounds", "probe_tag": "keep", "probe_score": 0.9846, "luna_label": 1, "luna_reason": null}]}, {"key": "aj2-074", "text": " those of their\nnative counterparts. Tani (2020) found\nthat in Australia, licensing raised hourly\n\n\n\nvalue to the economy. This estimate may\nunderestimate the potential benefits,\nas the boost in productivity would most\nlikely rise not just employee wages, but\nemployer profits as well. Conversely, the\noverall impact on wages might be lower, if\nincreased worker competition reduced the\naverage individual premium.\n\n\nwages and reduced over-education for\nmigrants working in licensed jobs, while\nproducing worse labour market outcomes\nfor those who did not gain licensure.\nAccording to Peterson et al. (2014), over the\n1973–2010 period, U.S. states with more\nstringent occupational licensing for migrant\nphysicians received fewer new migrant\nphysicians and struggled more with staffing\nshortages in healthcare. Aleksynska and\nTritah (2013) quoted data that migrants\nin France were denied legal access to\napproximately 30% of jobs in the country.\n\n\n\nUkrainian refugees Polish citizens\n\n\nSource: Deloitte own elaboration based on mid-2024 SEIS UNHCR survey\n(Ukrainian refugees’ educational attainment), 2023 Eurostat Labour Force\nSurvey Eurostat (Polish citizens educational attainment), and mid-2024 ZUS\nadministrative data (occupational groups).\n\n\n\nSource: Deloitte own elaboration based on mid-2024 SEIS UNHCR survey\n(Ukrainian refugees’ educational attainment and median net wages),\n2023 Eurostat Labour Force Survey Eurostat (Polish citizens educational\nattainment), and mid-2024 ZUS administrative data (occupational groups).\n\n\n\n**Widespread occupational licensing**\n**is a serious obstacle to an efficient**\n**use of Ukrainian refugees’ human**\n**capital.** Poland has the third highest\nnumber of regulated professions among\nthe 28 European Union member states,\naccording to European Commission’s\nRegulated Professions Database. This can\nbe a problem, as occupational licensing is\ncited in the literature among the reasons\nfor occupational downgrading of migrants.\nCassidy and Dacass (2021) found that in the\nUnited States, immigrants were significantly\nless likely to", "source": "jad_paddy_docs", "subset": "annotate_aj_part2", "spans": [{"key": "sample:jad_paddy_docs:000001:14:1:0", "start": 1035, "end": 1052, "surface": "SEIS UNHCR survey", "probe_tag": "keep", "probe_score": 0.9974, "luna_label": 1, "luna_reason": null}, {"key": "sample:jad_paddy_docs:000001:14:1:1", "start": 1099, "end": 1141, "surface": "2023 Eurostat Labour Force\nSurvey Eurostat", "probe_tag": "keep", "probe_score": 0.999, "luna_label": 1, "luna_reason": "Eurostat Labour Force Survey supplies Polish citizens’ educational-attainment data."}, {"key": "sample:jad_paddy_docs:000001:14:1:2", "start": 1197, "end": 1220, "surface": "ZUS\nadministrative data", "probe_tag": "keep", "probe_score": 0.9499, "luna_label": 1, "luna_reason": "Named administrative data underpin Deloitte’s occupational-group analysis."}, {"key": "sample:jad_paddy_docs:000001:14:1:3", "start": 1298, "end": 1315, "surface": "SEIS UNHCR survey", "probe_tag": "keep", "probe_score": 0.9983, "luna_label": 1, "luna_reason": null}, {"key": "sample:jad_paddy_docs:000001:14:1:4", "start": 1800, "end": 1830, "surface": "Regulated Professions Database", "probe_tag": "confusion", "probe_score": 0.8069, "luna_label": 1, "luna_reason": null}]}, {"key": "aj2-075", "text": ", it has\ndeclined by 2.6 million. This trend is set to\ncontinue. According to the latest Eurostat\nprojections, without migration, the\npopulation (counting all nationalities) aged\n20-64 years would decrease by 4.8 million\nby 2050. <sup>20</sup> [^20: Eurostat data, <u>[https://ec.europa.eu/eurostat/databrowser/view/proj_23np__custom_8710248/bookmark/table?lang=en&bookmarkId=97472dd3-3dd2-](https://ec.europa.eu/eurostat/databrowser/view/proj_23np__custom_8710248/bookmark/table?lang=en&bookmarkId=97472dd3-3dd2-4aca-a51f-15c98be37466)</u>\n**Source:** Eurostat <u>[Statistics | Eurostat (europa.eu)](https://ec.europa.eu/eurostat/databrowser/view/lfsq_pganws__custom_8677828/bookmark/table?lang=en&bookmarkId=06047812-2bde-4cf8-a627-7d63d65f17db)</u> <u>[4aca-a51f-15c98be37466](https://ec.europa.eu/eurostat/databrowser/view/proj_23np__custom_8710248/bookmark/table?lang=en&bookmarkId=97472dd3-3dd2-4aca-a51f-15c98be37466)</u>]\n\n\n© UNHCR / Anna Liminowicz\n\n\n\n19  Statistics Poland data, <u>[https://stat.gov.pl/en/topics/population/internationa-migration/information-on-the-size-and-directions-of-emigration-for-](https://stat.gov.pl/en/topics/population/internationa-migration/information-on-the-size-and-directions-of-emigration-for-temporary-stay-from-poland-between-2004-2020,8,14.html)</u>\n<u>[temporary-stay-from-poland-between-2004-2020,8,14.html](https://stat.gov.pl/en/topics/population/internationa-migration/information-on-the-size-and-directions-of-emigration-for-temporary-stay-from-poland-between-2004-2020,8,14.html)</u>\n20  Eurostat data, <u>[https://ec.europa.eu/eurostat/databrowser/view/proj_23np__custom_8710248/bookmark/table?lang=en&bookmarkId=97472dd3-3dd2-](https://ec.", "source": "jad_paddy_docs", "subset": "annotate_aj_part2", "spans": [{"key": "sample:jad_paddy_docs:000007:8:1:0", "start": 250, "end": 263, "surface": "Eurostat data", "probe_tag": "keep", "probe_score": 0.9976, "luna_label": 1, "luna_reason": null}, {"key": "sample:jad_paddy_docs:000007:8:1:1", "start": 965, "end": 987, "surface": "Statistics Poland data", "probe_tag": "confusion", "probe_score": 0.7274, "luna_label": 1, "luna_reason": null}, {"key": "sample:jad_paddy_docs:000007:8:1:2", "start": 1542, "end": 1555, "surface": "Eurostat data", "probe_tag": "confusion", "probe_score": 0.7274, "luna_label": 1, "luna_reason": null}]}, {"key": "aj2-076", "text": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n# Glossary List of charts and tables\n\n\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n\n**GUS** - Główny Urząd Statystyczny, Polish statistical office, also known as Statistics Poland.\n**LFS** - Labour Force Survey, Eurostat labour market survey conducted by national statistical offices.\n**MSNA** - Multi-Sector Needs Assessment, a 2023 UNHCR survey of refugees from Ukraine.\n**PESEL/PESEL UKR** - Powszechny Elektroniczny System Ewidencji Ludności, Universal Electronic System for Registration of the Population.\nAn ID number of every Polish citizen. **PESEL UKR** is a version issued to Ukrainian citizens in connection with the armed conflict in the\nterritory of that country.\n**Poviat** - a middle tier of sub-central government in Poland between voivodship (province) and gmina (commune) level.\n**Pre-war Ukrainian migrants** - persons who migrated from Ukraine, primarily for economic reasons, before the full-scale Russian\ninvasion of Ukraine in February 2022.\n**SEIS** - Socio-Economic Inclusion Survey, a 2024 UNHCR survey of refugees from Ukraine as a follow-up to MSNA from the year before.\n**Ukrainian refugees** - persons fleeing Ukraine after the full-scale Russian invasion in February 2022, covered by EU's Temporary\nProtection Directive.\n**ZUS** - Zakład Ubezpieczeń Społecznych, Polish social security administration, also known as Social Insurance Institution.\n\n\n44\n\n\n\nChart 1. Poland-Ukraine border movement balance and registered/active PESEL data\b 07\nChart 2. Ukrainians registered for social insurance\b 07\nChart 3. Number of Ukrainians registered in Poland for social", "source": "jad_paddy_docs", "subset": "annotate_aj_part2", "spans": [{"key": "sample:jad_paddy_docs:000001:22:0:0", "start": 297, "end": 316, "surface": "Labour Force Survey", "probe_tag": "keep", "probe_score": 0.9765, "luna_label": 0, "luna_reason": null}, {"key": "sample:jad_paddy_docs:000001:22:0:1", "start": 318, "end": 347, "surface": "Eurostat labour market survey", "probe_tag": "keep", "probe_score": 0.9974, "luna_label": 0, "luna_reason": null}, {"key": "sample:jad_paddy_docs:000001:22:0:2", "start": 402, "end": 431, "surface": "Multi-Sector Needs Assessment", "probe_tag": "confusion", "probe_score": 0.8511, "luna_label": 0, "luna_reason": null}, {"key": "sample:jad_paddy_docs:000001:22:0:3", "start": 1082, "end": 1113, "surface": "Socio-Economic Inclusion Survey", "probe_tag": "confusion", "probe_score": 0.8576, "luna_label": 1, "luna_reason": null}]}, {"key": "aj2-077", "text": " refugees is for persons with PESEL UKR registered for social security on 30th September 2023. It\nis then compared to the general population by nine main occupational groups from GUS LFS in Q2 2023 and earnings from GUS (2023) “Structure\nof wages and salaries by occupation in October 2022”, and by detailed occupations workers and earnings from GUS (2022) “Structure of wages and\nsalaries by occupations in October 2020”.\n\n\n\n**Note:** Earnings in poviat Lubiński are so high, as it is the site of KGHM, state-owned copper mining corporation.\n\n\n**Source:** Deloitte own elaboration based on ZUS, and Statistics Poland data.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n32\n\n\n\n33", "source": "jad_paddy_docs", "subset": "annotate_aj_part2", "spans": [{"key": "sample:jad_paddy_docs:000007:16:4:0", "start": 591, "end": 594, "surface": "ZUS", "probe_tag": "drop", "probe_score": 0.0002, "luna_label": 1, "luna_reason": null}, {"key": "sample:jad_paddy_docs:000007:16:4:1", "start": 600, "end": 622, "surface": "Statistics Poland data", "probe_tag": "keep", "probe_score": 0.9696, "luna_label": 1, "luna_reason": null}]}, {"key": "aj2-078", "text": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n#### **Productivity shock rationale**\n\n\n\nAs Ukrainian refugees entered the labour\nmarket, the economy adapted in line\nwith expectations based on scientific\nliterature, resulting in greater specialisation\nand higher productivity. In a simplistic\nsupply-demand framework akin to the\n“canonical model”, the influx of Ukrainian\nrefugees should have caused some Polish\nworkers to become unemployed or leave\nthe labour force, or real wages to fall.\nEven in the Deloitte D.Climate model,\nUkrainian refugees add 0.4 percentage\npoints to the unemployment rate and\nlower real wages by 1.35% in 2024 when\nit is not counterbalanced by an additional\npositive productivity shock. However,\nthis is not what we observe in empirical\ndata. First, Polish citizens employment\n\n\n\nrates have grown, and unemployment\nrates have fallen. Second, poviats in\nwhich the employment share of Ukrainian\nrefugees has grown by 1 percentage point,\nexperienced higher by 0.5 percentage\npoint Polish citizens employment rates, and\n0.3 percentage point lower unemployment\nrates. Third, there is no evidence of\nlowered wages; in fact, the limited available\ndata suggests that Ukrainian refugees\nmay have caused higher wage growth in\npoviats to which they have moved. These\nare common findings in the scientific\nliterature quoted in the previous section,\nthat as immigrants enter the labour\nmarket, native workers tend to specialise\nin higher-value, complementary tasks.\nThis is evident in Polish workers moving to\n\n\n\nmore attractive occupational groups. This\nconstitutes a positive productivity shock,\ncounterbalancing labour market pressures.\n\n\nFirst, the employment rate of Polish citizens\nhas been growing since the Ukrainian\nrefugee influx, while the unemployment\nrate has been falling. This is particularly\nevident among women, who make up the\nmajority of refugees. The employment\nrate for women aged 20-64 has grown\nconsistently from 68.2% in Q2 2021 to\n70.2% in Q2 2022, 71.7%", "source": "jad_paddy_docs", "subset": "annotate_aj_part2", "spans": [{"key": "sample:jad_paddy_docs:000001:19:0:0", "start": 780, "end": 794, "surface": "empirical\ndata", "probe_tag": "keep", "probe_score": 0.9833, "luna_label": 1, "luna_reason": null}, {"key": "sample:jad_paddy_docs:000001:19:0:1", "start": 1175, "end": 1197, "surface": "limited available\ndata", "probe_tag": "drop", "probe_score": 0.0328, "luna_label": 1, "luna_reason": null}]}, {"key": "aj2-079", "text": "**The World Bank**\nSouth Sudan Emergency Food and Nutrition Security Project (P163559)\n\n\n**ANNEX 4: ENVIRONMENT AND SOCIAL SAFEGUARDS ACTION PLAN**\n\n\n**COUNTRY: South Sudan**\n**South Sudan Emergency Food and Nutrition Security Project**\n\n_The following section outlines the requirements of the Environmental and Social Safeguards Action Plan_\n_that has been prepared to ensure compliance with safeguards in line with the World Bank’s Operational_\n_Policy OP 10.00 paragraph 12._\n\n**Background**\n\nThe proposed South Sudan EFNSP is prepared and implemented according to Paragraph 12 of the\nWorld Bank’s Operational Policy 10.00, which allows for certain exceptions to the requirements of the IPF\npolicy, including deferral of safeguards requirements, if the Bank deems the client to be in urgent need of\nassistance.\n\n\n**Almost twelve years after gaining autonomy and then subsequent independence in 2011, South**\n**Sudan still struggles to break out of the conflict trap.** Conflict resumed in December 2013 and, despite a\nbrief period of optimism following the Agreement for the Resolution of Conflict signed in August 2015,\nstill continues. The conflict started in Juba and then was focused on the Greater Upper Nile Region;\nhowever recently there has been organized violence in previously peaceful areas such as Central and\nEastern Equatoria. The hostilities and unrest have led to massive displacement (both because of the\nfighting itself as well as fear of the violence). Available statistics indicate that over 2 million persons are\nnow internally displaced including over 200,000 civilians who have sought protection in the UN PoC sites\nacross the country. Further, some 1.4 million persons have sought refuge in neighboring countries.\n\n\n**Conflict has resulted into a near collapse of the economy.** Currently, the country exhibits all the\nsigns of macroeconomic collapse. There have been sharp declines in output, and a spike in the parallel\nexchange market premium.", "source": "jdc_operational", "subset": "annotate_aj_part2", "spans": [{"key": "sample:jdc_operational:000038:69:0:0", "start": 1475, "end": 1495, "surface": "Available statistics", "probe_tag": "keep", "probe_score": 0.968, "luna_label": 1, "luna_reason": null}]}, {"key": "aj2-080", "text": " mobile money, can give women access to a safe and private savings platform, which can alleviate some of the pressures\n\n\n16 Campos et al. 2015. “Breaking the Metal Ceiling Female Entrepreneurs Who Succeed in Male-Dominated Sectors.” Policy Research\nWorking Paper 7503. December.\n17 World Bank 2019. Profiting from Parity: Unlocking the Potential of Women’s Business in Africa. Washington DC.\n18 Government of Uganda 2018. National Labour Force Survey. UBOS.\n19 Campos, F., Frese, M., Goldstein, M., Iacovone, L., Johnson, H. C., McKenzie, D., and Mensmann, M. 2017. “Teaching personal\ninitiative beats traditional training in boosting small business in West Africa.” _Science_, _357_ (6357), 1287-1290.\n20 Urgent Action Fund 2019. Baseline study: <u>[https://eassi.org/wp-content/uploads/2020/03/Communiqu%C3%A9-on-Women-](https://eassi.org/wp-content/uploads/2020/03/Communiqu%C3%A9-on-Women-Economic-Empowerment-Convening-in-Kampala-2020.pdf)</u>\n<u>[Economic-Empowerment-Convening-in-Kampala-2020.pdf](https://eassi.org/wp-content/uploads/2020/03/Communiqu%C3%A9-on-Women-Economic-Empowerment-Convening-in-Kampala-2020.pdf)</u>\n21 World Bank 2021. High Frequency Phone Survey; Interviews with CARE, IRC, UN Women, April 2021; UNHCR 2020. Inter-", "source": "jdc_operational", "subset": "annotate_aj_part2", "spans": [{"key": "sample:jdc_operational:000005:6:2:0", "start": 422, "end": 450, "surface": "National Labour Force Survey", "probe_tag": "keep", "probe_score": 0.9629, "luna_label": 0, "luna_reason": null}]}, {"key": "aj2-081", "text": ", undermined trust in governmental institutions**\n**and increased existing pressures for emigration** . Even before the explosion, the fallout of the economic\ncrisis and the pandemic had led to a significant increase in poverty and a shrinking middle class. The Fall\n2021 LEM estimated that poverty rates have surged from 28% in 2019 to 55.3% in 2020. <sup>14</sup> [^14: Lebanon Economic Monitor, Fall 2020. World Bank.] As of Spring\n2021, projections using older data suggest that well over half of Lebanon’s population was under the\n\n\n5 Lebanon Economic Monitor, Spring 2021. World Bank.\n6 Lebanon Economic Monitor, Fall 2020. World Bank.\n7 Bank Byblos (February 2020) Lebanon This Week ‘Lebanon’s expats’ remittances drop by 20% in H1 of 2020 in Xinhuanet.\n8 Lebanon Economic Monitor, Spring 2021. World Bank.\n9 World Food Program (December 2020) Lebanon, VAM Update of Food Price and Market Trends.\n<u>[https://reliefweb.int/sites/reliefweb.int/files/resources/WFP-0000122981.pdf](https://reliefweb.int/sites/reliefweb.int/files/resources/WFP-0000122981.pdf)</u>\n10 <u>[https://www.unicef.org/lebanon/media/5616/file](https://www.unicef.org/lebanon/media/5616/file)</u>\n11 <u>[https://reliefweb.int/report/lebanon/vasyr-2020-key-findings-2020-vulnerability-assessment-syrian-refugees-lebanon](https://reliefweb.int/report/lebanon/vasyr-2020-key-findings-2020-vulnerability-assessment-sy", "source": "jdc_operational", "subset": "annotate_aj_part2", "spans": [{"key": "sample:jdc_operational:000002:3:2:0", "start": 262, "end": 275, "surface": "Fall\n2021 LEM", "probe_tag": "keep", "probe_score": 0.9986, "luna_label": 1, "luna_reason": null}, {"key": "sample:jdc_operational:000002:3:2:1", "start": 372, "end": 396, "surface": "Lebanon Economic Monitor", "probe_tag": "keep", "probe_score": 0.999, "luna_label": 1, "luna_reason": null}, {"key": "sample:jdc_operational:000002:3:2:2", "start": 459, "end": 469, "surface": "older data", "probe_tag": "keep", "probe_score": 0.9909, "luna_label": 1, "luna_reason": null}]}, {"key": "aj2-082", "text": "\nbalanced regional development; c) promoting urban competitiveness and productivity for employment\ncreation; d) promoting urban environmental conservation and protection, climate change, mitigation and\nadaptation mechanisms; and e) promoting good urban governance <sup>12</sup> [^12: The Policy has been adopted but has not yet been launched.] .\n\n8. **_Furthermore, the influx of refugees in Uganda is currently a major challenge, stretching LG_**\n**_capacities for service delivery due to the rapid increase in population._** Uganda is currently the largest host\nof refugees in Africa and the third-largest host in the world, with over 1.4 million refugees. Refugees settled\nin Northern Uganda, predominantly in the West-Nile sub-region, now constitute more than one-third of\ndistrict populations <sup>13</sup> [^13: Data from UNHCR shows that as of December 17, 2017, the districts of Arua, Yumbe, Moyo, Adjumani and Lamwo host a total\nof 971,572 refugees in addition to a host population of 1,832,831 nationals.], with refugee population in Moyo and Adjumani districts constituting close to 60\npercent. Uganda has one of the most progressive refugee regimes in the world, where refugees have right to\nwork, establish business, move freely within the country, access social services, own property, and obtain\ndocumentation. Refugees are also given plots of land on which to cultivate and build houses. This is putting\nenormous pressure on LGs’ ability to provide adequate infrastructure and services to this rapidly increased\npopulation, given that refugees are not limited to refugee settlements and can freely move to urban areas and\naccess services. The influx of around 900,000 refugees from South Sudan since July 2016 is stretching local\nplanning systems and capacities in Northern Uganda to the limit, in one of the poorest and most underserved\nsub-regions in the country. Recently, there has also been an increase in new arrivals from DRC who are\npredominantly settled in the Western and South West", "source": "jdc_operational", "subset": "annotate_aj_part2", "spans": [{"key": "sample:jdc_operational:000006:10:1:0", "start": 818, "end": 833, "surface": "Data from UNHCR", "probe_tag": "keep", "probe_score": 0.9961, "luna_label": 1, "luna_reason": null}]}, {"key": "aj2-083", "text": "**The World Bank**\nUganda Digital Acceleration Project – GovNet (P171305)\n\n\n\n|ANALYSIS:<br>Gender Gaps in Uganda|ACTIONS:<br>Proposed Actions under the<br>Project|INDICATORS:<br>Included in the<br>Results<br>Framework to<br>monitor progress|\n|---|---|---|\n|**Low ownership of mobile devices and access to Internet**<br>• <br>Gender gaps in ownership and access to Internet-enabled<br>devices. In Uganda there is a 4 percent urban gender gap in<br>mobile ownership while in rural areas it is over five times that,<br>at 22 percent. Overall percentage of women Internet users is a<br>mere 13 percent compared to men who access the Internet at<br>24 percent (Global System for Mobile Communications<br>Association [GSMA] 202064).<br>• <br>Gender gap in Internet use, estimated at 25 percent between<br>men and women (RIA 201965). A key barrier to access of the<br>Internet is lack of affordable points of access and high costs of<br>devices. An estimated 42 percent of women in Uganda cite the<br>cost of handsets as a barrier to mobile Internet use versus 29<br>percent of men (GSMA 201566).<br>• <br>While Internet access has become more affordable,<br>particularly on mobile phones, costs are still expensive for<br>many Ugandans, especially the women who have no<br>significant sources of income (Freedom House 201867). Figures<br>from the 2014 Uganda National Population and Housing<br>Survey indicate that 32 percent of women were not involved<br>in any", "source": "jdc_operational", "subset": "annotate_aj_part2", "spans": [{"key": "jdc_operational:000023:63:0:0", "start": 1341, "end": 1384, "surface": "2014 Uganda National Population and Housing", "probe_tag": "keep", "probe_score": 0.9356, "luna_label": 1, "luna_reason": "Named 2014 Uganda survey supports a concrete finding about women’s participation."}]}, {"key": "aj2-084", "text": "**The World Bank**\nGenerating Growth Opportunities and Productivity for Women Enterprises Uganda Project (P176747)\n\n\nto climate change impacts but are also stewards of environmental management, have rich traditional knowledge and\nexperience adapting to climate change, and have great potential to contribute green, resilient recovery of the Ugandan\neconomy.\n\n**_Refugees and Host Communities_**\n\n5. **Uganda hosts the largest number of refugees in Africa, of which 52 percent are female.** Their number has more\nthan doubled since 2015 to almost 1.6 million. <sup>5</sup> [^5: United Nations High Commissioner for Refugees (UNHCR) and the Office of the Prime Minister (OPM). 2022. Uganda Comprehensive Refugee\nResponse Poral.] About 94 percent of the refugees live in settlements across 12 Refugee\nHosting Districts (RHDs) with a population of 4,437,500 people (excluding Kampala), while the remainder live in urban\nareas. GoU has invested consistently in improving access to services, infrastructure and livelihoods opportunities for\nrefugees and hosting communities both in rural and urban settings. There is a working age population (between 18 and\n59) in refugee hosting districts of more than 315,000 refugee women and 918,000 host community women. <sup>6</sup> [^6: Host community numbers are UNHCR and OPM figures based on projected UBOS 2020 census data for women aged 20-59.] Half of all\nrefugee households are headed by women. <sup>7</sup> [^7: World Bank. 2019 Informing the Refugee Policy Response in Uganda: Results from the Uganda Refugee and Host Communities 2018 Household\nSurvey (English). Washington, DC: World Bank.]\n\n6. **Uganda’s refugee population is overwhelmingly young and female, highly vulnerable to climate and other**\n**shocks, and heavily dependent on government aid** . For refugee women, reduced humanitarian assistance and fewer\nfood rations coupled with the lockdowns-19", "source": "jdc_operational", "subset": "annotate_aj_part2", "spans": [{"key": "jdc_operational:000025:12:0:0", "start": 1340, "end": 1361, "surface": "UBOS 2020 census data", "probe_tag": "keep", "probe_score": 0.9437, "luna_label": 1, "luna_reason": "Census data underpins projected host community population figures."}, {"key": "jdc_operational:000025:12:0:1", "start": 1538, "end": 1595, "surface": "Uganda Refugee and Host Communities 2018 Household\nSurvey", "probe_tag": "keep", "probe_score": 0.9647, "luna_label": 1, "luna_reason": "Named household survey cited as evidence for female-headed refugee households."}]}, {"key": "aj2-085", "text": "ABBREVIATIONS AND ACRONYMS\n\n\n|BoU|Bank of Uganda|\n|---|---|\n|COVID-19|Coronavirus Disease 2019|\n|CPF|Country Partnership Framework|\n|DA|Designated Account|\n|DLG|District Local Government|\n|DRC|Democratic Republic of Congo|\n|EMIS|Education Management Information System|\n|ESCP|Environmental and Social Commitment Plan|\n|ESMP|Environmental and Social Management Plan|\n|FM|Finance Management|\n|GBV|Gender Based Violence|\n|GDP|Gross Domestic Product|\n|GoU|Government of Uganda|\n|GPE|Global Partnership for Education|\n|GRS|Grievance Redress Service|\n|HCI|Human Capital Index|\n|ICWMP|Infectious Control and Waste Management Plan|\n|IDA|International Development Association|\n|IFR|Interim Financial Report|\n|IPC&WMP|Infection Prevention and Control and Waste Management Plan|\n|IRR|Internal Rates of Return|\n|LMP|Labor Management Plan|\n|M&E|Monitoring and Evaluation|\n|MOES|Ministry of Education and Sports|\n|NCDC|National Curriculum Development Center|\n|NPV|Net Present Values|\n|OHS|Occupational, Health and Safety|\n|PCU|Project Coordination Unit|\n|RDCs|Resident District Commissioners|\n|RFQ|Requests for Quotations|\n|SEA|Sexual Exploitation and Abuse|\n|SEP|Stakeholder Engagement Plan|\n|SH|Sexual Harassment|\n|SMCs|School Management Committees|\n|SSA|Sub-Saharan Africa|\n|TA|Technical Assistance|\n|TFR|Total Fertility Rate|\n|UNHS|Uganda National Household Survey|\n|UNICEF|The United Nations Children's Fund|\n|UPE|Universal Primary Education|\n|UPPET|Universal Primary Education and Training Project|", "source": "jdc_operational", "subset": "annotate_aj_part2", "spans": [{"key": "sample:jdc_operational:000034:2:0:0", "start": 1322, "end": 1354, "surface": "Uganda National Household Survey", "probe_tag": "confusion", "probe_score": 0.3001, "luna_label": 0, "luna_reason": "Abbreviation-table entry merely defines the survey name without showing data use."}]}, {"key": "aj2-086", "text": "**The World Bank**\nCHAD Improving Learning Outcomes Project (P175803)\n\n\n12. **Learning Poverty (LP) in Chad is very high, at 98 percent, meaning that almost no child aged 10 is able to read**\n**and understand a simple age-appropriate text.** This LP level is 11 percentage points worse than the average for the SubSaharan Africa region and 8 percentage points worse than the average for low-income countries. At the end of primary,\nonly 22 percent and 12 percent of students achieved a satisfactory level of reading and mathematics, respectively, in the\nPASEC international learning outcomes survey conducted in 2019. This contrasted with the 48 percent and 38 percent\naverages observed among 14 participating countries. There were gender differences in performance, with boys doing\nbetter in both reading (456 vs. 444 for girls) and mathematics (442 vs. 432 for girls). Between 2014 and 2019, the average\npercentage of end- of primary students achieving a satisfactory performance in reading and mathematics was relatively\nunchanged (18 percent vs. 17 percent, respectively). <sup>11</sup> [^11: PASEC. _Qualité des Systèmes Éducatifs en Afrique SubSaharienne Francophone. Performances et Environnement de l’Enseignement-Apprentissage_\n_au Primaire_ . Hereafter referred to as PASEC 2014 and 2019, the years in which the learning outcomes surveys were conducted.] The evidence also suggests that learning outcomes are markedly\nhigher in urban than rural schools; and among children in the highest socioeconomic bracket. There was no statistically\nsignificant difference in the reading and mathematics scores between students attending public or community schools. <sup>12</sup> [^12: PASEC 2019.]\nIt should be noted that whereas 65 percent public school teachers are state-qualified teachers (graduates of the ENIBs),\namong community schools only 38 percent are ENIB graduates, while 22 percent have received 90 days of in-service\ntraining and 40 percent no pedagogical training at all.\n\n\n13. There are several proximate causes that help to explain these", "source": "jdc_operational", "subset": "annotate_aj_part2", "spans": [{"key": "jdc_operational:000009:6:0:0", "start": 554, "end": 598, "surface": "PASEC international learning outcomes survey", "probe_tag": "confusion", "probe_score": 0.8528, "luna_label": 1, "luna_reason": "Survey provides learning achievement figures and is identified as PASEC 2019."}]}, {"key": "aj2-087", "text": "➢❨¢ Conduct relevant training and dissemination workshops\n➢❨¢ Develop a manual for the indicators metadata and extraction of various indicators by\ndataset.\n\nComponent 4: Institutionalize National Health Accounts ($56,950)\n\nThe escalating financial pressure created by the Syrian crisis, and the resurgence of unprecedented\nconsumption of health goods and services accompanied with unorganized financial flows, has\nbrought to the picture the need for a solid, well established, institutionalized National Health\nAccounts (NHA). The production of NHA surveys are largely linked to Household Surveys (HHS),\nand in the absence of a HHS in the past, all NHA figures are based on projections rather than\nupdated data. A new NHA was conducted in 2012, based on the data from the latest household\nsurvey (2011-2012) conducted by the CAS in collaboration with the World Bank.\nThe purpose of this component is to institutionalize NHA based on the new System of Health\nAccounts (SHA) 2.0. The new systems allows the production of a NHA between two time periods;\nthe actual NHA (t1) data and the year of the study (t2). Specific activities under this component will\ninclude:\n➢❨¢ Development of a platform that can extract NHA data from the various public funds based\non the structure of the Health Accounts Production Tool (NHAPT). This platform will be tailored to\nthe specific needs of the different public funds to facilitate the timely collection, tabulation, and\nanalysis of the data for NHA\n➢❨¢ Assign trained focal points at each public fund\n➢❨¢ Conduct training workshop(s) for the designated focal points on the new system\n➢❨¢ Provide on-the-job training and support to the focal points at the public funds for\nimplementation\n➢❨¢ Conduct the NHA survey based on the new SHA2.0 and using the NHAPT\n➢❨¢ Analyze results\n➢❨", "source": "jdc_operational", "subset": "annotate_aj_part2", "spans": [{"key": "jdc_operational:000046:4:0:0", "start": 579, "end": 596, "surface": "Household Surveys", "probe_tag": "confusion", "probe_score": 0.6003, "luna_label": 0, "luna_reason": "Generic survey category is mentioned without an attributed finding or concrete data use."}, {"key": "jdc_operational:000046:4:0:1", "start": 779, "end": 795, "surface": "household\nsurvey", "probe_tag": "confusion", "probe_score": 0.4297, "luna_label": 1, "luna_reason": "Existing household survey data directly supported the 2012 National Health Accounts."}, {"key": "jdc_operational:000046:4:0:2", "start": 1739, "end": 1749, "surface": "NHA survey", "probe_tag": "confusion", "probe_score": 0.6903, "luna_label": 0, "luna_reason": "Survey is planned to be conducted, so it represents future data production."}]}, {"key": "aj2-088", "text": "|Project Development Objective Indicators|Col2|\n|---|---|\n|**Indicator Name : **|**Description (indicator definition etc.) **|\n|Direct project beneficiaries of safety net programs<br>(individuals), of which women (%)|Direct beneficiaries of safety net programs are the number of NPTP card holders.|\n|Beneficiaries of safety net programs (number), of<br>which are e-card food vouchers|The breakdown of beneficiaries of which are e-card food voucher beneficiaries.|\n|NPTP beneficiaries from extremely poor households<br>as a share of total NPTP beneficiaries.|Beneficiaries=NPTP card holders.<br>Extreme poverty=$3.84/day per person in 2012 prices.|\n|Number of NPTP Applicants|Households that have applied to the program.|\n|Time Lapse between application and eligibility<br>notification|Acceptance notification must be accompanied by a benefits card (not<br>cumulative).|\n|Household awareness of NPTP|Percentage of respondents to the opinion poll survey that have head of the NPTP.|\n|Proportion of assisted people informed about the e-<br>card food program (who is included, what people<br>receive, and where they can complain)|Households that have been provided training in SDCs on the e-card food voucher<br>system.|\n|||\n\n\n24", "source": "jdc_operational", "subset": "annotate_aj_part2", "spans": [{"key": "sample:jdc_operational:000047:34:0:0", "start": 932, "end": 951, "surface": "opinion poll survey", "probe_tag": "confusion", "probe_score": 0.8978, "luna_label": 0, "luna_reason": null}]}, {"key": "aj2-089", "text": " the population, although phone ownership\nrates are higher among urban residents compared to rural residents. <sup>21</sup> The telecommunications market includes\ntwo major private operators (MTN and Airtel) that control market shares (in terms of mobile subscriptions) at 37\npercent and 45 percent, respectively, and other mobile operators, such as Uganda Telecom and Africell, with\nmarket shares below 10 percent each. <sup>22</sup> The increased access to mobile phones and mobile services in Uganda\nhas enabled the take-up of related services such as mobile banking, demonstrated by the latest available 2017\n\n\n18 Uganda Digital Economy for Africa (DE4A) Report, Country Diagnostic, 2020.\n19 Uganda Digital Economy for Africa (DE4A) Report, Country Diagnostic, 2020.\n20 World Bank. 2020. Uganda Economic Update, 15th Edition _D_ igital Solutions in a Time of Crisis _: Uganda Economic Update, 15th Edition,_\n_July 2020_ .\n21 NITA-U (National Information Technology Authority of Uganda). 2018. National Information Technology Survey 2017/18 Report. NITA\nUganda, March 2018\n22 NITA-U (National Information Technology Authority of Uganda). 2018. National Information Technology Survey 2017/18 Report. NITA\nUganda, March 2018.\n\n\nPage 3 of 76", "source": "jdc_operational", "subset": "annotate_aj_part2", "spans": [{"key": "jdc_operational:000023:15:2:0", "start": 997, "end": 1050, "surface": "National Information Technology Survey 2017/18 Report", "probe_tag": "confusion", "probe_score": 0.7676, "luna_label": 1, "luna_reason": "Named survey report cited as the source for telecommunications and mobile-service findings."}]}, {"key": "aj2-090", "text": " the Systematic**\n**Country Diagnostic (SCD) and unlocking new opportunities.** Constraints such as poor infrastructure, weak public\nservice delivery, low levels of human capital, and underdeveloped institutions elaborated in the country’s SCD <sup>54</sup> can\nbe mitigated by the Digital sector in several ways. The fast-growing Digital sector poses significant investment and\njob creation potential. Progress toward achieving greater digital connectivity within the country and across the region\n\n\n[51 Uganda UN eGovernment Survey 2018. https://publicadministration.un.org/egovkb/en-us/Resources/E-Government-Survey-in-](https://publicadministration.un.org/egovkb/en-us/Resources/E-Government-Survey-in-Media/ID/1945/Uganda-Improves-in-Government-Online-Service-Delivery-UN-Survey)\n<u>[Media/ID/1945/Uganda-Improves-in-Government-Online-Service-Delivery-UN-Survey](https://publicadministration.un.org/egovkb/en-us/Resources/E-Government-Survey-in-Media/ID/1945/Uganda-Improves-in-Government-Online-Service-Delivery-UN-Survey)</u>\n52 World Bank Enterprise Surveys 2013.\n53 Digital Uganda Vision. Draft 1.17. 2019. Ministry of ICT and National Guidance Uganda.\n54 Boosting Inclusive Growth and Accelerating Poverty Reduction, Uganda Systematic Country Diagnostic, World Bank, 2015.\n\n\nJul 22, 2019 Page 8 of 28", "source": "jdc_operational", "subset": "annotate_aj_part2", "spans": [{"key": "jdc_operational:000063:7:2:0", "start": 505, "end": 538, "surface": "Uganda UN eGovernment Survey 2018", "probe_tag": "keep", "probe_score": 0.9515, "luna_label": 1, "luna_reason": "Named survey cited as an existing external data resource."}, {"key": "jdc_operational:000063:7:2:1", "start": 1036, "end": 1070, "surface": "World Bank Enterprise Surveys 2013", "probe_tag": "confusion", "probe_score": 0.8748, "luna_label": 1, "luna_reason": "Named World Bank Enterprise Survey source cited in a footnote."}]}, {"key": "aj2-091", "text": "-grant agreements and agreed list of eligible\nexpenditures.\n\n22. **Training and Implementation Support:** The World Bank will provide focused training\nto participating municipalities on the World Bank FM and disbursement guidelines and\nprocedures, and will provide close support during the first year of Project implementation.\n\n_Disbursement Arrangements_\n\n23. The proceeds of the Grant will be disbursed in accordance with the World Bank's\ndisbursements guidelines as outlined in the Disbursement Letter and in accordance with the\nWorld Bank Disbursement Guidelines for Projects. Disbursements will be Report-based; the\ninitial disbursement for CVDB will be submitted to the Bank after Project effectiveness, based\non the forecast for two (2) quarters as provided in the quarterly IFRs. Thereafter, disbursements\nwill be made into the Designated Account (DA) based on quarterly IFRs which would provide\nactual expenditure for the preceding quarter (three months) and cash flow projections for the next\ntwo quarters (six months). All supporting documentation will be retained at CVDB. They will be\nkept in a manner readily accessible for review by Bank missions and internal and external\nauditors.\n\n24. The supporting documentation for reporting eligible expenditures paid from the DA will\nbe summary reports and records evidencing eligible expenditures for payments against contracts\nfor prior and post reviews. The supporting documentation for direct payment requests should be\nrecords evidencing eligible expenditures (i.e., copies of receipts, suppliers' invoices, etc.). CVDB\nwill prepare quarterly IFRs in form and content satisfactory to the Bank. The format and content\nof the IFR will be agreed upon between the Bank and CVDB. The contents of the IFR will\n\n\n39", "source": "jdc_operational", "subset": "annotate_aj_part2", "spans": [{"key": "jdc_operational:000026:50:1:0", "start": 773, "end": 787, "surface": "quarterly IFRs", "probe_tag": "confusion", "probe_score": 0.0737, "luna_label": 0, "luna_reason": "Project financial reports used for disbursement administration, not substantive data analysis."}]}, {"key": "aj2-092", "text": " limited domestic contracting capacity to conduct\nprojects of this complexity and scope; (b) NITA-U staff and partner agencies not familiar with Procurement\nRegulations (July 2016, revised January 2020); (c) underestimation of the cost of contracts; (d) NITA-U has a\nvacancy rate of 58 percent, resulting in gaps in technical staff to support the project; (e) inadequate storage space\nfor procurement records; (f) delays in commencement of procurement processing due to late preparation of E&S\nsafeguards studies; (g) gaps in the bidding documents leading to many inquiries from bidders prolonging the\nbidding process; (h) heavy workload on Procurement Unit resulting in delays in procurement processing; (i)\ninadequate stakeholder engagements in project area resulting in delays in contract execution; (j) delayed site\nhandover to contractors for construction due to delays in implementation of the Resettlement Action Plan (RAP);\n(k) bid tampering during project implementation; (l) forgery of documentation and misrepresentation of\nqualification requirements in the bids; and (m) delays in implementation at different stages of the procurement\ncycle.\n\n**84.** **Preliminary risk mitigation measures:** These will include, (a) wider dissemination of bidding opportunities to\nreach international and regional markets to elicit participation from the capable providers; (b) trainings for staff\non World Bank Procurement Regulations; (c) prepare and disseminate the Procurement Manual to all project\nimplementation staff; (d) conduct a market survey before procurement processing and update the cost estimate\nin the Procurement Plan if needed; (e) hiring of individual consultants to fill staffing gaps to ensure sufficient inhouse technical capacity (in skills and numbers); (f) purchase lockable cabinets and lockable cupboards for storage\nof both active and archived records; (g) E&S safeguards studies to commence timely; (h) an internal Quality\nAssurance Team shall review all UDAP-GovNet bidding documents to", "source": "jdc_operational", "subset": "annotate_aj_part2", "spans": [{"key": "jdc_operational:000023:43:1:0", "start": 1535, "end": 1548, "surface": "market survey", "probe_tag": "confusion", "probe_score": 0.0548, "luna_label": 0, "luna_reason": "Planned survey to be conducted before procurement, so data does not yet exist."}]}, {"key": "aj2-093", "text": "**The World Bank**\nUganda: Investment for Industrial Transformation and Employment (P171607)\n\n\n\n\n\n\n\n\n\n\n\n\n|Indicator Name|PBC|Baseline|Intermediate Targets|Col5|Col6|Col7|End Target|\n|---|---|---|---|---|---|---|---|\n|<br>|||**1 **|**2 **|**3 **|**4 **||\n|manufacturing sectors<br>(Number)||||||||\n|**Firm Acess to Finance**|**Firm Acess to Finance**|**Firm Acess to Finance**|**Firm Acess to Finance**|**Firm Acess to Finance**|**Firm Acess to Finance**|**Firm Acess to Finance**|**Firm Acess to Finance**|\n|Beneficiaries reached with<br>financial services (CRI,<br>Number)||0.00|50,000.00|100,000.00|130,000,000.00<br>|170,000,000.00|200,000.00|\n|Number of SMEs with a loan<br>or line of credit (CRI,<br>Number)|<br>|0.00|2,700.00||||5,300.00|\n|**Number of formally employed in the manufacturing sector according to PAYE data collected by URA TIN**|**Number of formally employed in the manufacturing sector according to PAYE data collected by URA TIN**|**Number of formally employed in the manufacturing sector according to PAYE data collected by URA TIN**", "source": "jdc_operational", "subset": "annotate_aj_part2", "spans": [{"key": "sample:jdc_operational:000021:56:0:0", "start": 817, "end": 847, "surface": "PAYE data collected by URA TIN", "probe_tag": "confusion", "probe_score": 0.8746, "luna_label": 1, "luna_reason": null}, {"key": "sample:jdc_operational:000021:56:0:1", "start": 921, "end": 951, "surface": "PAYE data collected by URA TIN", "probe_tag": "keep", "probe_score": 0.9709, "luna_label": 1, "luna_reason": null}]}, {"key": "aj2-094", "text": "u>(USh)</u>\n\n\n\n<u>Hours worked</u>\n\n\n\nper week\n\n\n\n<u>Hourly</u>\n\n\n\nwage per week wage wage per week wage\n<u>(USh)</u> <u>(Hrs.)</u> <u>(USh)</u> <u>(USh)</u> <u>(Hrs.)</u> <u>(USh)</u>\n\n<u>No schooling/below P1</u> <u>69,696</u> <u>37.8</u> <u>461</u> <u>93,970</u> <u>44.6</u> <u>527</u>\nSome primary 119,322 42.1 709 139,762 50.3 695\nPrimary completed 167,770 47.6 881 194,652 53.7 906\nSome lower secondary 182,227 55.3 824 201,804 57.1 884\nLower secondary completed 216,050 59.3 911 251,784 58.0 1,085\nSome or completed upper secondary 308,920 59.3 1,303 348,405 56.6 1,539\nPost-primary TVET 305,407 49.5 1,543 343,265 51.5 1,666\nPost-secondary TVET 353,743 48.9 1,807 456,475 49.8 2,292\nHigher/tertiary level of education 767,550 48.8 3,930 955,036 48.9 4,883\nData on educational level missing 173,136 37.8 1,145 371,596 45.1 2,060\n<u>Total</u> <u>194,926</u>", "source": "jdc_operational", "subset": "annotate_aj_part2", "spans": [{"key": "sample:jdc_operational:000018:93:1:0", "start": 764, "end": 797, "surface": "Data on educational level missing", "probe_tag": "confusion", "probe_score": 0.2814, "luna_label": 0, "luna_reason": null}]}, {"key": "aj2-095", "text": " immediate,**\n**and potentially long-lasting impact of the Syrian crisis on Lebanon**, while strengthening state\ninstitutions, addressing existing vulnerabilities, and bolstering efforts on longer term development\nchallenges, all through interventions that foster inclusion and shared prosperity. Specifically, the project\nwould support two focus areas of the CPF to renew the social contract between the state and the\ncitizens: (i) expand access to and quality of service delivery; and (ii) expand economic opportunities\nand increase human capital. The proposed Project will contribute to advancing CPF (FY17-FY22)\nobjectives. Poor delivery of electricity supply was identified in the Systematic Country Diagnostic (2015)\nas a binding constraint to Lebanon’s economic development. Inefficiencies in the electricity sector have\nripple effects on the lives of Lebanese citizens, not just because they increase the cost of living as\npeople cope with deficiencies in the quality of electricity services, but they can also have deleterious\nimpacts on job opportunities, education, and healthcare services. For women, limited access to reliable\nelectricity can increase the time they conduct specific household chores. It can also negatively impact\ntheir ability to engage in entrepreneurial activities, both inside and outside of the home. <sup>9</sup> Moreover,\nstudies have demonstrated that improved infrastructure has strong positive impacts not only on longrun economic growth, but also on income equality.\n\n19. **The Project also contributes to the updated Middle East and North Africa (MNA) Regional**\n**Strategy** <sup>**10**</sup> **and is aligned with the Maximizing Finance for Development (MFD) approach** The\n\n9 World Bank EEX Gender Follow Up Note, 2017.\n10 Middle East and North Africa Regional Update 2019 _- #OpenforBusiness,_ The World Bank Group\n\n\nJun 21, 2019 Page 9 of 14", "source": "jdc_operational", "subset": "annotate_aj_part2", "spans": [{"key": "jdc_operational:000010:8:3:0", "start": 686, "end": 715, "surface": "Systematic Country Diagnostic", "probe_tag": "confusion", "probe_score": 0.7734, "luna_label": 1, "luna_reason": "Diagnostic cited as evidence identifying electricity supply as an economic constraint."}]}, {"key": "aj2-096", "text": " the GOJ, while providing a buffer\nto help mitigate the impact of price risks driven by the current volatility and uncertainty in international\ncommodity markets, in particular on vulnerable households in Jordan. On the other hand, the investment and\nadvisory activities supported under Component 2 will contribute directly to strengthening the GOJ’s physical and\ninstitutional capacities over the medium-term to address future shocks in global commodity markets. These\ncapacity improvements will be driven by expanded physical grain storage capacities and an improved knowledge\nand information base to guide targeted investments and policy reforms in commodity value chains and regional\ntrading systems.\n\n**43.** **The ultimate results, going beyond the scope and lifetime of this project but being facilitated by it, are**\n**expected to be** : (i) more efficient and resilient import supply chains for basic agricultural commodities in Jordan,\n(ii) a more fiscally sustainable policy framework to strengthen food security and protect the most vulnerable\nhouseholds, and (iii) improved regional collaboration on managing supply and price risks associated with imports\nof basic agricultural commodities. To achieve this, the following gradual approach has been embedded in the\nproject design:\n\n\n(i) _In the short term (0-9 months)_, the focus will be on (i) ensuring minimum required levels of strategic\nreserves of wheat and barley are maintained; and (ii) analyzing options for improving import supply chain\nlogistics for selected agricultural commodities and for broader food policies to mitigate future shocks in basic\nagricultural commodity markets.\n(ii) _In the medium term (9-18 months)_, the focus will be on (i) investing in strategic grain storage capacities;\n\n\n34 The vulnerable households (poor Jordanian population and refugees, respectively) will be drawn and sampled based on the current WFP\nand UNHCR databases, respectively. The indicator will track bread consumption, specifically, rather than food security more broadly; the\nactual values will be determined through the high frequency surveys foreseen during project", "source": "jdc_operational", "subset": "annotate_aj_part2", "spans": [{"key": "sample:jdc_operational:000024:24:1:0", "start": 1911, "end": 1926, "surface": "UNHCR databases", "probe_tag": "keep", "probe_score": 0.9411, "luna_label": 1, "luna_reason": null}, {"key": "sample:jdc_operational:000024:24:1:1", "start": 2089, "end": 2111, "surface": "high frequency surveys", "probe_tag": "confusion", "probe_score": 0.2232, "luna_label": 0, "luna_reason": null}]}, {"key": "aj2-097", "text": " benefits to the population served by the roads.\n\n48. In the absence of comprehensive surveys on the above variables, the economic internal rate of\nreturn (EIRR) for USMID roads were obtained from previous studies with more or less the same\nenvironment to generate the stream of benefits. The Net Present Values show the net economic benefits\n\n\n75 Using up-dated population figures from FY 2017/18.\n\n\n60", "source": "jdc_operational", "subset": "annotate_aj_part2", "spans": [{"key": "sample:jdc_operational:000062:67:2:0", "start": 354, "end": 381, "surface": "up-dated population figures", "probe_tag": "confusion", "probe_score": 0.6286, "luna_label": 1, "luna_reason": null}]}, {"key": "aj2-098", "text": "</sup> The\nmost-affected area happened to be the vibrant epicenter of the city, driven by traditional and modern artisans\nthat were largely operating within its creative ecosystem, with a unique urban fabric embedded with historical\nbuildings hosting the production of CCI. The impact on the livelihoods of those working in CCIs, mainly youth,\nwomen, and marginalized groups, was devastating with an estimated 3,500 jobs lost as a result.\n\n\n**17.** **Many heritage buildings were neglected prior to the explosion.** Although new heritage initiatives have\nbeen formed to identify and stabilize affected heritage buildings, sufficient funding remains lacking. The absence\nof a housing policy and a legal framework for heritage buildings has generated difficulties for owners. The previous\nreconstruction history of Beirut depicts the controversial case of Solidere, where a lack of protection for heritage\nbuildings caused the private developers to buy the heritage property for lower costs and replace them with\n\n\n110 According to the Beirut RDNA ( _[https://www.worldbank.org/en/country/lebanon/publication/beirut-rapid-damage-and-needs-assessment-](https://www.worldbank.org/en/country/lebanon/publication/beirut-rapid-damage-and-needs-assessment-rdna---august-2020)_\n_[rdna---august-2020](https://www.worldbank.org/en/country/lebanon/publication/beirut-rapid-damage-and-needs-assessment-rdna---august-2020)_ ).\n111 Ibid.\n\n\nPage 57 of 66", "source": "jdc_operational", "subset": "annotate_aj_part2", "spans": [{"key": "jdc_operational:000012:62:1:0", "start": 1034, "end": 1045, "surface": "Beirut RDNA", "probe_tag": "confusion", "probe_score": 0.8514, "luna_label": 1, "luna_reason": "Named assessment cited as the source supporting the reported claim."}]}, {"key": "aj2-099", "text": ". The Project will include a broad range of activities that<br>will integrate climate change resilience and adaptation measures in transport infrastructure<br>construction design and maintenance, institutional capacity building, policy and planning<br>including contingency planning.<br>The Project Development Objectives are to enhance: (a) road transport connectivity in select<br>refugee hosting districts of Uganda; and (b) the capacity of Uganda National Roads Authority to<br>manage environmental, social and road safety risks. Part (a) of the PDO will be achieved through|\n\n\n\n_76_ [https://crudata.uea.ac.uk/cru/data/hrg/](https://crudata.uea.ac.uk/cru/data/hrg/) Current Datasets and Static Climatologies\n[77 https://catalogue.ceda.ac.uk/uuid/58a8802721c94c66ae45c3baa4d814d0](https://catalogue.ceda.ac.uk/uuid/58a8802721c94c66ae45c3baa4d814d0) Climatic Research Unit (CRU) Time-Series (TS) version 4.01 of\nhigh-resolution gridded data of month-by-month variation in climate (Jan. 1901- Dec. 2016)\n[78 https://climateknowledgeportal.worldbank.org/country/uganda/vulnerability](https://climateknowledgeportal.worldbank.org/country/uganda/vulnerability)\n\n\nPage 72 of 80", "source": "jdc_operational", "subset": "annotate_aj_part2", "spans": [{"key": "jdc_operational:000050:76:2:0", "start": 671, "end": 712, "surface": "Current Datasets and Static Climatologies", "probe_tag": "confusion", "probe_score": 0.1143, "luna_label": 0, "luna_reason": "Reference-link heading without shown data use or attributed finding."}, {"key": "jdc_operational:000050:76:2:1", "start": 915, "end": 982, "surface": "high-resolution gridded data of month-by-month variation in climate", "probe_tag": "confusion", "probe_score": 0.2466, "luna_label": 1, "luna_reason": "Cited existing climate dataset with temporal and spatial detail."}]}, {"key": "aj2-100", "text": "\n- The unit costs of centrally managed contracts under UTSEP are slightly higher in comparison to LG managed\ncontracts, and the price difference is due to the challenging locations of the centrally managed construction\nsites which are often located in hard to reach / northern territories (with expected higher cost of construction)\nand low LG capacity. Local communities and most of the LGs have limited capacity in procuring, managing and\nsupervising large construction contracts, thus the transaction costs to support contracts supervision are high.\nProcurement trough International Competitive Bidding (ICB) ends up with much higher costs than with\nNational Competitive Bidding (NCB) (AfDB-IV). The civil works will be managed centrally under the Project\nwith support from the LGs in supervising the contracts implementation.\n\n- Community-based procurement and contract management of school construction is highly cost-effective to\nbuild primary schools (2000-2004 SFG program; 2013-2014 Emergency program for primary schools) as well\nas secondary schools (2009-2014 UPPET). However, the quality of the supervision is challenging in these cases\nand could be associated with high centrally enforced supervision costs. Evidence from UPPET-APL1 shows that\nlarge contracts that exceed the school-communities’ management capacity lead to serious implementation\ndifficulties and delays.\n\n\n70. **Lessons related to promoting girls’ education incorporated into the Project design:**\n\n- Distance to lower secondary schools for young adolescents, especially girls from poor families, tends to raise\nopportunity costs and physical risks. Recent studies on child marriage and early pregnancy have shown that\nincreasing access to lower secondary schools, reducing costs of education for poor households, and providing\nincentives for girls to stay in school, are likely to have a positive effect on education access and attainment.\nThe project is addressing all three.\n\n- Current successful programs in Uganda show that it is critical to engage parents and communities in\nsupporting girls’ education. The Project will support such an approach under the Child Friendly School\nProgram", "source": "jdc_operational", "subset": "annotate_aj_part2", "spans": [{"key": "sample:jdc_operational:000018:32:1:0", "start": 1235, "end": 1245, "surface": "UPPET-APL1", "probe_tag": "confusion", "probe_score": 0.5887, "luna_label": 1, "luna_reason": null}]}, {"key": "aj2-101", "text": "br>Description:This indicator will measure the increase in percentage of population with access to jobs and services located at the CBD using public transport services. This<br>indicator captures the improved accessibility objective of the project for public transport passengers.|<br>Description:This indicator will measure the increase in percentage of population with access to jobs and services located at the CBD using public transport services. This<br>indicator captures the improved accessibility objective of the project for public transport passengers.|<br>Description:This indicator will measure the increase in percentage of population with access to jobs and services located at the CBD using public transport services. This<br>indicator captures the improved accessibility objective of the project for public transport passengers.|\n\n\n\n\n\n\n\n\n\n\n\n\n|Col1|Name: Average travel time<br>by public transport from<br>Tabarja station to Charles<br>Helou terminal at morning<br>peak hours|Col3|Minutes|75.00|45.00|Biannual|Data to be obtained from<br>the ITS.|CDR / the RPTA<br>BRT operators|Col10|\n|---|---|---|---|---|---|---|---|---|---|\n||<br>Description:Average rush hour in-vehicle travel time by the PT services from Tabarja station to Beirut (Charles Helou terminal) at morning peak hours between 7:00am<br>and 9:00am. This indicator measures the improved speed objective of the project  for public transport services.|<br>Description:Average rush hour in-vehicle travel time by the PT services from Tabarja station to Beirut (Charles Helou terminal) at morning peak hours between 7:00am<br>and 9:00am. This indicator measures", "source": "jdc_operational", "subset": "annotate_aj_part2", "spans": [{"key": "sample:jdc_operational:000022:47:2:0", "start": 1057, "end": 1060, "surface": "ITS", "probe_tag": "confusion", "probe_score": 0.424, "luna_label": 0, "luna_reason": "Future data retrieval from ITS is planned, not existing data use."}]}, {"key": "aj2-102", "text": "FRP)** . GFRP combined fast-track funding from the\nInternational Bank for Reconstruction and Development (IBRD) and International Development Association (IDA)\nwith trust fund grants to help governments address the immediate food crisis, while encouraging agricultural\npolicies that build countries’ resilience to future shocks. Key lessons reflected in the project design are summarized\nbelow:\n\n  - _Rapid response strategy_ **:** Food crisis response projects can be used as an opportunity to move forward a\nlonger-term agenda for improving resilience and sustaining development impact. As part of the preparation\nprocess, a follow-up operation should be considered that can build on the experiences of the emergency\noperation\n\n  - _Project design:_ A simple design of emergency operations is crucial for a rapid response. The design of the\nproject should focus on responding to the government’s short-term priority and to the urgent needs of the\nbeneficiaries, as a key factor in the project’s successful implementation.\n\n  - _Project monitoring and evaluation_ : Establishing an effective monitoring and evaluation (M&E) system in\nthe context of a crisis response operation is a challenge, but its importance should not be underestimated.\n\n\n**50** . **The project also builds on evidence from the implementation of Takaful, as it relates to monitoring.** The\nnational welfare support program “Takaful” has increased the use of digitization, and refinement of targeting\nbased on government coverage targets using national databases. Takaful has automated processes for online\nregistration, data verification, selection of households for field verification, as well as selection, enrollment, and\ndigital payment to beneficiaries through bank accounts and e-wallets. The Takaful database already includes\nadministratively verified and most up-to-date data for over one million households who applied earlier through\nthe Takaful platform for social assistance. Nevertheless, for registration of applicants, the National Aid Fund (NAF)\nreaches out to poor and vulnerable households in remote areas", "source": "jdc_operational", "subset": "annotate_aj_part2", "spans": [{"key": "jdc_operational:000024:27:1:0", "start": 1516, "end": 1534, "surface": "national databases", "probe_tag": "confusion", "probe_score": 0.477, "luna_label": 1, "luna_reason": "Existing databases inform refinement of household targeting."}, {"key": "jdc_operational:000024:27:1:1", "start": 1772, "end": 1788, "surface": "Takaful database", "probe_tag": "keep", "probe_score": 0.9091, "luna_label": 1, "luna_reason": "Existing Takaful database provides verified household data used for targeting and monitoring."}]}, {"key": "aj2-103", "text": " for COVID19 hospital claims and confirm that these expenditures are eligible as per the legal agreement and POM. In\naddition, and for better control over the vaccine stock, this technical audit will be conducting independent physical\nstock count of the COVID-19 vaccine doses at the vaccination sites and storage sites and reconciling the physical\nstock count with the MoPH stock reports. The PMU, from its end, will finalize the recruitment of a stock\nmanagement officer to monitor and validate the inventory of the vaccine stock which will help to align the stock\ncount between MoPH and the technical audit. In addition, the PMU will complete the procurement and\ninstallation of an accounting software to record transactions under the project and produce financial reports.\n\nh. _Budgeting:_ The WB funds will be channeled through the MoF Treasury Account and will be transferred to the\n\nproject accounts. A procurement plan and a disbursement plan for World Bank financing will be used to compare\nplanned expenditures with actual ones and monitor any variances. PMU will be preparing a separate annual\nbudget and a disbursement plan. The budget will be prepared on an annual basis and submitted to the World\nBank in November/December of each year covering the subsequent year. The PMU will monitor the variances in\nthe disbursement plan and will provide justification on any major divergence.\n\ni. _Project accounting system:_ The PMU does not have an accounting software to record transactions and produce\nfinancial reports. The same accounting software that is currently being procured under LHRP will be used under\nthe proposed project to record daily transactions and produce the required financial reports. The project Financial\nOfficer and Financial Assistant will be responsible for preparing the IFRs before their transmission to the Project\nDirector for approval. Project accounting will cover all sources and uses of project funds, including payments made\nand expenses incurred. All transactions related to the project will be recorded using the cash basis of accounting.\n\nj. _Project reporting:_ The project financial reporting includes", "source": "jdc_operational", "subset": "annotate_aj_part2", "spans": [{"key": "sample:jdc_operational:000000:54:1:0", "start": 370, "end": 388, "surface": "MoPH stock reports", "probe_tag": "drop", "probe_score": 0.0177, "luna_label": 0, "luna_reason": null}]}, {"key": "aj2-104", "text": "**The World Bank**\nEmergency Food Security Project (P178936)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nPage 4 of 54", "source": "jdc_operational", "subset": "annotate_aj_part2", "spans": [{"key": "sample:jdc_operational:000024:8:0:0", "start": 19, "end": 50, "surface": "Emergency Food Security Project", "probe_tag": "drop", "probe_score": 0.0147, "luna_label": 0, "luna_reason": null}]}, {"key": "aj2-105", "text": "**The World Bank**\nUganda: Investment for Industrial Transformation and Employment (P171607)\n\n\n**D. Project Description**\n\n**Component 1: Mitigating the impact of COVID-19.** The objective of this component is to ease liquidity constraints on\nMSMEs, including women led and refugee MSMEs. For the reasons discussed above, the component will seek to prioritize\nthe manufacturing and exporting sectors driving economic transformation, with the vision of connecting lower income\nregions, i.e. RHDs with more viable and sustainable markets. The component will operate three different windows targeting\ndifferent types of firms within the supply chain. All PFIs will be required to provide gender disaggregated data on their\nportfolios in order to address the lack of data on women-led firms as well as data on refugee or host community status to\nensure intersectional issues of exclusion are sufficiently addressed. _Window 1_ will support the extension of the loan period\nfor well performing firms by financing the cost of providing a grace period. _Window 2_ (supporting micro firms) will target\nmicro firms, including in RHDs, to enable them to restart or continue their operations as critical units in funding the link\nsay between producers with aggregators, processors, and distributors. _Window 3_ (receivables financing, including\ngovernment arrears) will provide finance to MSMEs based on security in the form of their receivables.\n\n**Component 2: Creating and Operating New Productive and Transformative Assets.** The component is focused on\nenabling new financing to restart and bolster economic growth. The component provides risk coverage for new lending to\nMSMEs, extends local currency liquidity on a long-term basis to larger investment projects, and de-risks or incentivizes\nprivate investment in RHDs through a competitive grant program. Component 2 seeks to mitigate the financial sector’s risk\naversion and thereby improve the availability of credit to MSMEs, and to provide longer", "source": "jdc_operational", "subset": "annotate_aj_part2", "spans": [{"key": "jdc_operational:000043:5:0:0", "start": 685, "end": 710, "surface": "gender disaggregated data", "probe_tag": "drop", "probe_score": 0.0329, "luna_label": 0, "luna_reason": "PFIs will be required to provide this data; it is future data production."}, {"key": "jdc_operational:000043:5:0:1", "start": 798, "end": 838, "surface": "data on refugee or host community status", "probe_tag": "drop", "probe_score": 0.0213, "luna_label": 0, "luna_reason": "PFIs are required to provide this data; it is planned data production."}]}, {"key": "aj2-106", "text": " training will address<br>the dimensions of :<br>identification of GBV<br>victims, simple counselling<br>and support mechanisms<br>and possible referral<br>pathways for further|6 months<br>|MOPH<br>|Administrative data<br>|PMU/MOPH<br>|\n\n\nPage 44 of 54", "source": "jdc_operational", "subset": "annotate_aj_part2", "spans": [{"key": "sample:jdc_operational:000000:48:1:0", "start": 199, "end": 218, "surface": "Administrative data", "probe_tag": "drop", "probe_score": 0.0001, "luna_label": 0, "luna_reason": null}]}, {"key": "aj2-107", "text": " growth quality, poverty has remained elevated and the job content of**\n**growth has been weak.** Based on available but incomplete data, significant progress was made\nin reducing poverty prior to the civil war. Since that date, however, progress has stopped, and\neven reversed as poverty incidence has hovered around 28 percent for the few data points\navailable. Extreme poverty has remained stable at around 8 percent since the end of the civil war.\nThe country’s employment challenge is also daunting as job growth has not kept pace with the\ngrowth of the labor force. Even during periods of relatively rapid economic growth, Lebanon\nexperienced weak private sector job creation with an employment growth elasticity of only 0.2,\nwhich is considerably lower than those observed in other countries in the region. Meanwhile, the\nlabor force has been growing, in part driven by an increase in the working age population. Under\ncurrent conditions, Lebanon is not making significant progress toward increasing shared\nprosperity or eliminating extreme poverty.\n\n\n**B.** **Situations of Urgent Need of Assistance**\n\n\n4. This project is being prepared and implemented in accordance with the provisions of\nparagraph twelve of World Bank OP10.00, “Projects in situations of urgent need of Assistance or\nCapacity Constraints.” This permits the provision of investment project financing with specific\nexceptions in cases where there is an urgent need of assistance because of a natural or man-made\ndisaster or conflict (among other factors). The situation in Lebanon reflects both the impact of a\nconflict in neighboring Syria and of a man-made disaster, in the form of the continuing influx of\n\n\n1 This and the following paragraphs in the Country Context section draw directly from the concept note of the\nLebanon Systematic Country Diagnostic (2015).\n\n\n1", "source": "jdc_operational", "subset": "annotate_aj_part2", "spans": [{"key": "sample:jdc_operational:000030:9:1:0", "start": 107, "end": 136, "surface": "available but incomplete data", "probe_tag": "drop", "probe_score": 0.0384, "luna_label": 1, "luna_reason": null}]}, {"key": "aj2-108", "text": " It will be especially important to include women in the design and construction\nof WASH facilities, for instance, to ensure these facilities are rehabilitated in ways that promote security\nand effective management on completion. The project will harmonize, to the extent possible, the labor\nprovisions adopted by the World Bank’s SSSNP and coordinate salary levels with UN coordination cluster\nstandards.\n\n\n47 Population figures for urban areas would be calculated based on a headcount or by complementing 2008 census with other\ndata sources (for example, DTM.)\n\n\nJune 22, 2020 Page 12 of 23", "source": "jdc_operational", "subset": "annotate_aj_part2", "spans": [{"key": "sample:jdc_operational:000058:11:1:0", "start": 507, "end": 518, "surface": "2008 census", "probe_tag": "confusion", "probe_score": 0.0823, "luna_label": 1, "luna_reason": null}, {"key": "sample:jdc_operational:000058:11:1:1", "start": 557, "end": 560, "surface": "DTM", "probe_tag": "drop", "probe_score": 0.0, "luna_label": 1, "luna_reason": "DTM data is identified as a source for calculating urban population figures."}]}, {"key": "aj2-109", "text": " centers assessed monthly<br>(using check list) treatment, isolation &<br>quarantine|Number of centers<br>assessed monthly|monthly<br>|<br>COVID-19<br>report<br> <br>|routine data<br>|MOPH<br>|\n|<br>Establishment of monitoring and<br>evaluation system for COVID-19 <br> <br>|Establishment of a COVID-<br>19 M&E system|once<br>|<br>COVID-19<br>report<br>|routine data<br>|MOPH<br>|\n\n\n\nPage 34", "source": "jdc_operational", "subset": "annotate_aj_part2", "spans": [{"key": "sample:jdc_operational:000039:38:1:0", "start": 167, "end": 179, "surface": "routine data", "probe_tag": "drop", "probe_score": 0.0117, "luna_label": 0, "luna_reason": null}]}, {"key": "aj2-110", "text": " the temporary rental of housing by displaced owners is projected\nat US$173.3 million for the same period. <sup>93</sup> [^93: RDNA]\n\n**7.** **Units and buildings remaining in need of repair are mainly those that are severely damaged, requiring**\n**more costly structural works, encompassing historic including heritage-grade buildings.** The wide national and\ninternational immediate response mostly focused on the less damaged units due to the technical complexity of\naddressing severely damaged units. As of 25 February 2021, 5,777 buildings remain with low or cosmetic damage\n(L1 damage level), 1,881 buildings with major but not structural damage (L2 level), and 1,093 with structural\ndamage (L3 level).\n\n**8.** **Most of the impacted residential buildings with cultural heritage value are still unattended and remain**\n**in precarious condition, requiring rehabilitation to allow habitability (see figure 3).** So far early recovery efforts\nhave focused on addressing affected residential buildings that suffered minor damage <sup>94</sup> [^94: Buildings with less than 10 percent of physical damage.] due to a lack of leadership\nfrom the authorities, as well as funds, capacity, and time required to assume the complex rehabilitation works of\nthe most severely damaged buildings during what was considered the “humanitarian phase”. According to the\nUN-Habitat damage inventory for all the buildings within the blast affected area of damaged buildings,\napproximately 25 buildings have not received any type of rehabilitation assistance yet, 20 have been propped but\nnot rehabilitated, 50 buildings are still under rehabilitation, and 80 have been completely rehabilitated. According\nto the DGA, 80 percent of the 640 heritage buildings which were damaged by the blast are of residential use.\nAmong these buildings, UNESCO interventions have focused on securing the most severely damaged buildings\nusing international and DGA standards <sup>95</sup>, with", "source": "jdc_operational", "subset": "annotate_aj_part2", "spans": [{"key": "sample:jdc_operational:000012:57:1:0", "start": 1357, "end": 1384, "surface": "UN-Habitat damage inventory", "probe_tag": "drop", "probe_score": 0.0131, "luna_label": 1, "luna_reason": null}]}, {"key": "aj2-111", "text": " registration procedures, the\nmediation committee will be established, and mediation meetings will be organized with interested\nparties. Minutes of meetings will be recorded. The existence of this first instance mechanism will be\nwidely disseminated to the affected people as part of the consultation undertaken for the sub‐project\nin general. It is important that these mediation committees be set up as soon as RAP preparation\nstarts. Disputes documented for example, through socio‐economic surveys should be dealt with by\nappropriate mediation mechanisms which must be available to cater for claims, disputes and\ngrievances at this early stage. A template form for claims should be developed and these forms be\ncollated on a quarterly basis into a database held at project level.\n\n\n**VIII.** **Verification**\n\n\n11. The Mediation Meeting Minutes, including agreements of compensation and evidence of\ncompensation made shall be provided to the Municipality/district, to the supervising engineers, who\nwill maintain a record hereof, and to auditors and socio‐economic monitors when they undertake\nreviews and post‐project assessment. This process shall be specified in all relevant project documents,\nincluding details of the relevant authority for complaints at the municipal/district or implementing\nagency level.\n\n\nPage 80 of 90", "source": "jdc_operational", "subset": "annotate_aj_part2", "spans": [{"key": "sample:jdc_operational:000008:83:1:0", "start": 478, "end": 500, "surface": "socio‐economic surveys", "probe_tag": "drop", "probe_score": 0.0022, "luna_label": 0, "luna_reason": null}, {"key": "sample:jdc_operational:000008:83:1:1", "start": 751, "end": 781, "surface": "database held at project level", "probe_tag": "drop", "probe_score": 0.0019, "luna_label": 0, "luna_reason": null}]}, {"key": "aj2-112", "text": " provided with a prepaid electronic\nvoucher (e-card) to meet their monthly food needs. <sup>37</sup> Each month WFP delivers vouchers worth\nUS$30 to every Syrian refugee in Lebanon who qualifies for food assistance. Beneficiaries are\nnot obliged to spend the full amount at once, which means they can use it whenever they need, as\nlong as they spend the amount within the month. These vouchers can be exchanged for food\nitems of their choice in any of approximately 285 WFP contracted shops throughout Lebanon.\nVouchers were adopted as the primary modality of assistance in Lebanon as the local market is\nmore than capable of providing sufficient food for the host and refugee populations alike. Thus\nthere is no need to import large quantities of food. Instead, the vouchers, and now the e-cards,\nprovide vulnerable Syrian refugees with the means to access the Lebanese market themselves.\n\n10. In early 2013, WFP began working to shift modality from the paper voucher system to a\nnew, electronic, pre-paid voucher system. Following several months of planning and research,\nWFP signed a partnership agreement in September 2013 with MasterCard and a local bank. The\nfirst 1,908 credit card-style e-cards (for 10,306 beneficiaries) were distributed in a successful\npilot scheme in South Lebanon. In October 2013, a general roll out followed for the entire\ncaseload in Beirut, Mt Lebanon and the South, some 140,000 beneficiaries.\n\n\n36 In cases where a new applicant is ranked as one of the poorest 50,000 beneficiaries using the NPTP database, she/he will\nreceive all NPTP benefits including the e-card food voucher.\n37 Eligible families are registered by UNHCR and based on a vulnerability criteria agreed by WFP and UNHCR.\n\n\n27", "source": "jdc_operational", "subset": "annotate_aj_part2", "spans": [{"key": "sample:jdc_operational:000047:37:1:0", "start": 1527, "end": 1540, "surface": "NPTP database", "probe_tag": "drop", "probe_score": 0.0035, "luna_label": 1, "luna_reason": null}]}, {"key": "aj2-113", "text": "**The World Bank**\nEmergency Food Security Project (P178936)\n\n\n|Indicator Name|PBC|Baseline|End Target|\n|---|---|---|---|\n|Monitoring tool for access to animal feed developed and<br>accessible to the public (Yes/No)||No|Yes|\n|External users of monitoring tool for access to bread satisfied<br>with information provided (Percentage)||0.00|90.00|\n|External users of monitoring tool for access to animal feed<br>satisfied with information provided (Percentage)<br>||0.00|90.00|\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Monitoring & Evaluation Plan: PDO Indicators|Col2|Col3|Col4|Col5|Col6|\n|---|---|---|---|---|---|\n|**Indicator Name **|**Definition/Description **|**Frequency **|**Datasource **|**Methodology for Data**<br>**Collection **|**Responsibility for Data**<br>**Collection **|\n|Cumulative amount of wheat procured<br>through the project|Cumulative amount of<br>wheat imports procured<br>with project financing since<br>the start of the project and<br>delivered to the port of<br>Aqaba|Monthly and<br>at the end of<br>the project<br>implementati<br>on period.<br>|MOITS<br>|Data collected regularly<br>and reported by the<br>MOITS<br>|Project Coordination<br>Team<br>|\n|Cumulative amount of barley procured", "source": "jdc_operational", "subset": "annotate_aj_part2", "spans": [{"key": "sample:jdc_operational:000024:42:0:0", "start": 1054, "end": 1078, "surface": "Data collected regularly", "probe_tag": "drop", "probe_score": 0.0148, "luna_label": 0, "luna_reason": "Standalone table cell describing collection methodology, not an independent data-use mention."}]}, {"key": "aj2-114", "text": "**The World Bank**\nSouth Sudan Emergency Food and Nutrition Security Project (P163559)\n\n\ndifficult for Bank staff and other independent agencies to access the project sites and confirm that project\nresources have been utilized efficiently and economically towards the development objective.\n\n\n23. Other risks relate to the rapidly deteriorating macroeconomic situation in South Sudan coupled with\nthe significant depreciation of the local currency relative to the US$, which could further present a risk of\nmisapplication of project resources. These risks are effectively mitigated by the involvement of UN\nagencies in the implementation of the project. The UN agencies have adequate technical and fiduciary\ncapacity to implement similar types of emergency operations. The three UN agencies will each sign\ncontracts with MAFS as a basis for their engagement. During the course of implementation, the agencies\nwill submit quarterly utilization (progress and financial) reports, which will be validated by the PIU in line\nwith the existing contracts, before sharing with the Bank. Further, the UN has got adequate machinery to\naccess insecure locations and project sites.\n\n\n24. Funds disbursed into the DA for the implementation of component 3 will be ring‐fenced from\nministry‐wide fiduciary risks by ensuring segregated project accounts (DA), cashbooks and financial\nstatements, operated, maintained and prepared by the MAFS ‐ based PIU. The PIU will maintain an up‐to‐\ndate contract register as well as an assets register. Similarly, the FM team will prepare monthly bank\nreconciliation statements to ascertain the accuracy of the cash balances in the DA. Fiduciary oversight will\nbe effected by the IAD, the NAC, and other private audit firms working with the two Government\ninstitutions. The in‐year internal audit reviews will be conducted at least once a year and the audit reports\nwill be shared with MAFS, MoFP and the Bank for review and comments.\n\n\n**Funds flow and Disbursement arrangements**\n\n\n25. Disbursement of the Grant will use advances, reimbursement", "source": "jdc_operational", "subset": "annotate_aj_part2", "spans": [{"key": "sample:jdc_operational:000038:51:0:0", "start": 1475, "end": 1492, "surface": "contract register", "probe_tag": "drop", "probe_score": 0.0035, "luna_label": 0, "luna_reason": null}, {"key": "sample:jdc_operational:000038:51:0:1", "start": 1507, "end": 1522, "surface": "assets register", "probe_tag": "drop", "probe_score": 0.0095, "luna_label": 0, "luna_reason": null}]}, {"key": "aj2-115", "text": "400|18,894|4.8|\n|Killa Saifullah|342,814|18,842|5.5|\n|Killa Abdullah|757,578|10,775|1.4|\n\n\n_Source_ : Population data from Census 2017; Registered refugee data from UNHCR as of December 31, 2019.\n_Note_ : The table includes data for districts with more than 10,000 registered refugees.\n\n\n\n\n\n**B. Sectoral and Institutional Context**\n\n\n9. **Pakistan has invested significantly in designing refugee protection framework and**\n**administrative practices that are consistent with international standards and norms.** Pakistan’s\nProtection Framework for Afghan Refugees has developed over time. It includes: (a) implementing\nadministrative and legal measures for refugees, such as the exemption from applicability of the 1946\nForeigners’ Act; (b) authorizing Afghan refugees to work in the country; (c) issuing and renewing PoR cards\nwith the support of the UNHCR; (d) signing of the regional Solutions Strategy for Afghan Refugees (SSAR)\nin 2012, with Iran and Afghanistan, under UNHCR facilitation; and (e) approving the Repatriation and\nManagement Policy for Afghan Refugees (RMP) in 2017. This Protection Framework has been found to\nbe adequate by the UNHCR and the World Bank.\n\n\n10. **Pakistan’s refugee management approach draws from the principles of the SSAR.** It has three\npillars: (a) support voluntary repatriation, (b) promote sustainable reintegration in Afghanistan, and (c)\nprovide continued assistance to host communities. The SSAR has five outcomes: (a) support to voluntary\nrepatriation, (b) access to shelter and essential social services for refugees, returnees, and host\ncommunities, (c) improved and diversified livelihood opportunities through training and enhanced food\nsecurity, (d) social and environmental protection of refugees and returnees, as well as", "source": "refugee_pads", "subset": "annotate_aj_part2", "spans": [{"key": "refugee_pads:000085:11:1:1", "start": 136, "end": 170, "surface": "Registered refugee data from UNHCR", "probe_tag": "keep", "probe_score": 0.9312, "luna_label": 1, "luna_reason": "UNHCR refugee data is cited as the source for the presented district table."}]}, {"key": "aj2-116", "text": " need for increased efficiency in the use of water resources especially in these regions.\n\n14. **While piped water coverage is relatively high in Turkey, more than 40 percent of water is distributed untreated,**\n**which increases risks linked to poor water quality, including to public health.** According to Municipal Water\nStatistics prepared by TURKSTAT in 2018, 99 percent of the population living in municipalities has access to piped\nwater supply, however only 60 percent are served by a water treatment plant. The municipalities targeted in this\nproject face significant water supply service challenges, including poor quality water due to inadequate water\ntreatment facilities. Thus, based on the SDG definition of a safely managed drinking water service as one located on\npremises, available when needed and free from contamination, the municipalities are out of compliance with these\nservice requirements, putting Turkey at risk of not fulfilling the SDG goal if not addressed. Service efficiency is also\nan issue, with utilities having high Non-Revenue Water (NRW), in some cases with over 50 percent losses, due to\nageing or sub-optimally maintained transmission and distribution infrastructure. NRW in utilities averages about 36\npercent country-wide.\n\n15. **Similarly, while access to sewage networks is relatively high, a significant proportion of wastewater is discharged**\n**untreated into the environment.** According to TURKSTAT Municipal Wastewater Statistics for 2016, 90 percent of\nthe population living in municipalities are served with a sewage network. However, only 70 percent of the population\nis served with a wastewater treatment plant. In individual municipalities coverage is lower, and the quality of\nsewerage infrastructure is inadequate, resulting in sewage leakages. These conditions not only impact the\nenvironment, but also lead to significant increases in operation and maintenance costs of the systems. With higher\npopulations, impacts on the environment are increased. The current situation in the areas with no wastewater\ntreatment puts the affected municipalities out of compliance with the", "source": "refugee_pads", "subset": "annotate_aj_part2", "spans": [{"key": "refugee_pads:000125:14:1:0", "start": 309, "end": 335, "surface": "Municipal Water\nStatistics", "probe_tag": "keep", "probe_score": 0.9396, "luna_label": 1, "luna_reason": "TURKSTAT statistics support municipal piped-water access and treatment findings."}]}, {"key": "aj2-117", "text": ".7 15.7 15.3 14.9\nServices\n\nHousehold final consumption expenditure 79.5 73.2\nGeneral gov’t final consumption expenditure 10.2 11.5\nImports of goods and services 38.4 46.0 45.5 45.6\n\n\n**199545** growth **of exports** and imports (%)\n(average annual growth)\nAgriculture 1.8 1.2 0 . 7 2.5 2o\nIndustry 6.2 4.2 5.2 6.0 i Manufacturing 7.6 4.3 5.1 6.0\nServices 4.7 5.3 7.6 5.1\n\nHousehold final consumption expenditure 4.0 -10\nGeneral gov’t final consumption expenditure 3.7 .. **-20**\nGross capital formation 2.5 5.3 11.6 12.0 -Exports +Imports\nImports of goods and services 5.6 7.3 9.3 8.7\n\n\nNote: 2005 data are preliminary estimates.\nThis table was produced from the Development Economics LDB database.\n\n- The diamonds show four key indicators in the countly (in bold) compared with its income-group average. If data are missing, the diamond will\nbe incomplete.\n\n\n72", "source": "refugee_pads", "subset": "annotate_aj_part2", "spans": [{"key": "sample:refugee_pads:000023:77:2:0", "start": 594, "end": 603, "surface": "2005 data", "probe_tag": "keep", "probe_score": 0.9905, "luna_label": 0, "luna_reason": null}, {"key": "sample:refugee_pads:000023:77:2:1", "start": 664, "end": 698, "surface": "Development Economics LDB database", "probe_tag": "keep", "probe_score": 0.999, "luna_label": 1, "luna_reason": null}]}, {"key": "aj2-118", "text": "**Annex 1: Background and Program Design Framework**\n\n**SRI** **LANKA: NORTH EAST HOUSING RECONSTRUCTION PROGRAM**\n\n\n**Background Conditions and Issues**\n\n\n_Housing Conditions in the North East:_ The Assessment o f Needs in the Conflict-Affected Area (May,\n\n2003) estimated that 326,000 housing units were either fully damaged or partly damaged in the North\nEast.\n\n\nHousing Needs o f IDPs: Based on the needs assessment and other sources (including **_MRRR,._** NEPC,\nUNHCR, validation through community consultation and secondary data analyses) it i s estimated that\napproximately 130,401 o f these units (or about 40% o f all damaged houses) are owned by IDPs. 144,890\nor 84% o f all IDP-owned homes are in the North East and _90%_ - f these are estimated as damaged or\ndestroyed. Nearly 45% o f IDPs to be resettled are from Jafha. A large percentage o f IDPs originating\nErom the East have returned. The housing needs - f vulnerable families such as the landless, families\nwhose houses are located in high security zones, single-headed families, and elderly living in welfare\ncenters are estimated at 18,500 units. Due to the higher population growth rate o f families in welfare\ncenters, the actual number o f people living in these centers i s greater than the registered number, resulting\nin additional housing needs. Besides, nearly 12,000 to 15,000 damaged units belong to refugees living in\nwelfare camps and these families are returning to their homes on a regular basis.\n\n\nHousing Needs o f non-IDPs: It i s estimated that nearly 196,300 damaged units belong to non-displaced\nfamilies, constituting 57% o f the total damaged units in the North East. Nearly 45% o f non", "source": "refugee_pads", "subset": "annotate_aj_part2", "spans": [{"key": "refugee_pads:000115:21:0:0", "start": 200, "end": 250, "surface": "Assessment o f Needs in the Conflict-Affected Area", "probe_tag": "keep", "probe_score": 0.9027, "luna_label": 1, "luna_reason": "Named 2003 assessment provides the estimated number of damaged housing units."}]}, {"key": "aj2-119", "text": "**The World Bank**\nGreater Beirut Public Transport Project (P160224)\n\n\n**<mark>I.</mark>** **<mark>STRATEGIC CONTEXT</mark>**\n\n\n**A. Country Context**\n\n\n1. **Lebanon is a middle-income country with a population of 4.5 million people in 2015, not taking**\n**into account the approximate 1.5 million Syrian refugees and 450,000 Palestinian refugees residing in**\n**the country.** Real gross domestic product (GDP) growth for 2016 was estimated at 1.8 percent, reflecting\nthe impact of regional turmoil and the absence of reforms **.** The services sector—historically a key growth\ndriver <sup>1</sup> [^1: Between 1997 and 2011—latest utilized final national accounts—the services sector accounted for an average of 74 percent of\nreal GDP.] —has been severely affected by the Syria conflict and has contributed significantly to Lebanon’s\nlow growth in recent years. Tumbling growth since 2011 and the large fiscal burden associated with Syrian\nrefugees’ access to public services and infrastructure have pushed the debt-to-GDP ratio higher again\n(around 140 percent as of end-2015), resulting in a marked deterioration of the country’s macroeconomic\nenvironment. Meanwhile, the growth outlook remains subdued given the ongoing conflict in Syria and\nother regional tensions and economic slowdown. The World Bank projects real growth between 2 percent\nand 2.5 percent yearly over the medium term.\n\n\n2. **Lebanon’s poor infrastructure represents a key constraint to growth.** Despite being an uppermiddle-income country, Lebanon’s infrastructure is in a poor condition. According to the World Economic\nForum’s Competitiveness Index, <sup>2</sup> [^2: World Economic Forum. Global Competitiveness Index 2014/2015.] Lebanon’s infrastructure is the second main constraint to growth and its\nsupply and quality is materially", "source": "refugee_pads", "subset": "annotate_aj_part2", "spans": [{"key": "sample:refugee_pads:000074:12:0:0", "start": 642, "end": 665, "surface": "final national accounts", "probe_tag": "keep", "probe_score": 0.9975, "luna_label": 1, "luna_reason": null}]}, {"key": "aj2-120", "text": "lines in the first years of primary school. <sup>13</sup> [^13: According to MOE data for the 2015‐2016 academic year, enrollment is similar for girls and boys.] Limited specialized in‐service training opportunities and\npedagogical support constrain KG teachers’ ability to structure learning around age‐appropriate and\nplay‐based activities that stimulate child development and early noncognitive skills. This, coupled with\na lack of an efficient quality assurance system for KGs means that there is no mechanism to monitor\nprogress or incentivize continuous quality improvements, and likely is restricting the ECE’s\ncontribution to children’s school readiness in the country. The 2014 Early Development Instrument,\nfor example, revealed that a quarter of children enrolled in public KG2 in Jordan are “not ready to\nlearn”, mainly due to inadequate levels of socioemotional development. As such, expanding access\nand ensuring quality in the provision of KG are likely to transform Jordanian and non‐Jordanian\nstudents’ ability to learn and succeed in school.\n\n12. **Poor student learning outcomes at all levels are a challenge in Jordan.** One in five students in\ngrade 2 cannot read a single word from a reading passage, while nearly half are unable to perform a\nsingle subtraction task correctly, thus lacking the foundational literacy and numeracy skills that enable\nfurther cognitive skill development. <sup>14</sup> [^14: Latest (2012) EGRA and EGMA scores for Jordan.] With a weak start, skills deficits compound such that by age 15,\ntwo‐thirds of students do not meet the most basic level of proficiency in mathematics, and half are\nbelow basic proficiency in reading and science, as measured by the 2015 Program for International\nStudent Assessment (PISA). Furthermore, learning outcome data show a reverse gender gap with girls\nperforming better than boys in reading, mathematics, and science. <sup>15</sup> [^15: PISA 2015] International comparisons place\nJordan in", "source": "refugee_pads", "subset": "annotate_aj_part2", "spans": [{"key": "sample:refugee_pads:000127:11:0:0", "start": 77, "end": 85, "surface": "MOE data", "probe_tag": "keep", "probe_score": 0.9723, "luna_label": 1, "luna_reason": "MOE data supports the enrollment comparison for girls and boys."}, {"key": "sample:refugee_pads:000127:11:0:1", "start": 1708, "end": 1757, "surface": "2015 Program for International\nStudent Assessment", "probe_tag": "keep", "probe_score": 0.9959, "luna_label": 1, "luna_reason": null}, {"key": "sample:refugee_pads:000127:11:0:2", "start": 1779, "end": 1800, "surface": "learning outcome data", "probe_tag": "keep", "probe_score": 0.9547, "luna_label": 1, "luna_reason": "Existing learning outcome data supports the reported gender-gap finding."}]}, {"key": "aj2-121", "text": "**The World Bank**\nMunicipal Services Improvement Project in Refugee Affected Areas (P169996)\n\n\nwill normally be undertaken annually during the World Bank’s supervision mission, or the World Bank may request\nto review any particular contract at any time. In such cases, the PMUs shall provide the World Bank the relevant\ndocumentation for its review.\n\n\n19. **Complaint review.** The procurement complaints other than covered under Annex III of the Procurement Regulations\nare to be handled by the ILBANK in accordance with the procedures agreed by the Bank and stipulated in the POM.\nImmediately upon received, the complaints will be recorded in the STEP complaint module by PMU. ILBANK will not\nproceed with the next stage/phase of the procurement process, including with awarding a contract without\nsatisfactory resolution of the complaint(s).\n\n\n20. **Operational costs** will not be considered under procurement implementation which could be the incremental\nexpenses, including office supplies, vehicles operation and maintenance cost, maintenance of equipment,\ncommunication costs, rental expenses, utilities expenses, consumables, transport and accommodation, per diem,\ncost for procurement advertisements, and salaries of locally contracted support staff.\n\n\nPage 87 of 94", "source": "refugee_pads", "subset": "annotate_aj_part2", "spans": [{"key": "refugee_pads:000125:91:0:0", "start": 650, "end": 671, "surface": "STEP complaint module", "probe_tag": "confusion", "probe_score": 0.2486, "luna_label": 0, "luna_reason": "Names a complaint-recording system without showing its data informing analysis or decisions."}]}, {"key": "aj2-122", "text": "The World Bank\nMauritania Water and Sanitation Sectoral Project (P167328)\n\n\n**Table 4.2: Project Economic Benefits**\n\n\n\n\n\n\n\n|Activities|Incremental Benefits|\n|---|---|\n|**Development of access**|**Development of access**|\n|Mini and regular water systems|-Incremental water revenues from new stand posts and<br>connections, including resale to neighbors.<br>-Consumer surplus accruing to beneficiaries<br>-Value of time saved.<br>-Jobs created and additional income generated.|\n|**Systems rehabilitation and expansion**|**Systems rehabilitation and expansion**|\n|Rehabilitation and expansion of<br>ONSER and SNDE systems and in<br>Camp M’Bera|-Increased water consumption and increased water revenues<br>from existing users.<br>-Reduction of energy consumption (thermal pumping) by<br>switching to solar.<br>-Reduced technical and commercial losses (non-revenue<br>water).<br>-Jobs created and additional income generated.|\n|**Sanitation**||\n|Construction of household latrines<br>and rainwater drainage canals|-Direct health benefits (lower incidents of diarrhea and other<br>water borne diseases).<br>-Health care cost savings.<br>-Increase in female student attendance at school.<br>-Decreased flood damage.<br>-Incremental revenues from fecal sludge removal.<br>-Jobs created and additional income generated.|\n\n\n6. **Incremental Revenues** . The incremental consumption, water prices and revenues are estimated\nbased on: (i) results of household surveys; and (ii) water rates for domestic customers and stand post\nvendors from the recently approved tariff", "source": "refugee_pads", "subset": "annotate_aj_part2", "spans": [{"key": "refugee_pads:000106:59:0:0", "start": 1439, "end": 1456, "surface": "household surveys", "probe_tag": "confusion", "probe_score": 0.5477, "luna_label": 1, "luna_reason": "Survey results are used to estimate incremental consumption, prices, and revenues."}]}, {"key": "aj2-123", "text": " of Expenditures (SOE) and the Special\nAccount (SA), would be audited quarterly internally and annually by an independent auditor, in\naccordance with internationally accepted standards. In addition, the auditor would carry out field spot\ncheck audits to ascertain compliance with contractual requirements. Compliance with conditional cash\ntransfers would be monitored by an independent external consultant (paragraph _C.3)._\n\n\n**4.** **Social**\n\nOpportunities, constraints, impacts, and risks arising. out of the socio-cultural and political context.\n\nThe impact of closure and incursions in the West Bank and Gaza has been extensively documented. On\nthe rise are poverty, unemployment, school drop out rates; on the decline or deteriorating are household\nincomes, living conditions, school attendance rates, at-large nutritional status and in particular of children\n0-5 years of age.13\n\nThe so called “newly poor”, those who are just above the poverty line before the outbreak of the second\nIntifada, in the third quarter of 2000, have been assisted by various interventions. To date, it has been\nmuch more difficult to find ways to assist the very poor, or first decile, whose coping mechanisms are\nessentially exhausted. The proposed project i s designed to support children (0-18 years old) in the first\ndecile. Although the SHC has targeted the first decile for more than 20 years, the program i s very small\ntoday in relation to need and requires new instruments to address the present situation and to shift\nMOSA’s overall strategy from one of coping to one of social springboard. Therefore, the project will\nsupport MOSA in reshaping its social assistance strategy and to improve effectiveness and efficiency of\n\n\n~\n\n**l3** PCBS quarterly household surveys, Palestinian Living Conditions quarterly surveys, IUCN, University of Geneva, Living\n\nStandards quarterly surveys, Nutrition Study, Johns Hopkins University, _2002,_ Nutrition Survey, PCBS and", "source": "refugee_pads", "subset": "annotate_aj_part2", "spans": [{"key": "refugee_pads:000047:20:1:0", "start": 1732, "end": 1764, "surface": "PCBS quarterly household surveys", "probe_tag": "confusion", "probe_score": 0.7827, "luna_label": 1, "luna_reason": "Named household surveys cited as evidence for documented social conditions"}, {"key": "refugee_pads:000047:20:1:1", "start": 1766, "end": 1813, "surface": "Palestinian Living Conditions quarterly surveys", "probe_tag": "keep", "probe_score": 0.9613, "luna_label": 1, "luna_reason": "Named existing survey cited among sources documenting social conditions."}, {"key": "refugee_pads:000047:20:1:2", "start": 1843, "end": 1878, "surface": "Living\n\nStandards quarterly surveys", "probe_tag": "confusion", "probe_score": 0.7496, "luna_label": 1, "luna_reason": "Existing survey source listed among evidence documenting social conditions."}]}, {"key": "aj2-124", "text": "decentralized \"partnership\" approach to governance that involves line ministnes, NGOs, CBOs, <sup>and</sup> <sup>civil</sup>\nsociety. NCRRR/NaCSA has been supported by the African Development Bank, UNDP, DflD, and IDA.\nIt has provided assistance for more than 500,000 displaced persons, shelter rehabilitation, vocational\ntraining, trauma healing, and micro-finance programs. It has financed 275 community-based sub-projects\nin the areas of health, education, water and sanitation, agriculture and capacity building. These <sup>tasks</sup>\nhave been carried out with considerable support from the 260 NGOs registered in Sierra Leone, of which\n68 are international. These NGOs have been instrumental in ensuring service delivery to remote <sup>areas</sup>\nwhere public services were absent.\n\n\n**3.** **Sector** **issues** **to be** **addressed** **by the** **project and strategic choices:**\n\n**Poverty in a Post-Conflict** **Environment.** Section 2 above outlines the principal characteristics\nof poverty in Sierra Leone and the condition of the country at the close of the civil war. <sup>Access</sup> <sup>of the</sup>\npoor majority to food, shelter, employment opportunities and social services are among the <sup>principal</sup>\n\n\n\nconstraints to post-conflict reconstruction, economic recovery and poverty reduction. District recovery\nassessments reveal that over 340,000 houses were destroyed dunng the war and only 10,000 have been\nrebuilt so far. Government is particularly concerned with the shelter needs of returnees, IDPs <sup>and</sup>\n\n\n\ngovernment employees such as health workers and", "source": "refugee_pads", "subset": "annotate_aj_part2", "spans": [{"key": "refugee_pads:000104:9:0:0", "start": 1323, "end": 1352, "surface": "District recovery\nassessments", "probe_tag": "confusion", "probe_score": 0.2697, "luna_label": 1, "luna_reason": "Assessments provide the attributed finding on destroyed and rebuilt houses."}]}, {"key": "aj2-125", "text": "; sulfate (SO42); and total dissolved solids (TDS). The LRA then uses a simple Water Quality\nIndex (WQI), which presents the advantage of communicating water quality information in an\nunderstandable way for all stakeholders. The WQI summarizes a large amount of water quality data in\nscores reported as a total number between 1 and 100, with (a) 90–100 as excellent, (b) 75–90 as good,\n(c) 60–75 as fair, (d) 40–60 as marginal, and (e) 0–40 as poor. Under this component, the number of\nlocations will be increased to 20 and support will be mainly in the form of water quality measurement\nequipment, which could also expand the water quality indicator measured (such as BOD <sup>52</sup> ).\n\n\n116. **Improving water resources modeling** . Over time, the LRA will need to develop a systemwide modeling of the upper-catchment (hydrology, water quality, and so on), which will support\nmonitoring progress during the implementation of the MoE’s Business Plan for Combating Pollution\nin Qaraoun Lake. The LRA has already existing surface and groundwater flow models (such as HECRAS and Modflow) and these will be a good basis to expand to the wider upper catchment modeling.\nUnder this component, a water expert will be hired to support in assessing existing models, current,\nand projected water balance and integrate as possible current models to a wider upper catchment\nmodeling. The TOR of the water expert was discussed and is in advanced stage of preparation.\n\n\n117. **Raise awareness** . The LRA will continue to raise awareness about the need to clean up the\nLitani River by undertaking awareness and clean-up campaigns. It is important to involve all\nstakeholders in order to change the behavior of water users. The impact of awareness should be to the", "source": "refugee_pads", "subset": "annotate_aj_part2", "spans": [{"key": "refugee_pads:000036:39:1:0", "start": 262, "end": 280, "surface": "water quality data", "probe_tag": "confusion", "probe_score": 0.326, "luna_label": 1, "luna_reason": "Existing water quality data are summarized into WQI scores and categories."}]}, {"key": "aj2-126", "text": " out of 10 firms in Costa Rica report difficulties filling vacancies. <sup>11</sup> [^11: Encuesta de expectativas de empleo, Q1 2024, ManpowerGroup: https://go.manpowergroupcca.com/meos-cr.] Despite\nan increasing demand for specialist technicians, only 25 percent of the short cycle tertiary Technical and Vocational\nEducation and Training (TVET) course graduates from the National Vocational Training Agency ( _Instituto Nacional de_\n_Aprendizaje,_ INA), and 44 percent from the TVET programs delivered under the aegis of the Ministry of Public Education\n( _Ministerio de Educación Pública,_ MEP) are hired in their field of study, pointing to skills mismatches. <sup>12</sup> [^12: OECD Economic Surveys - Costa Rica, February 2023.] Only 22 percent of\nstudents from lower secondary to short-cycle tertiary enroll in vocational education and training, compared to 32 percent\n\n\n9 <u>[https://thedocs.worldbank.org/en/doc/64e578cbeaa522631f08f0cafba8960e-0140062023/related/HCI-AM23-CRI.pdf](https://thedocs.worldbank.org/en/doc/64e578cbeaa522631f08f0cafba8960e-0140062023/related/HCI-AM23-CRI.pdf)</u>\n10 OECD Education at A Glance, 2023, Table A4.2. The correlation (not causation) between socio-economic conditions, academic achievement and\nlabor market outcomes is a global phenomenon. For the OECD countries as a whole in 2018, the percentage of below Level 2 performers from the\ntop quintile of the PISA index for economic, social and cultural status, was 8%; while for the bottom quintile, the figure was 49%. For the labor market\nfigures quoted in the text, 30% of 25-64 year olds for the OECD countries correspond to the 32% mentioned in the text for Costa", "source": "refugee_pads", "subset": "annotate_aj_part2", "spans": [{"key": "refugee_pads:000189:11:2:0", "start": 90, "end": 124, "surface": "Encuesta de expectativas de empleo", "probe_tag": "confusion", "probe_score": 0.7908, "luna_label": 1, "luna_reason": "Named employment expectations survey cited as evidence for reported vacancy-filling difficulties."}, {"key": "refugee_pads:000189:11:2:2", "start": 1406, "end": 1416, "surface": "PISA index", "probe_tag": "confusion", "probe_score": 0.4274, "luna_label": 1, "luna_reason": "PISA index data supports comparison of below-Level-2 performance by socioeconomic quintile."}]}, {"key": "aj2-127", "text": "**The World Bank**\nSocio-economic Inclusion of Refugees & Host Communities in Rwanda Project (P164130)\n\n\n73. **The project will, to the extent possible, utilize existing government systems and procedures** . Districts implement\nM&E activities under the coordination of LODA and use the LODA-administered Monitoring, Evaluation, and\nInformation System (MEIS). The MEIS facilitates coordination of social protection planning, household profiling and\nM&E of projects from grassroots to central level. The system can generate reports with values on key figures and the\nprogress of indicators. While the MEIS is operational and implemented nationally as the central MIS, the level of\nsystem utilization varies from district to district due to different levels of technical capacity. The SEIRHCP will build\ndistrict capacity to use the MEIS. The MINEMA SPIU will receive required project data and information from the\ndistricts and consolidate it in the P-MIS.\n\n\n74. **Project M&E arrangements** **_._** The MINEMA SPIU will have a dedicated M&E team, which will include (i) a Kigalibased National Project M&E Specialist, who will oversee overall M&E implementation; and (ii) District field specialists\n(embedded in district offices, financed by the project) to monitor all project activities in the target districts. The District\nfield specialists will support the districts to meet the project M&E requirements and ensure data accuracy and\nreporting quality. They will also ensure district-level M&E activities are implemented as per the agreed timelines and\nprocedures. Progress on all project components will be reported in a consolidated quarterly report to the World Bank.\nAnnual Reports will also be prepared and submitted to the World Bank.\n\n75. BRD will collect and analyze data on component two activities. This includes data collection from participating\nentities (SACCOs, MFIs, MSMEs, cooperatives, etc.", "source": "refugee_pads", "subset": "annotate_aj_part2", "spans": [{"key": "refugee_pads:000030:29:0:0", "start": 1825, "end": 1868, "surface": "data collection from participating\nentities", "probe_tag": "confusion", "probe_score": 0.1217, "luna_label": 0, "luna_reason": "Project will collect and analyze data from participating entities."}]}, {"key": "aj2-128", "text": " survey poverty criteria at different levels will provide the basis for estimating\nthe extent of any inclusion and exclusion errors (ECOSIT 2011 is the most recent national\nhousehold survey, but a new one is expected to be conducted in 2016).\n\n\n40. **M&E capacity building.** An important objective of the project is to strengthen the\nnational M&E capacity for SSNs and other social programs and develop harmonized tools for\nidentifying and registering beneficiaries of SSNs covered by different programs. The project will\nprovide significant support and TA to the Government to develop a robust MIS and to reinforce\nthe capacity of the CFS in the management of such system even after the Project closure. In\naddition, under Component 2, the project, by developing harmonized data collection procedures\nand targeting instruments, will support the government in developing a social registry, which\nwould provide a platform for effective monitoring of beneficiaries; effectiveness of safety net\ninterventions, and serve as a repository of data to support program evaluations and other\nassessments as a single beneficiary registry.\n\n\n**_Role of Partners_**\n\n\n41. **The ASP MDTF is co-financing the project.** The ASP MDTF is a U.K. Department for\nInternational Development-World Bank initiative and financing platform that is supporting a\nbroader Sahel Adaptive Social Protection Program (ASPP), whose objectives are to increase\naccess to effective adaptive social protection systems for poor and vulnerable populations in the\nSahel (Burkina Faso, Chad, Mali, Mauritania, Niger and Senegal). The ASPP contributes to\nbuilding long-term resilience and to the World Bank’s global strategy of reducing absolute\npoverty and promoting shared prosperity by supporting the development of sustainable systems\n\n\n48", "source": "refugee_pads", "subset": "annotate_aj_part2", "spans": [{"key": "refugee_pads:000028:59:1:0", "start": 874, "end": 889, "surface": "social registry", "probe_tag": "confusion", "probe_score": 0.3969, "luna_label": 0, "luna_reason": "Planned registry development; future platform use is proposed, not existing data use."}]}, {"key": "aj2-129", "text": ".\n\n\n33. The criteria to select the twelve provinces, and locations within the provinces, included a\ndetailed analysis of concentration of SuTP at the district level, their access to education, and population\ndensities of SuTP compared to host communities. Based on these criteria, the selected locations\nrepresent the following conditions:\n\na. Districts which host more than 50,000 SuTP and with a resident population over 500,000 (where\nthe ratio of SuTP versus host community creates considerable distress for existing infrastructure\nand service capacity)\nb. Districts where the majority of school-aged SuTP reside and which currently host the highest\nconcentration (ratio) of out-of-school SuTP due to very limited (deprived) access to education\nservices,\nc. Districts where a planned change from double-shifts to single-shifts and abolishment of\nTemporary Education Centers are imminent,\nd. Districts where the appropriate public land is available and secured for construction.\n\n34. The Bank team jointly with MoNE used various sources of available data to ensure all\ndimensions of the aforementioned criteria were addressed in the selection. Apart from administrative\ndata from MoNE and DGMM, the team also used the National Muhtar Survey (NMS). The NMS was\nconducted in every neighborhood and village throughout Turkey, jointly by the World Bank and the\nGovernment, to ascertain the accessibility criteria. The survey relies on the information provided by\nmuhtars, who are the elected heads for neighborhoods and villages. They report on population related\n\n\nPage 16 of 86", "source": "refugee_pads", "subset": "annotate_aj_part2", "spans": [{"key": "refugee_pads:000160:17:1:0", "start": 1158, "end": 1196, "surface": "administrative\ndata from MoNE and DGMM", "probe_tag": "keep", "probe_score": 0.9645, "luna_label": 1, "luna_reason": "Existing MoNE and DGMM administrative data informed location selection criteria."}, {"key": "refugee_pads:000160:17:1:1", "start": 1221, "end": 1243, "surface": "National Muhtar Survey", "probe_tag": "confusion", "probe_score": 0.8307, "luna_label": 1, "luna_reason": "Named survey used to assess accessibility criteria for selecting locations."}]}, {"key": "aj2-130", "text": "**PAD DATA SHEET**\n\n_Lebanon_\n\n_Lake Qaraoun Pollution Prevention Project (P147854)_\n\n**PROJECT APPRAISAL DOCUMENT**\n\n\n_MIDDLE EAST AND NORTH AFRICA_\n\n_GENDR_\n\nReport No.: PAD860\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Col1|Col2|Col3|Col4|Col5|Col6|Col7|\n|---|---|---|---|---|---|---|\n|**Basic Information**|**Basic Information**|**Basic Information**|**Basic Information**|**Basic Information**|**Basic Information**|**Basic Information**|\n|Project ID|Project ID|Project ID|EA Category|EA Category|Team Leader(s)|Team Leader(s)|\n|P147854|P147854|P147854|B - Partial Assessment|B - Partial Assessment|Maria Sarraf|Maria Sarraf|\n|Lending Instrument|Lending Instrument|Lending Instrument|Fragile and/or Capacity Constraints [  ]|Fragile and/or Capacity Constraints [  ]|Fragile and/or Capacity Constraints [  ]|Fragile and/or Capacity Constraints [  ]|\n|Investment Project Financing|Investment Project Financing|Investment Project Financing|Financial Intermediaries [  ]|Financial Intermediaries [  ]|Financial Intermediaries [  ]|Financial Intermediaries [  ]|\n||||Series of Projects [  ]|Series of Projects [  ]|Series of Projects [  ]|Series of Projects [  ]|\n|Project Implementation Start<br>Date|Project Implementation Start<br>Date|Project Implementation Start<br>Date|Project Implementation End Date|Project Implementation End Date|Project Implementation End Date|Project Implementation End Date|\n|14-", "source": "refugee_pads", "subset": "annotate_aj_part2", "spans": [{"key": "sample:refugee_pads:000036:4:0:0", "start": 2, "end": 16, "surface": "PAD DATA SHEET", "probe_tag": "confusion", "probe_score": 0.0838, "luna_label": 0, "luna_reason": null}]}, {"key": "aj2-131", "text": "sup> -US$150/m <sup>2</sup> ) * 6.6 km <sup>2</sup> = US$31 million).\n(f) The annual value of land (rental value) estimated based on 3 percent of its price.\n\n\n183. **Reduced frequency of diarrhea** . Improved sanitation can result in a reduction of diarrheal\ndiseases, which would otherwise occur due to environmental hazards. In Lebanon, diarrheal mortality\ndue to unsafe sanitation is negligible. <sup>62</sup> [^62: Only 1 case in 2012, based on Pruss-Ustun et al. 2014. Burden of disease from water, sanitation, and hygiene in low resource settings: a retrospective\nanalysis of data from 145 countries. _Journal of Tropical Medicine and International Hygiene._] However, diarrheal morbidity among children aged below five\nyears is estimated at 2,300 disability-adjusted life years (DALYs) at national level. <sup>63</sup> [^63: This is equivalent to about 19,170 episodes per year. WHO. 2014. Global Burden of Disease. WHO Geneva.] Only two percent\nof them are attributable to unsafe sanitation, which corresponds to 46 DALYs. <sup>64</sup> [^64: Personal communication with WHO officer.]\n\n\n184. It is assumed that in the project area, the number of diarrheal cases due to unsafe sanitation is\nproportional with the ratio of population served by this component (351,700 people) and that at the\nnational level (4.5 million people), or eight percent. Accordingly, diarrhea morbidity in children aged\nbelow five years due to unsafe sanitation is estimated at only 4 DALYs, or 34 episodes, <sup>65</sup> [^65: Considering a disability weight of 0.12.] if the project\nis not implemented. Considering that the implementation of Component 1 will result in avoidance of\nthese cases,", "source": "refugee_pads", "subset": "annotate_aj_part2", "spans": [{"key": "refugee_pads:000036:56:4:0", "start": 582, "end": 605, "surface": "data from 145 countries", "probe_tag": "confusion", "probe_score": 0.7813, "luna_label": 1, "luna_reason": "Cited retrospective analysis data support the reported diarrheal mortality finding."}]}, {"key": "aj2-132", "text": "**The World Bank**\nStrengthening Institutions for Refugee Administration Project (P165542)\n\n\n\n\n|Col1|hosting districts.|Col3|Col4|\n|---|---|---|---|\n|FY 22/23|#2. Up to additional five (5) outreach sessions on<br>the implementation arrangements for the visa<br>policy have been conducted in the top ten (10)<br>refugee hosting districts.|1,500,000.00|Scalability: Yes. Disbursements<br>prorated per each outreach s|\n|FY 23/24|#3. NADRA has provided access to the registered<br>refugee database to the CCAR to improve<br>functionality for implementation of the visa<br>policy.|2,000,000.00|Scalability: No|\n|FY24/25|#4. SAFRON has conducted a review of<br>implementation of the visa policy.|1,000,000.00|Scalability: No|\n\n\n\n|Verification Protocol Table: Disbursement Linked Indicators|Col2|\n|---|---|\n|<br>**DLI 1**|<br>Improved resolution of the complaints of refugees and refugee hosting communities through operationalized complaints<br>handling mechanisms|\n|**Description**|This DLI tracks the GoP's effort to create systems for handling complaints reported by refugees and host communities.|\n|**Data source/ Agency**|SAFRON/CCAR/CARs|\n|**Verification Entity**|Third Party Verification Agent|\n|**Procedure **<br>|Review of the database on grievances provided by CCAR<br>|\n\n\n32", "source": "refugee_pads", "subset": "annotate_aj_part2", "spans": [{"key": "refugee_pads:000009:40:0:0", "start": 477, "end": 493, "surface": "refugee database", "probe_tag": "confusion", "probe_score": 0.2638, "luna_label": 0, "luna_reason": "Database access is described, but its data are not shown informing analysis or decisions."}, {"key": "refugee_pads:000009:40:0:1", "start": 1230, "end": 1252, "surface": "database on grievances", "probe_tag": "confusion", "probe_score": 0.413, "luna_label": 0, "luna_reason": "DLI verification procedure describes project monitoring machinery, not substantive data use."}]}, {"key": "aj2-133", "text": "2. Broader social capital building outcome: Capacity building interventions for implementing\npartners and local authorities would include conflict resolution training, and emphasize sub-project\ndesign and supervision processes which build social capital and mutual accountability between\ncommunities and the array of support organizations and institutions.\n\n\n3. Intra-community equity outcomes: To address intra-community equity issues in a more\nsystematic manner, NaCSA would revise its Operations Manual to enhance procedures for community\nneeds identification and sub-project selection. The enhanced guidelines would include, inter alia, a\nrequirement for implementing partners to fill out a Community Assessment Form. This would include\ninformation on community population (by gender and age group), basic infrastructure, main income\ngenerating activities, housing, organization, forms and levels of outside assistance, and particularly\nvulnerable groups.\n\n6.5 How will the project monitor performance in terms of social development outcomes?\n\nA Social Assessment is under preparation. It is being designed so as to ensure that the project\nresponds to social development concerns by identifying the opportunities, constraints and social risks\n\n\n\ninherent in the project and translating these ideas into practical design and implementation measures.\nThe World Bank's Social Capital Assessment Tool (SOCAT) and instruments for analyzing local\ninstitutions will be used in the Social Assessment. Subsequent iterative rounds of social analysis using\nsimple locally adapted variants of these tools would continue during the duration of the project to collect\nand analyze data on social development issues. These would include associational memberships and\ntrust, the process of creation and destruction of social capital and data on groups and networks,\n\n\n\nsubjective well-being, political engagement, sociability, community activities, cohesion and\ncommunication. The Assessment would thus provide baseline data on social issues, recommend and\n\n\n\napply social capital measurement tools, and provide a framework for continuing social analysis\nthroughout the project.\n\n\n\n7. Safeguard Policies:\n7.1 Are any of the following safeguard policies triggered by the prcect?\n\n     - '& **~** P19 ~ f _-", "source": "refugee_pads", "subset": "annotate_aj_part2", "spans": [{"key": "sample:refugee_pads:000121:24:0:0", "start": 1670, "end": 1703, "surface": "data on social development issues", "probe_tag": "confusion", "probe_score": 0.333, "luna_label": 0, "luna_reason": null}]}, {"key": "aj2-134", "text": "s HRM strategy in\nthe civil service for 2023-2027). Recent gender audits of two public sector institutions carried out by the Jordanian National\nCommission for Women identified the need to improve gender mainstreaming, so as to ensure equal opportunities for\nwomen to assume leadership positions as well as to engage in digital jobs created in the public sector. Furthermore, as\nthe government continues to digitalize its services and introduce citizen engagement platforms, the gender digital gap\naround the adoption of digital ID and access to digitalized services through GSCs will be addressed. <sup>9</sup> [^9: Only about <mark>800,000 of the nearly 11 million ID holders have activated their digital IDs on Sanad as of January 2024, and only 35</mark>\n<mark>percent of those are women. Similarly, of the 90,000 visitors to the two existing GSCs since their inauguration, fewer than 20 percent</mark>\n<mark>have been women (the exact percentage is not available because MODEE has not been collecting GSC visitor demographics thus far).</mark>] Women will directly\nbenefit from the Program in three main ways: (1) through improved representation in senior positions in the civil service\nas a result of competency-based promotions and human resource management (HRM); (2) enhanced digital skills of\nwomen employed by the government and applying for jobs in the civil service; and (3) gender-balanced and inclusive\naccess to and use of DPI and trusted, user-centric digitalized services, including through the equitable expansion of Sanad\ncoverage, free access to the internet in the GSCs, and facilitation of access to services for women, persons with disabilities,\nand refugees through appropriate staffing at the GSCs. Also, persons with physical disabilities and elderly people (over 65\nyears of age) will benefit from the facilitated access to government services through GSCs, including because of the\nenforcement of accessibility guidelines contained in the 2022 _Jordan Government Websites Standards_ . These aim to make\nthe Jordanian government websites more", "source": "refugee_pads", "subset": "annotate_aj_part2", "spans": [{"key": "refugee_pads:000181:17:1:0", "start": 1006, "end": 1030, "surface": "GSC visitor demographics", "probe_tag": "confusion", "probe_score": 0.2576, "luna_label": 0, "luna_reason": "Demographics are unavailable; no substitute estimate or analytical use is provided."}]}, {"key": "aj2-135", "text": " income levels for many households have\nnot returned to pre-COVID-19 levels. By April 2021, income levels were still below pre-COVID-19 levels for at least\none third of households. The second lockdown in mid-2021 is likely to have stalled and even possibly reversed\nprogress in income recovery. In fact, 49 percent of MSMEs interviewed on the impact of the second lockdown\n\n\n[10 Uganda Comprehensive Refugee Response Portal (https://data2.unhcr.org/en/country/uga), September 20, 2020.](https://data2.unhcr.org/en/country/uga)\n11 Calculation based on district-level firm data from Census of Business Establishments, and refugee and host community household data\nfrom the Refugee and Host Community Household Survey.\n\n\nPage 10 of 92", "source": "refugee_pads", "subset": "annotate_aj_part2", "spans": [{"key": "refugee_pads:000073:15:3:1", "start": 581, "end": 614, "surface": "Census of Business Establishments", "probe_tag": "confusion", "probe_score": 0.7705, "luna_label": 1, "luna_reason": "Census data directly supports the stated district-level calculation."}, {"key": "refugee_pads:000073:15:3:2", "start": 620, "end": 661, "surface": "refugee and host community household data", "probe_tag": "keep", "probe_score": 0.9057, "luna_label": 1, "luna_reason": "Household data from a named survey directly supports the calculation."}, {"key": "refugee_pads:000073:15:3:3", "start": 671, "end": 714, "surface": "Refugee and Host Community Household Survey", "probe_tag": "confusion", "probe_score": 0.8727, "luna_label": 1, "luna_reason": "Named household survey data used in a calculation of income-related findings."}]}, {"key": "aj2-136", "text": "complementary and interact to achieve the objectives of accelerated growth and sustainable\ndevelopment.\n\n6. The first axis identifies energy as an important element of growth and the second axis\nhighlights the need to increase access to modern energy services.  To promote access to energy\nservices for the greatest number of people and improve their productive capacity, the\nGovernment will pay particular attention to rural areas where rates of access to energy are\ngenerally very low. To address energy service access, the Government plans to: (i) connect most\nof the population to the electricity network, (ii) install power stations in major centers outside the\nnetwork, (iii) develop multifunctional platforms with small networks providing access to energy\nfor sparsely populated communities, and (iv) use photo-voltaic systems for population in lowdensity areas. The SCADD pays particular attention to the development of renewable energies,\nin particular solar energy, and the development of interconnection with countries of the subregion.\n\n\n**B.** **Sectoral and Institutional Context**\n\n\n7. Burkina Faso faces limited access to modern energy sources. The electrification rate is\nabout 14 percent (about 40 percent in urban areas and no more than 5 percent in rural areas).\nThe full survey of the living conditions of households shows that the rate of access to electricity\nremains generally low in Burkina Faso, albeit with disparities between urban areas. The rate of\naccess to electricity by region varies greatly from one region to another 41.3 percent for the\nCenter region, 27.3 percent for the Hauts-Bassins, and 20.8 percent for the Cascades region.\nHowever, it remains very low for the Sahel (2.6 percent), the Center-South (3.2 percent), and\nCenter-North (3.4 percent) regions.\n\n\n\n\n\n\n\n\n\n8. Per capita consumption of electricity by total population is only 50 kWh per year. About\n90 percent of the population still relies on firewood and charcoal for the bulk of their", "source": "refugee_pads", "subset": "annotate_aj_part2", "spans": [{"key": "refugee_pads:000136:12:0:0", "start": 1292, "end": 1337, "surface": "survey of the living conditions of households", "probe_tag": "confusion", "probe_score": 0.6571, "luna_label": 1, "luna_reason": "Survey is cited as showing electricity-access findings."}]}, {"key": "aj2-137", "text": "_Sierra Leone_\n\n\nPRICES and GOVERNMENT FINANCE\n\n1981 1991 2000 2001 Inflation (%)\n_Domest)c_ _pHces_\n_(% change)_ c 1\nConsumer prices 16 7 102 7 -0.9 3 0 30 _< _\nImplicit GDP deflator 8 7 128 8 6 2 6 1 20\n\n_Govemment finance_ _10_\n_(% of GDP,_ _includes curent_ grants) 0\nCurrentrevenue .. 112 182 178 .10. 98 97 93 99 00 01\nCurrent budget balance .. -5 8 -4.5 -7 1 - GDP deflator _ CPI\nOverall surplus/deficit -10 4 -10.6 -12 3\n\n\nTRADE\n\n1981 1991 2000 2001 Export and Import levels (USS mnIll.)\n_(US$ millions)_\nTotal exports (fob) 147 176 75 78 400\nRutile . 72\nDiamonds (recorded) 32 10 21 300\nManufactures\nTotal imports (cHf) 317 158 161 303 20\nFood . 53 66 72 100\nFuel and energy 26 29 3d _ _8_\nCaptal goods .. 38 18 22  - __\n96 D6 97 9o 99 00 01\nExport price index _(1995=100)_ 90 86 87\nImport price Index (1995=100) 93 93 92 mExports ***Mrrports**\nTerms of trade (1995-100) 97 93 94\n\n\n\nBALANCE of PAYMENTS\n\n\n\n1981 1991 2000 2001 Curmnt account balance to GDP _(%)_\n_(US$_ _millions)_\nExports of goods and services 163 244 110 116 0\nImports of goods and services 349 226 212 252\nResource balance -186 18 -102 -137 .a*\n\n\n\nExports of goods and services 163 244 110 116 0\nImports of goods and services 349 226 212 252\nResource balance -186 18 -102 -137 .a*\n\nNet income -28 -60 -18 -20\nNet current", "source": "refugee_pads", "subset": "annotate_aj_part2", "spans": [{"key": "refugee_pads:000050:61:0:1", "start": 792, "end": 810, "surface": "Import price Index", "probe_tag": "confusion", "probe_score": 0.1084, "luna_label": 0, "luna_reason": "Standalone table indicator label with numeric values; not an independent data-use mention."}]}, {"key": "aj2-138", "text": "_Sierra Leone_\n\n\nPRICES and GOVERNMENT FINANCE\n\n1981 1991 2000 2001 Inflation (%)\n_Domest)c_ _pHces_\n_(% change)_ c 1\nConsumer prices 16 7 102 7 -0.9 3 0 30 _< _\nImplicit GDP deflator 8 7 128 8 6 2 6 1 20\n\n_Govemment finance_ _10_\n_(% of GDP,_ _includes curent_ grants) 0\nCurrentrevenue .. 112 182 178 .10. 98 97 93 99 00 01\nCurrent budget balance .. -5 8 -4.5 -7 1 - GDP deflator _ CPI\nOverall surplus/deficit -10 4 -10.6 -12 3\n\n\nTRADE\n\n1981 1991 2000 2001 Export and Import levels (USS mnIll.)\n_(US$ millions)_\nTotal exports (fob) 147 176 75 78 400\nRutile . 72\nDiamonds (recorded) 32 10 21 300\nManufactures\nTotal imports (cHf) 317 158 161 303 20\nFood . 53 66 72 100\nFuel and energy 26 29 3d _ _8_\nCaptal goods .. 38 18 22  - __\n96 D6 97 9o 99 00 01\nExport price index _(1995=100)_ 90 86 87\nImport price Index (1995=100) 93 93 92 mExports ***Mrrports**\nTerms of trade (1995-100) 97 93 94\n\n\n\nBALANCE of PAYMENTS\n\n\n\n1981 1991 2000 2001 Curmnt account balance to GDP _(%)_\n_(US$_ _millions)_\nExports of goods and services 163 244 110 116 0\nImports of goods and services 349 226 212 252\nResource balance -186 18 -102 -137 .a*\n\n\n\nExports of goods and services 163 244 110 116 0\nImports of goods and services 349 226 212 252\nResource balance -186 18 -102 -137 .a*\n\nNet income -28 -60 -18 -20\nNet current", "source": "refugee_pads", "subset": "annotate_aj_part2", "spans": [{"key": "refugee_pads:000121:61:0:0", "start": 751, "end": 769, "surface": "Export price index", "probe_tag": "confusion", "probe_score": 0.068, "luna_label": 0, "luna_reason": "Standalone table indicator header with numeric values"}, {"key": "refugee_pads:000121:61:0:1", "start": 792, "end": 810, "surface": "Import price Index", "probe_tag": "confusion", "probe_score": 0.1084, "luna_label": 0, "luna_reason": "Standalone table row label with index values; not an independent data-use mention."}]}, {"key": "aj2-139", "text": " the management<br>control to support the program<br>budgeting approach|Subcomponent 1.1 activities designed to embed the management<br>control function as advisory services for the program managers|\n|Joint IMF-World Bank PIM assessment|Component 2 designed to reflect the recommendation of the PIM<br>assessment such as (a) strengthening the link between the sectoral<br>strategies, the MTEF, program, and PIP, (c) establishing the Maturation<br>Funds, and (c) supporting PPBS|\n|Setting up of an initial BOOST database|Subcomponent 2.2 includes activities aiming to support the regular<br>update of the BOOST database and the online dissemination of the<br>budget execution report|\n|Rapid Result Initiative in the<br>procurement system / value chain<br>analysis in the procurement system|Performance contracts activities under Component 3 will be<br>implemented based on the preliminary lessons learned from the RRI<br>approach and value chain analysis|\n|Feasibility study of the Purchasing<br>Central Unit|Subcomponent 3.3 includes support to the implementation of the<br>Purchasing Central Unit once the final decision will be made by GoC|\n\n\n\n**III.** **IMPLEMENTATION**\n\n\n\nPage 28 of 93", "source": "refugee_pads", "subset": "annotate_aj_part2", "spans": [{"key": "refugee_pads:000044:31:1:0", "start": 505, "end": 519, "surface": "BOOST database", "probe_tag": "drop", "probe_score": 0.026, "luna_label": 0, "luna_reason": "Setting up the initial database is planned data production."}]}, {"key": "aj2-140", "text": "DJIBOUTI\nSchool Access and Improvement Program\n\n\n**Project Appraisal Document**\n\n\nMiddle East and North Africa Region\n\nMNSHD\n\n\n\nDate: November 17, 2000 Team Leader: Qaiser M. Khan\n\n\n\nCountry Director: Inder K. Sud Sector Director: Baudouy\nProject **ID:** P044585 Sector(s): EP - Primary Education, ES - Secondary\n\n\n\n. Education\nLending Instrument: Adaptable Program Loan <sup>(APL)</sup> Theme(s): Education; Gender and development\n\n\n\nPoverty Targeted Intervention: N\n\n\n\nProgram Fin ncing Data\n\n\n\nEstimated\nAPL Indicative Financing Plan Implementation Period (Bank FY) Borrower\n\n\n\n**IBRD** Others **Total** **COMMITMENT** **Closing**\n**US$** m % US$ m US$ m Date Date\nAPL 1 10.00 75.8 3.20 13.20 03/31/2001 06/30/2005 Republic of\n\n\n\nLoan/ Credit Djibouti\nCredit Ministry of\n\n\n\n________________ Education\n\n\n\nAPL 2 10.0 65.8 5.20 15.20 07/01/2005 06/30/2008 Republic of\n\n\n\nLoan/ Credit Djibouti\n\n\n\nCredit Ministry of\n\n\n\ni_________ ________________ Education\n\n\n\nAPL 3 10.00 41.0 14.40 24.40 07/01/2008 06/30/2011 Republic of\n\n\n\nLoan/ Credit Djibouti\nCredit Ministry of\n\n\n\nEducation\n\n\n\nTotal 30.00 22.80 52.80\nProject Financing Data Credit\nFor Loans/Credits/Others: Amount (US$m): 10.0\n\n\n\nProposed Terms: Standard Credit\n\n\n\nGrace period (years): 10 Years to maturity: 40\nCommitment fee: 0.50% (0% for FY01) Service charge: 0.75", "source": "refugee_pads", "subset": "annotate_aj_part2", "spans": [{"key": "refugee_pads:000175:4:0:0", "start": 1106, "end": 1128, "surface": "Project Financing Data", "probe_tag": "drop", "probe_score": 0.0462, "luna_label": 0, "luna_reason": "Standalone table heading, not a substantive data-use mention."}]}, {"key": "aj2-141", "text": "|**Component 3: Road Safety**|\n|Development<br>and<br>operationalization of the Road<br>Accident Database Management<br>System<br>Training<br>and<br>awareness<br>campaigns in the Project area|• <br>Road<br>safety<br>awareness<br>campaigns in the Project area,<br>and road safety data collection<br>and management as part of<br>contingency planning including<br>accident data attributed to<br>climate<br>change<br>such<br>as<br>increased runoff and higher<br>temperatures which increase<br>the pavement deterioration<br>hence the ride quality of the<br>road<br>and<br>necessitating<br>frequent<br>maintenance<br>routines.<br>• <br>Use<br>the<br>Road<br>Accident<br>Database Management System<br>to inform decision making<br>towards targeted interventions<br>that make the road safer to<br>users and more resilient to<br>climate change||\n\n\n\nPage 78 of 80", "source": "refugee_pads", "subset": "annotate_aj_part2", "spans": [{"key": "sample:refugee_pads:000146:82:1:0", "start": 267, "end": 283, "surface": "road safety data", "probe_tag": "drop", "probe_score": 0.0119, "luna_label": 0, "luna_reason": null}, {"key": "sample:refugee_pads:000146:82:1:1", "start": 361, "end": 374, "surface": "accident data", "probe_tag": "drop", "probe_score": 0.0483, "luna_label": 0, "luna_reason": null}]}, {"key": "aj2-142", "text": "**PAD** **DATA** **SHEET**\n\nLebanon\n\nSocial Promotion and Protection Project\n\n**PROJECT APPRAISAL DOCUMENT**\n\n\nMiddle East and North Africa\n\n**MNSHD**\n\n\n**Basic** **Information**\n\nDate: April 22, **2013** Sectors: Other social services **(100%)**\n\nCountry Director: Ferid Belhaj Themes: Social Safety Nets **_(50%);_** Social Risk Mitigation **_(25%);_**\nVulnerability Assessment and Monitoring **_(25%)_**\n\nSector Manager/Director: Yasser **El** Gammal/ Steen **EA** B-Partial Assessment\nLau Jorgensen Category:\n\nProject **ID:** P124761\n\nLending Instrument: Specific Investment Loan\n\nTeam Leader(s): Haneen Sayed\n\nJoint **IFC:**\n\n\nBorrower: Lebanese Republic, Ministry of Finance\n\nResponsible Agency: Ministry of Social Affairs\n\nContact: **H.E** Wael Abou Faour Title: Minister of Social Affairs\n\nTelephone No.: +961-1-611242 Email: ckalot@socialaffairs.gov.lb\n\n\nProject Implementation Period: Start Date: 01-Jan-2014 End Date: 30-June-2018\n\nExpected Effectiveness Date: **01** -Jan-2014\n\nExpected Closing Date: 31-Dec-2018\n\n\n**Project Financing Data(US$M)**\n\n[X] Loan [ **]** Grant [ **]** Other\n\n**[ ]** Credit [ ] Guarantee\n\n**For Loans/Credits/Others**\n\nTotal Project Cost: **US$70** million Total Bank **US$30** million\nFinancing **:**\nTotal Cofinancing: Financing Gap: **0", "source": "refugee_pads", "subset": "annotate_aj_part2", "spans": [{"key": "refugee_pads:000109:4:0:0", "start": 1029, "end": 1051, "surface": "Project Financing Data", "probe_tag": "drop", "probe_score": 0.0261, "luna_label": 0, "luna_reason": "Standalone table header, not a substantive data-use mention."}]}, {"key": "aj2-143", "text": "13\n\n\n**_Monitoring and Evaluation_**\n\n\nMonitoring will be done according to the development indicators given in the attachment to Annex 1.\nThe project will strengthen the capacity of CNOSEGE, and the Planning Unit of the Ministry so that\nmonitoring reports on the implementation of the reform can include key progress and impact\nindicators. Currently the Planning unit generates statistical data on all aspects of the education sector,\nhowever this can be further strengthened to monitor progress on key reform objectives such as access,\nequity and quality. In addition, during the donors round-table UNESCO offered support to develop an\nEducation Management Information System (EMIS). If this is not in place by the end of Phase I of the\nAPL, this would be a priority item for Phase II.\n\n\nEvaluation of the impact of the reforms will be done by CNOSEGE by recruiting experts in this field\n\nand an initial evaluation will be done at the end of Phase I. Particular areas of impact assessment will\nbe student performance and success in reaching out to disadvantaged groups. Normally, student\nperformance would be measured by overall test results but as the pool of students widens to include\nstudents from less advantaged socioeconomic groups, there will be a downward pressure on test\nscores. The Planning Unit of the Ministry will be strengthened to monitor progress in reaching out to\ndisadvantaged groups and test scores of students by socioeconomic background. Staff will carry out a\nrandom survey (5 to 10% sample) of students by socioeconomic background in 2001 to establish a\nbaseline. To keep the survey simple, the socioeconomic background questions will be limited to easily\nidentified categories such as day-laborers, civil servants, shopkeepers etc. The survey will be repeated\nin 2005 and 2110.\n\n\n**D.** PROJECT RATIONALE\n\n\n**1. Project alternatives considered and reasons for rejection**\n\nOriginally, the project was designed as a Sector Investment Loan, however, given the Government's\ncommitment to the education sector, and the", "source": "refugee_pads", "subset": "annotate_aj_part2", "spans": [{"key": "refugee_pads:000038:16:0:0", "start": 379, "end": 395, "surface": "statistical data", "probe_tag": "drop", "probe_score": 0.0402, "luna_label": 0, "luna_reason": "Planning unit generates the statistical data; it is project-produced rather than reused."}]}, {"key": "aj2-144", "text": "13\n\n\n**_Monitoring and Evaluation_**\n\n\nMonitoring will be done according to the development indicators given in the attachment to Annex 1.\nThe project will strengthen the capacity of CNOSEGE, and the Planning Unit of the Ministry so that\nmonitoring reports on the implementation of the reform can include key progress and impact\nindicators. Currently the Planning unit generates statistical data on all aspects of the education sector,\nhowever this can be further strengthened to monitor progress on key reform objectives such as access,\nequity and quality. In addition, during the donors round-table UNESCO offered support to develop an\nEducation Management Information System (EMIS). If this is not in place by the end of Phase I of the\nAPL, this would be a priority item for Phase II.\n\n\nEvaluation of the impact of the reforms will be done by CNOSEGE by recruiting experts in this field\n\nand an initial evaluation will be done at the end of Phase I. Particular areas of impact assessment will\nbe student performance and success in reaching out to disadvantaged groups. Normally, student\nperformance would be measured by overall test results but as the pool of students widens to include\nstudents from less advantaged socioeconomic groups, there will be a downward pressure on test\nscores. The Planning Unit of the Ministry will be strengthened to monitor progress in reaching out to\ndisadvantaged groups and test scores of students by socioeconomic background. Staff will carry out a\nrandom survey (5 to 10% sample) of students by socioeconomic background in 2001 to establish a\nbaseline. To keep the survey simple, the socioeconomic background questions will be limited to easily\nidentified categories such as day-laborers, civil servants, shopkeepers etc. The survey will be repeated\nin 2005 and 2110.\n\n\n**D.** PROJECT RATIONALE\n\n\n**1. Project alternatives considered and reasons for rejection**\n\nOriginally, the project was designed as a Sector Investment Loan, however, given the Government's\ncommitment to the education sector, and the", "source": "refugee_pads", "subset": "annotate_aj_part2", "spans": [{"key": "sample:refugee_pads:000100:16:0:0", "start": 379, "end": 395, "surface": "statistical data", "probe_tag": "confusion", "probe_score": 0.582, "luna_label": 0, "luna_reason": "The Planning unit generates this data, so it is project-produced rather than existing data used."}, {"key": "sample:refugee_pads:000100:16:0:1", "start": 1487, "end": 1500, "surface": "random survey", "probe_tag": "drop", "probe_score": 0.012, "luna_label": 0, "luna_reason": null}]}, {"key": "aj2-145", "text": "**Safeguards Deferral (from Decision Review Decision Note)**|**Safeguards Deferral (from Decision Review Decision Note)**|**Safeguards Deferral (from Decision Review Decision Note)**|\n|Will the review of Safeguards be deferred? [ ] Yes   [ X ]  No|Will the review of Safeguards be deferred? [ ] Yes   [ X ]  No|Will the review of Safeguards be deferred? [ ] Yes   [ X ]  No|Will the review of Safeguards be deferred? [ ] Yes   [ X ]  No|\n|**Project Financing Data(in USD Million)**|**Project Financing Data(in USD Million)**|**Project Financing Data(in USD Million)**|**Project Financing Data(in USD Million)**|\n|[  ]<br>Loan|[ X ]<br>IDA Grant|[  ]<br>Guarantee|[  ]<br>Guarantee|\n|[  ]<br>Credit|[ X ]<br>Grant|[  ]<br>Other|[  ]<br>Other|\n\n\ni", "source": "refugee_pads", "subset": "annotate_aj_part2", "spans": [{"key": "refugee_pads:000028:5:3:0", "start": 441, "end": 463, "surface": "Project Financing Data", "probe_tag": "drop", "probe_score": 0.0212, "luna_label": 0, "luna_reason": "Standalone table header for project financing information."}]}, {"key": "aj2-146", "text": "**The World Bank**\nEducation Quality Improvement Project (P179363)\n\n\n\n\n\n\n\n|Col1|inclusion, and sustainability)|Col3|Col4|Col5|Col6|\n|---|---|---|---|---|---|\n|Number of sector staff participating in<br>capacity building trainings under the<br>project|This indicator will measure<br>the number of sector staff<br>trained on (EMIS, national<br>and international<br>assessments and data<br>analysis,<br>tutoring/accelerated<br>learning programs, ECEC<br>reforms, integrated<br>approach to designing and<br>implementing resilient,<br>sustainable, and inclusive<br>school and preschool<br>projects). Progress will be<br>tracked, and the capacity<br>building plan will be<br>updated every two years.|Annual<br>|Progress and<br>monitoring<br>reports,<br>capacity<br>building plan<br>|Progress and<br>monitoring reports<br>|NORLD, MoER, PMT<br>|\n|Monitoring tool with reliable gender-<br>disaggregated data to identify<br>disadvantaged students to receive<br>accelerated learning|This indicator will capture<br>the development of the<br>monitoring tool with reliable<br>gender-disaggregated data<br>to identify disadvantaged<br>students to receive tutoring,<br>accelerated learning or<br>other catch-up program|<br>Annual<br>|EMIS<br>|EMIS and monitoring<br>tool data<br>|CTICE, MoER, PMT<br>", "source": "refugee_pads", "subset": "annotate_aj_part2", "spans": [{"key": "refugee_pads:000185:52:0:0", "start": 880, "end": 898, "surface": "disaggregated data", "probe_tag": "drop", "probe_score": 0.0241, "luna_label": 0, "luna_reason": "Fragment embedded in a table indicator and monitoring-tool development entry."}]}, {"key": "aj2-147", "text": "**The World Bank**\nProductive Safety Net for Socioeconomic Opportunities Project (P177663)\n\n\n\n\n\n\n\n\n\n|Col1|Project Operations Manual,<br>and have received cash<br>transfers, at least for one<br>payment cycle.|minimum<br>on a<br>quarterly<br>basis|Information<br>System (MIS)|course of project<br>implementation.<br>Payment data will be<br>liked to and updated in<br>the MIS.|Col6|\n|---|---|---|---|---|---|\n|Number of beneficiaries receiving cash for<br>performing labor intensive public works<br>who are female|<br>Number of total<br>beneficiaries that directly<br>receive cash transfer for<br>working on LIPW under sub-<br>component 1.1 on behalf of<br>beneficiary HH, of which are<br>female|This<br>indicator<br>will be<br>measured<br>at a<br>minimum<br>on a<br>quarterly<br>basis<br>|Registration<br>and payment<br>data in the<br>SNSOP MIS<br>|Beneficiary data is<br>collected during<br>registration and<br>updated over the<br>course of the project.<br>Payment data will also<br>be periodically updated<br>in the MIS<br>|Selected Implementing<br>Partner<br>|\n|Number of beneficiary households<br>receiving cash transfer for participating in<br>the behavioral change communication<br>training|The number of beneficiary<br>households that participate<br>in behavioral change", "source": "refugee_pads", "subset": "annotate_aj_part2", "spans": [{"key": "refugee_pads:000153:60:0:0", "start": 314, "end": 326, "surface": "Payment data", "probe_tag": "drop", "probe_score": 0.0239, "luna_label": 0, "luna_reason": "Future project payment-data updating is planned monitoring activity."}, {"key": "refugee_pads:000153:60:0:1", "start": 833, "end": 842, "surface": "SNSOP MIS", "probe_tag": "confusion", "probe_score": 0.1431, "luna_label": 1, "luna_reason": "Named MIS provides registration and payment data for the indicator."}]}, {"key": "aj2-148", "text": "**The World Bank**\nCash for Jobs Project (P175327)\n\n\n\n\n\n\n\n\n\n|Beneficiaries of social safety net programs (CRI, Number)|Col2|56,090.00 200,000.00|\n|---|---|---|\n|Beneficiaries of social safety net programs - Female (CRI,<br>Number)||50,000.00<br>170,000.00|\n|Beneficiaries of Safety Nets programs - Unconditional cash<br>transfers (number) (CRI, Number)||56,090.00<br>200,000.00|\n|Beneficiaries of safety nets programs - emergency cash<br>transfers, disaggregated by gender (Number)||0.00<br>25,000.00|\n|Beneficiaries of Safety Nets programs - refugees,<br>disaggregated by gender (Number)||0.00<br>8,000.00|\n|Beneficiaries of Safety Nets programs - host communities,<br>disaggregated by gender (Number)||0.00<br>12,000.00|\n\n\n|To promote productive inclusion and access to jobs|Col2|Col3|Col4|\n|---|---|---|---|\n|Beneficiaries of job-focused interventions (CRI, Number)||0.00<br>100,000.00|0.00<br>100,000.00|\n|Beneficiaries of job-focused interventions - Female (CRI,<br>Number)||0.00<br>80,000.00|0.00<br>80,000.00|\n|Beneficiaries of job-focused interventions - refugees", "source": "refugee_pads", "subset": "annotate_aj_part2", "spans": [{"key": "refugee_pads:000130:63:0:0", "start": 19, "end": 40, "surface": "Cash for Jobs Project", "probe_tag": "drop", "probe_score": 0.0316, "luna_label": 0, "luna_reason": "Project title does not identify or show use of a real data resource."}]}, {"key": "aj2-149", "text": "\ntargeted communities and assisted conmmunities; into national planning and\nbeneficiaries; and                  - Technical audits resource allocation\n\n                  - Proportion of sub-projects frameworks (such as the\noperative 24emonths after National Recovery Strategy,\ncorpletion. the PRSP, and the MTEF)\n\n\n**Output** **from** **each** **Output Indicators:** **Project** **reports:** **(from** **Outputs to Objective)**\n**Component:**\n**1.** Community-Driven\n**Program** (CDP)\nl(a) Rural social and Ia. 1 At least 1,000 - M&E data; - Targeting mnechanisms are\neconomic infrastructure and 'community based\" - NaCSA Progress reports efficient and implemented with\nservices are established, sub-projects implemented minimal political interference;\nupgraded and used. (breakdown by type and\nlocation).\n\n\nla.2 At least 90% of                  - Annual technical audit -Line agencies and/or other\n\n\n-25", "source": "refugee_pads", "subset": "annotate_aj_part2", "spans": [{"key": "sample:refugee_pads:000013:29:2:0", "start": 530, "end": 538, "surface": "M&E data", "probe_tag": "drop", "probe_score": 0.0, "luna_label": 0, "luna_reason": null}]}, {"key": "aj2-150", "text": "\nSOE portfolio.\n\n\n**Component 2: Improving quality of public investment in selected sectors (US$5.5 million)**\n\n\n39. This component aims to address some key bottlenecks in the maturation, programming,\nbudgeting, and execution monitoring processes of public investment activities. MINEDUB and\nMINSANTE will be major beneficiaries of this component to be implemented under the leadership of\nMINEPAT. This component will consist of the following subcomponents:\n\n\n     - **Subcomponent 2.1: Strengthening public investment budget programming and**\n**budgeting.** The subcomponent will provide support to enhance the PIB preparation\nprocess by (a) defining and implementing public investment management, in particular\ninvestment project programming, preparation and selection (policy note/decree/order on\na new Project Investment Management (PIM) cycle <sup>26</sup> and stocktaking of existing\ninvestment projects to identify projects to be supported from appraisal to selection or to\nbe cancelled); (b) defining and establishing ICT-based solution for the management of\ninformation of public investment project preparation and piloting performance contracting\nfor the Cellules PBBS of MINEDUB and MINSANTE and for the MINEPAT/ _Direction de la_\n\n\n25 BOOST is a Bank-wide collaborative effort launched in 2010 to facilitate access to budget data and promote\neffective use for improved decision-making processes, transparency and accountability, deployed in about 40\ncountries so far. It provides user-friendly platforms where all expenditures data can be easily accessed and used by\nresearchers, government officials and citizens.\n26 Strategic guidance, programming, appraisal, project selection in program budgets preparation, implementation, and\nevaluation and audit.\n\n\nPage 22 of 93", "source": "refugee_pads", "subset": "annotate_aj_part2", "spans": [{"key": "sample:refugee_pads:000044:25:1:0", "start": 1330, "end": 1341, "surface": "budget data", "probe_tag": "drop", "probe_score": 0.0, "luna_label": 1, "luna_reason": null}, {"key": "sample:refugee_pads:000044:25:1:1", "start": 1526, "end": 1543, "surface": "expenditures data", "probe_tag": "drop", "probe_score": 0.0001, "luna_label": 1, "luna_reason": null}]}, {"key": "aj2-151", "text": "**FIGURE 10:** Type of floor material for the Shona community and Kenyans\n\n\n\n\n\n\n\n100\n\n\n80\n\n\n60\n\n\n40\n\n\n20\n\n\n0\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nEarth/sand Dung Cement Carpet Ceramic tiles Other\n\n\n**Source:** Shona SES (2019) and KIHBS (KNBS 2015/16).\n\n\n **FIGURE 11:** Type of wall material for the Shona community and Kenyans\n\n\n\n100\n\n\n80\n\n\n60\n\n\n40\n\n\n20\n\n\n0\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nMud/with stone/bamboo/uncovered adobe\nCorrugated iron sheet\n\nCement/cement blocks/bricks\nStone with lime/cement\nOther\n\n\n**Source:** Shona SES (2019) and KIHBS (KNBS 2015/16).\n\n\n69 percent). However, for Kenyans, those living in Nairobi are almost as likely to use cement as those in\nKiambu (78 percent vs. 73 percent, p<0.293).\n\n\n**21. On average, most Shona community houses are built using stone with lime and cement.** Almost\nhalf of Shona houses, mainly in Nairobi, have stone with lime or cement as wall materials, which is less\nthan what is observed for nationals living in urban areas where cement blocks are more common (Figure 11). The use of stone with lime for walls is more common for Shona community houses in Nairobi\nthan those in Kiambu. In contrast, Shona house walls in Kiambu are more likely to be built with corrugated iron sheets.\n\n###### Findings  13", "source": "reliefweb", "subset": "annotate_aj_part2", "spans": [{"key": "reliefweb:001424:27:0:1", "start": 229, "end": 234, "surface": "KIHBS", "probe_tag": "keep", "probe_score": 0.9777, "luna_label": 1, "luna_reason": "Named household budget survey cited as the source for presented housing-material figures."}]}, {"key": "aj2-152", "text": "anos en sus\ncomunidades, así como en atender\nsus necesidades básicas.\n\n\n\n**Figura 7.1 Intención de quedarse**\n\n\n\nSí No\n\n\nFuentes: Elaboración propia a partir de las siguientes encuestas. Chile: Encuesta de Migración (Banco\nMundial, SERMIG y Centro UC 2022). Colombia: Pulso de la Migración (DANE 2021). Ecuador, Encuesta\na Personas en Movilidad Humana y en Comunidades Receptoras en Ecuador (EPEC 2019) y Encuestas\nTelefónicas de Alta Frecuencia ALC Banco Mundial (HFPS 2022). Perú: Encuesta dirigida a la población\nvenezolana que reside en el país (ENPOVE II 2022), INEI.\n\n\nNota: El plazo de los planes de residencia para venezolanos es de un año en Colombia y cinco años en\nChile. En Perú y Ecuador no se especifica. Los intervalos de confianza están incluidos.", "source": "reliefweb", "subset": "annotate_aj_part2", "spans": [{"key": "reliefweb:001322:43:1:1", "start": 268, "end": 289, "surface": "Pulso de la Migración", "probe_tag": "keep", "probe_score": 0.9397, "luna_label": 1, "luna_reason": "Named migration survey cited as the source for the figure."}]}, {"key": "aj2-153", "text": " ensure the protection of stateless persons, the\nnaturalization of the Makonde community, and an agreement to naturalize qualifying members of the\nShona community. However, scarce socioeconomic information of stateless populations that is comparable to nationals prevents a deeper understanding of their living conditions, hence hindering efforts\nto design targeted policy aimed at solving statelessness.\n\n\n**The Shona SES provides comparable socioeconomic profiles for the Shona community and nation-**\n**als, while contributing toward informing a targeted response to address the socioeconomic impacts**\n**of the COVID-19 pandemic.** Together with the Department of Immigration Services (DIS) and the\nKenya National Bureau of Statistics (KNBS) of the GoK, UNHCR Kenya, with technical support from the\nWorld Bank, conducted a preregistration exercise and socioeconomic survey for the Shona commu\nnity. The Shona SES marks one of the first quantitative studies of a stateless population that is based\non a national socioeconomic assessment tool. The SES compares the living conditions of the Shona\ncommunity residing in Nairobi and urban Kiambu counties to the conditions of Kenyan nationals in\nsuch counties, as well as to the national urban average. <sup>3</sup> [^3: Results from the Shona survey are compared to those from the Kenya National Bureau of Statistics and its Kenya Integrated\nHousehold Budget Survey 2015/16.] This approach does not attempt to establish\na causal connection between their legal status and living conditions. It does, however, provide evidence that shows strong correlations between statelessness, access to rights, and key indicators of\nwell-being. In addition, the SES links its findings to the results of the first wave of the Kenya COVID-19\nRapid Response Phone Surveys (RRPS) designed to assess the socioeconomic impacts of the COVID19 pandemic on nationals, refugees, and stateless persons.\n\n\n1 Based on the information available from 76 countries.\n2 [https://www.unhcr.org/protection/statelessness/54621bf49/global-action-plan-end-statelessness-2014-2024.html](https", "source": "reliefweb", "subset": "annotate_aj_part2", "spans": [{"key": "sample:reliefweb:001424:10:1:0", "start": 413, "end": 422, "surface": "Shona SES", "probe_tag": "keep", "probe_score": 0.96, "luna_label": 1, "luna_reason": null}, {"key": "sample:reliefweb:001424:10:1:1", "start": 1761, "end": 1804, "surface": "Kenya COVID-19\nRapid Response Phone Surveys", "probe_tag": "keep", "probe_score": 0.9836, "luna_label": 1, "luna_reason": null}]}, {"key": "aj2-154", "text": "X\n###### Who are included in the statistics?\n\n\n\n**Refugees** include individuals\nrecognized under the 1951\nConvention relating to the Status\nof Refugees; its 1967 Protocol; the\n1969 OAU Convention Governing\nthe Specific Aspects of Refugee\nProblems in Africa; those\nrecognized in accordance with\nthe UNHCR Statute; individuals\ngranted complementary forms of\nprotection; <sup>**(38)**</sup> or, those enjoying\ntemporary protection. <sup>**(39)**</sup> The\nrefugee population also includes\npeople in a refugee-like situation. <sup>**(40)**</sup>\n\n\n**Internally displaced persons**\nare people or groups of individuals\nwho have been forced to leave\ntheir homes or places of habitual\nresidence, in particular as a result\nof, or in order to avoid the effects\nof armed conflict, situations of\ngeneralized violence, violations of\nhuman rights, or natural/humanmade disasters, and who have not\ncrossed an international border. <sup>**(41)**</sup>\nFor purposes of UNHCR’s statistics,\nthis population only includes\nconflict-generated IDPs to whom\nthe Office extends protection and/\nor assistance. The IDP population\nalso includes people in an IDP-like\nsituation. <sup>**(42)**</sup>\n\n\n**Asylum-seekers** are individuals\nwho have sought international\nprotection and whose claims for\nrefugee status have not yet been\ndetermined. Those covered in\n\n\n\nthis report refer to claimants\nwhose individual applications\nwere pending at the end of 2010,\nirrespective of when they may have\nbeen lodged.\n\n\n**Stateless persons** are individuals\ndefined under international law as\npersons who are not considered as\nnationals by any State under the\noperation of its law. In other words,\nthey do not possess the nationality\nof any State.", "source": "reliefweb", "subset": "annotate_aj_part2", "spans": [{"key": "sample:reliefweb:000915:18:0:0", "start": 953, "end": 971, "surface": "UNHCR’s statistics", "probe_tag": "keep", "probe_score": 0.9816, "luna_label": 0, "luna_reason": "Defines the statistical population; does not show data being used or analyzed."}]}, {"key": "aj2-155", "text": "\n**sos en la tramitación. Se calcula que, en los**\n**lugares donde ACNUR trabajaba con los**\n**desplazados internos, 1,6 millones de per-**\n**sonas pudieron regresar a su hogar en 2012.**\n**Lamentablemente, la situación de muchos**\n**países impidió el retorno de millones de**\n**desplazados forzosos. Por ejemplo, el**\n**número de refugiados considerados en sit-**\n**uaciones prolongadas era de 6,4 millones**\n**al finalizar el año.**\n\n**Las cifras de Tendencias Globales 2012**\n**se basan en datos facilitados por gobiernos,**\n**organizaciones no gubernamentales y AC-**\n**NUR. Los números se han redondeado**\n**a la unidad de centena o de millar más**\n**próxima. Dado que tendrán que realizarse**\n**algunos ajustes para el Anuario estadístico**\n**2012 que se publicará más adelante este año,**\n**las cifras incluidas en este informe deben**\n**considerarse provisionales y susceptibles de**\n**modificación. Salvo que se especifique lo**\n**contrario, el informe no hace referencia a**\n**hechos ocurridos después del 31 de diciem-**\n**bre de 2012.**", "source": "reliefweb", "subset": "annotate_aj_part2", "spans": [{"key": "reliefweb:001451:5:2:0", "start": 493, "end": 524, "surface": "datos facilitados por gobiernos", "probe_tag": "keep", "probe_score": 0.9492, "luna_label": 1, "luna_reason": "Government-provided data underpin Global Trends figures and reported refugee estimates."}]}, {"key": "aj2-156", "text": "<br>Q3<br>Q4<br>Italy|**Table 8. Origin of asylum applicants in 43 industrialized countries by quarter, 2007**<br>Covering 43 countries which provided monthly data to UNHCR (excluding Italy). <br>Total<br>2007<br>No. of applications (excluding Italy)<br>Change (%)<br>Share (%)<br>including<br>Origin<br>Q1<br>Q2<br>Q3<br>Q4<br>Total<br>Q2-Q1<br>Q3-Q2<br>Q4-Q3<br>Q1<br>Q2<br>Q3<br>Q4<br>Italy|**Table 8. Origin of asylum applicants in 43 industrialized countries by quarter, 2007**<br>Covering 43 countries which provided monthly data to UNHCR (excluding Italy). <br>Total<br>2007<br>No. of applications (excluding Italy)<br>Change (%)<br>Share (%)<br>including<br>Origin<br>Q1<br>Q2<br>Q3<br>Q4<br>Total<br>Q2-Q1<br>Q3-Q2<br>Q4-Q3<br>Q1<br>Q2<br>Q3<br>Q4<br>Italy|**Table 8. Origin of asylum applicants in 43 industrialized countries by quarter, 2007**<br>Covering 43 countries which provided monthly data to UNHCR (excluding Italy). <br>Total<br>2007<br>No. of applications (excluding Italy)<br>Change (%)<br>Share", "source": "reliefweb", "subset": "annotate_aj_part2", "spans": [{"key": "sample:reliefweb:000427:20:3:0", "start": 151, "end": 163, "surface": "monthly data", "probe_tag": "keep", "probe_score": 0.9605, "luna_label": 1, "luna_reason": null}, {"key": "sample:reliefweb:000427:20:3:1", "start": 523, "end": 535, "surface": "monthly data", "probe_tag": "keep", "probe_score": 0.9611, "luna_label": 1, "luna_reason": null}]}, {"key": "aj2-157", "text": " del\nMIRPS en Honduras, especialmente en el contexto de la\nCOVID-19, y se han brindado respuestas adaptadas a sus\nnecesidades específicas.\n\n\n\nPara las personas desplazadas internamente, la Secretaría\nde Derechos Humanos (SEDH) continúa implementando\nuna ruta de asistencia y protección que facilite la\nrecepción, atención y remisión de casos. Se ejecuta un\nproyecto piloto de asistencia humanitaria, financiado en\n\n\n\n8 En 2020 el cálculo sería: 53x100 / 5,498 = 0.96%. Del porcentaje total registrado, se identificó que, el 64% son de sexo masculino y el 26% de sexo femenino.\nLa variación del porcentaje entre ambos años, se explica por la relación de personas que solicitaron protección internacional de entre una alta estadística de\nmigración irregular registrada en 2019; comparada con el descenso en la migración irregular experimentado en 2020 por la Covid-19. Aún así, hay variables\nque afectan este dato, como el deseo de las personas de solicitar protección o no, y la posibilidad de identificar perfiles de riesgo; y la interrelación entre\nambos factores.\n\n\n**39**", "source": "reliefweb", "subset": "annotate_aj_part2", "spans": [{"key": "reliefweb:000818:38:2:0", "start": 721, "end": 755, "surface": "estadística de\nmigración irregular", "probe_tag": "confusion", "probe_score": 0.3848, "luna_label": 1, "luna_reason": "2019 migration statistics explain variation in protection-request percentages."}]}, {"key": "aj2-158", "text": " la débil\nintervención de adolescentes para garantizar la\natención centrada en los éxitos, la capacidad para\nmejorar la aceptación de anticonceptivos o las\ncomunicaciones para recopilar más información.\n\n\nLos tres programas visitados para los estudios de\ncasos fueron: programa Profamilia en la costa del\nPacífico en Colombia, Centro Juvenil de Gulu de la\nfundación Straight Talk Foundation en el norte de\nUganda y Red de Salud Reproductiva de los\nAdolescentes (ARHN) en Mae Sot, Tailandia.\n\nLos tres programas de estudios de casos tienen\nuna presencia bien establecida y una reputación\npositiva en sus respectivos países. Profamilia es\nun proveedor de SRH establecido que ofrece\nservicios de ASRH en toda Colombia. En 1998, la\norganización amplió sus programas a las regiones\nafectadas por situaciones de crisis al adaptar de\nmanera exitosa su modelo para satisfacer a este\ngrupo vulnerable. La fundación Straight Talk\nFoundation comenzó a hacerse cargo de los\n\n\n\nadolescentes afectados por las crisis en 2004 cuando\nun conflicto activo prevalecía en el norte de\nUganda. La Fundación ha documentado su\naprendizaje sobre cómo llegar de manera efectiva\na los adolescentes afectados por las crisis a través\nde la publicación de Kintu et al en 2007. <sup>42</sup> La ARHN,\ntambién establecida para cubrir específicamente\nlas necesidades de las comunidades extranjeras\ndesplazadas de y dentro de Birmania (Myanmar),\nha estado funcionando por casi 10 años. Al comparar\ncada programa con la lista de verificación del IAFM\nde los servicios ad", "source": "reliefweb", "subset": "annotate_aj_part2", "spans": [{"key": "reliefweb:000914:16:1:0", "start": 1485, "end": 1515, "surface": "lista de verificación del IAFM", "probe_tag": "confusion", "probe_score": 0.8684, "luna_label": 0, "luna_reason": "Checklist used as comparison framework, not a cited or analyzed data resource."}]}, {"key": "aj2-159", "text": "\nNVivo statistical software was used to thematically code the transcripts and cross-reference them with the\ninsights generated from manual cross-referencing. Taken together, this analytical approach allowed for an\n\nand coping strategies.\nin - depth and collective interpretation of the data by the research team, highlighting participants’ perceptions\n\nOur quantitative data builds on the impact evaluation of the SPIR programme conducted in Amhara and\nOromiya by Alderman _et al_ . (2021), which ran from 2018 (baseline) to 2021 (endline). The study _woredas_\nwere selected purposefully by the SPIR programme implementation teams, in collaboration with regional\ngovernments and partners. An additional household survey was conducted by the Better Assistance in\nCrises (BASIC) Research team in late 2022/early 2023 specifically to assess the role of social protection in\nthe context of conflict (in the case of Amhara) and multiple shocks (in the case of Oromiya), conducted in\nAmhara (November–December 2022) and Oromiya (March 2023).\n\nThe sample for the follow-up survey consisted of 1,014 households in Amhara (from 51 _kebeles_ and seven\n_woredas_ ) and 1,255 in Oromiya (from 43 _kebeles_ and six _woredas_ ). The Amhara sample consisted of\nhouseholds that had received PSNP payments alone, or PSNP payments and additional support through the\nSPIR programme at some point in the previous six years or were still receiving them. The Oromiya sample\nalso included households that had never benefited from the PSNP or the SPIR programme. In addition to the\nhousehold questionnaire, community and market surveys at _woreda_ and _kebele_ levels were also conducted. <sup>2</sup>\nThe aim of the post-conflict survey was to assess differences in poverty and livelihood outcomes among\nhouseholds with varying levels of exposure to conflict", "source": "reliefweb", "subset": "annotate_aj_part2", "spans": [{"key": "reliefweb:000561:8:1:0", "start": 703, "end": 719, "surface": "household survey", "probe_tag": "confusion", "probe_score": 0.5636, "luna_label": 0, "luna_reason": "The sentence describes the project research team's survey collection, not use of existing data."}, {"key": "reliefweb:000561:8:1:1", "start": 1583, "end": 1611, "surface": "community and market surveys", "probe_tag": "confusion", "probe_score": 0.654, "luna_label": 0, "luna_reason": "Surveys were conducted as part of the study, indicating data production rather than reuse."}]}, {"key": "aj2-160", "text": "**9 /** Synthesis of key findings from Inter-Agency Humanitarian Evaluations (IAHEs) of the international responses to crises in\nthe Philippines (Typhoon Haiyan), South Sudan and the Central African Republic\n\n\nBox 1: The crises and responses covered by the IAHEs\n\n\nPhilippines (Low Middle Income Country): Rapid onset natural hazard-related disaster. Typhoon\nHaiyan hit the Central Visayas region of the Philippines on 8 November 2013. The typhoon,\ntogether with the related storm surge, caused massive devastation. Within four days, the\nUnited Nations Emergency Relief Coordinator declared an L3 emergency and the Humanitarian\nCountry Team (HCT) released a Humanitarian Action Plan for international assistance alongside\nthe Government’s own response. A massive response was launched with 462 surge personnel\ndeployed within three weeks. The 12-month SRP was published on 10 December 2013. Its total\nbudget of US$788 million was 60 per cent funded.\n\n\nThe subsequent inter-agency response formed only part of a larger set of responses to the\nemergency including those of the Government, the private sector, Filipino and broader Asian\ncivil society and the Filipino diaspora. On 4 July 2014, the Government announced the end of\nthe humanitarian phase of the Typhoon Haiyan response. In response to this, the HCT decided\nto close the SRP on 31 August 2014.\n\nSouth Sudan (Low Income Country): Civil conflict/rapid mass displacement. After achieving\nindependence from Sudan in 2011 following decades of civil war, the newly emerged state of\nSouth Sudan was itself plunged into civil war in December 2013. Existing aid operations, largely\ntargeting widespread acute malnutrition, were scaled up in 2014 (following the L3 declaration\nin February) in the light of escalating needs, including mass internal displacement. By the end\nof 2014, the planning figure for internally displaced persons (IDPs) had reached 1.95 million, and\nmore than 100,000 people had sought sanctuary in United Nations bases. At the beginning of\n2015", "source": "reliefweb", "subset": "annotate_aj_part2", "spans": [{"key": "reliefweb:000991:10:0:0", "start": 1837, "end": 1885, "surface": "planning figure for internally displaced persons", "probe_tag": "confusion", "probe_score": 0.7338, "luna_label": 1, "luna_reason": "Planning figure reports a concrete existing displacement estimate."}]}, {"key": "aj2-161", "text": "adosAmericas/Ecuador/2011/Refugiados_urbanos_en_Ecuador, February 2011.</u>\n\nJesuit Refugee Service _, Invisible and forgotten:_ _Colombian Refugees Seek_\n_Recognition and Renewed Dignity in Ecuador_, The Refugee Voice,\n<u>http://www.jrsusa.org/Assets/Publications/File/JRSUSA-RefVoice-Sept08.pdf,</u>\nSeptember 2008.\n\n_Refugee Processing Center_ - Arrivals data report, www.wrapsnet.org\n\nUNHCR, _Global Needs Assessment Pilot Report,_\n<u>http://www.unhcr.org/48ef09a62.html, 2008.</u>\n\nUNHCR, _2009 Global Trends_, http://www.unhcr.org/4c11f0be9.html, June 2010.\n\nUNHCR, _Magnitude of the Refugee Situation 2000-2010,_ UNHCR- Ecuador, 2010.\n\nUNHCR anti-discrimination campaign, www.ensuszapatos.com\n\nXavier Orellana, Large-scale refugee registration project starts in Ecuador, UNHCR,\nhttp://www.unhcr.org/news/NEWS/49cce42b2.html, March 2009.\n\n\n13", "source": "reliefweb", "subset": "annotate_aj_part2", "spans": [{"key": "reliefweb:000910:14:1:0", "start": 349, "end": 369, "surface": "Arrivals data report", "probe_tag": "confusion", "probe_score": 0.242, "luna_label": 0, "luna_reason": "Bibliographic report title, with no shown use of its data."}]}, {"key": "aj2-162", "text": "## **Acronyms**\n\n5W:OP Who does What, Where? Operational presence analysis including the “when”\nand “for whom” dimensions\n\n\nCRPD UN Convention on the Rights of People with Disabilities\n\n\nDHS Demographic and Health Survey\n\n\nDPO <mark>Organizations of persons with disabilities</mark>\n\n\nEMIS Education Management Information Systems\n\n\nHMIS Health Management Information Systems\n\n\nIASC Inter-Agency Steering Committee, mechanism for inter-agency coordination\nof humanitarian assistance\n\n\nINGO International Non-Governmental Organization\n\n\nL3 Level 3 Emergency, a system-wide designation for the most complex and\nchallenging emergency situations\n\n\nMARA Monitoring, Analysis, and Reporting Arrangements on Conflict-Related Sexual\nViolence\n\n\nMICS Multiple Indicator Cluster Survey\n\n\nMIS Management Information Systems\n\n\nMRM Monitoring and Reporting Mechanisms on grave violations\n\n\nOCHA Office of the Coordinator of Humanitarian Affairs\n\n\nOHCHR Office of the High Commissioner for Human Rights\n\n\nProGres Profile Global Registration System, the UNHCR database application for\nrefugee registration data\n\n\nUNDESA United Nations Department for Economic and Social Affairs\n\n\nUNDP United Nations Development Program\n\n\nUNHCR United Nations High Commissioner for Refugees\n\n\nUNICEF United Nations Children’s Fund\n\n\nCollecting Data on Persons with Disabilities in Humanitarian Contexts 1", "source": "reliefweb", "subset": "annotate_aj_part2", "spans": [{"key": "reliefweb:001044:5:0:1", "start": 736, "end": 774, "surface": "MICS Multiple Indicator Cluster Survey", "probe_tag": "confusion", "probe_score": 0.0632, "luna_label": 0, "luna_reason": "Survey acronym is defined without citing or using its data."}, {"key": "reliefweb:001044:5:0:2", "start": 990, "end": 1032, "surface": "ProGres Profile Global Registration System", "probe_tag": "confusion", "probe_score": 0.1804, "luna_label": 0, "luna_reason": "Named database application is defined without showing its data being used."}]}, {"key": "aj2-163", "text": "wopisrc=https%3A%2F%2Funicef-my.sharepoint.com%2Fpersonal%2Fjkaplan_unicef_org%2F_vti_bin%2Fwopi.ashx%2Ffiles%2Faef4415260cf4eee99f772a08d37b6bd&wdenableroaming=1&mscc=1&wdodb=1&hid=3FFAB5A0-107D-6000-9DF2-6B5F2D465E2B&wdorigin=BrowserReload&jsapi=1&jsapiver=v1&newsession=1&corrid=b990a935-a4cc-4491-9c61-de45fcb3ff92&usid=b990a935-a4cc-4491-9c61-de45fcb3ff92&sftc=1&cac=1&mtf=1&sfp=1&instantedit=1&wopicomplete=1&wdredirectionreason=Unified_SingleFlush&rct=Normal&ctp=LeastProtected#_ftnref1)</u>\n\n\n<u>[[2] Data from 2018 show that 78% of refugees were living in protracted situations, up from 66% the previous](https://euc-word-edit.officeapps.live.com/we/wordeditorframe.aspx?ui=en%2DUS&rs=en%2DUS&wopisrc=https%3A%2F%2Funicef-my.sharepoint.com%2Fpersonal%2Fjkaplan_unicef_org%2F_v", "source": "reliefweb", "subset": "annotate_aj_part2", "spans": [{"key": "reliefweb:000120:11:4:0", "start": 509, "end": 523, "surface": "Data from 2018", "probe_tag": "confusion", "probe_score": 0.5009, "luna_label": 0, "luna_reason": "Bare date-only qualifier lacks an identified data source."}]}, {"key": "aj2-164", "text": ". While some moved in groups, mostly as families, the crisis also left many families in need of reunification.\n\n###### **FIGURE 1**\n\n\n**Number of conflict-induced newly internally displaced people in Afghanistan, January - October 2021 (total)**\n\n\n300,000\n\n\n\n250,000\n\n\n200,000\n\n\n150,000\n\n\n100,000\n\n\n50,000\n\n\n0\n\n\n\n\n|Col1|Taliban takeover|\n|---|---|\n||Taliban takeover|\n|||\n|||\n|||\n|||\n|||\n\n\n\nJan Feb Mar Apr May Jun Jul Aug\n\n\n[Source: UN OCHA records, available from: www.humanitarianresponse.info/en/operations/afghanistan/idps . Last reported displacement up to 19 October 2021.](http://www.humanitarianresponse.info/en/operations/afghanistan/idps)\n\n\n\nSep Oct\n\n\n\nData for 2021 indicate that women make up roughly 21 per cent of internally displaced people, as do men. Children make up the\nremaining 58 per cent (figure 2). A look at the family composition of those that fled to other countries, however, reveals gender differences (figure 3). Neighboring countries such as Pakistan, Iran and, to a much lesser degree other Refugee Response Plan Countries\nsuch as Tajikistan, Turkmenistan and Uzbekistan, are key destination countries for Afghans seeking international protection. Prior to\n2021, there were more than 2 million <sup>1</sup> Afghan refugees registered in those countries, of which more than 64 per cent were in Pakistan\nand 35 per cent were in Iran. With the 2021 crisis, however, it is expected that the number of Afghans in need of international protection has increased in these and other countries. During 2021, women and girls made up an estimated 46 per cent of the almost 80\nthousand <sup>2</sup>", "source": "reliefweb", "subset": "annotate_aj_part2", "spans": [{"key": "reliefweb:001491:0:1:1", "start": 664, "end": 677, "surface": "Data for 2021", "probe_tag": "confusion", "probe_score": 0.2133, "luna_label": 0, "luna_reason": "Bare date-only qualifier names no identifiable data source."}]}, {"key": "aj2-165", "text": "**RESUME DU Q&A :** Des questions ont été abordées concernant l’impact du cash voucher sur l’économie\nlocale et sur l’intérêt des commerçants à stabiliser le prix des denrées malgré les fluctuations. En\nréponse à ces deux aspects, le PAM a souligné l’encrage local du projet. Les commerçants accrédités\nsont des locaux basés dans le marché de Mangaize s’approvisionnant à Niamey. De plus, les profits issus\ndu projet contribuent au développement de la communauté à hauteur de 65 millions CFA injectées\ndans l’économie locale par mois. Par rapport à la stabilisation des prix, les commerçants ont la capacité\nd’effectuer des stocks de 3 mois et donc de garder les mêmes prix, même en période de fluctuations.\n\n**PRESENTATION : Résultats de l’évaluation à mi-parcours** | _Allison Osterman, PAM Niger et_\n_Kokoévi Sossouvi, UNHCR Niger_\nEn aout et septembre 2013, le PAM et l’UNHCR ont conduit conjointement une évaluation du projet\ncash voucher auprès de 396 entretiens ménages (dont 213 ménages déjà enquêtés en Janvier 2013),\npour le PAM et 99 entretiens ménages et 11 focus groupes avec les parties prenantes pour l’UNHCR.\n\nLes conclusions principales de l’évaluation sont :\n\n Les indicateurs de la sécurité alimentaire des réfugiés se sont améliorés par rapport à la\n\nsituation de Janvier 2013 ;\n Les vouchers", "source": "reliefweb", "subset": "annotate_aj_part2", "spans": [{"key": "reliefweb:001521:4:0:0", "start": 954, "end": 976, "surface": "396 entretiens ménages", "probe_tag": "confusion", "probe_score": 0.5151, "luna_label": 0, "luna_reason": "The sentence describes household interviews conducted for the evaluation."}, {"key": "reliefweb:001521:4:0:1", "start": 1042, "end": 1063, "surface": "99 entretiens ménages", "probe_tag": "confusion", "probe_score": 0.6002, "luna_label": 1, "luna_reason": "Past household interviews supported the midterm evaluation’s reported findings."}]}, {"key": "aj2-166", "text": "eva York. 2011).\n13 OMS, _Adolescent pregnancy: unmet needs and undone deeds: a review of the literature and programmes_\n_(Ginebra. 2007)._ <u>[http://whqlibdoc.who.int/publications/2007/9789241595650_eng.pdf.](http://whqlibdoc.who.int/publications/2007/9789241595650_eng.pdf)</u>\n14 OMS, _Adolescent Pregnancy. Fact sheet N°364_, 2012.\n15 Ibíd.\n16 UNFPA, _State of the World Population 2012 By Choice, Not By Chance: Family Planning, Human Rights and_\n_Development (_ Nueva York: UNFPA, 2012).\n17 WHO, _Adolescent Pregnancy. Fact sheet N°364_, 2012.\n18 WHO, _Preventing early pregnancy and poor reproductive outcomes among adolescents in developing countries:_\n_what the evidence says_ . WHO/FWC/MCA/12.0 (Ginebra, 2011).\n<u>[http://whqlibdoc.who.int/hq/2012/WHO_FWC_MCA_12_02.pdf.](http://whqlibdoc.who.int/hq/2012/WHO_FWC_MCA_12_02.pdf)</u>\n19 Monica Akinyi Magadi, et al. “A comparative analysis of the use of maternal health services between teenagers\nand older mothers in sub-Saharan Africa: Evidence from Demographic and Health Surveys (DHS),” _Social Science &_\n_Medicine_ 64 (2006): 1311-1325.\n20 UNFPA, _State of the World Population 2012,_ 2012.\n21 UNFPA, _Marrying too Young, End Child Marriage", "source": "reliefweb", "subset": "annotate_aj_part2", "spans": [{"key": "reliefweb:000914:44:2:0", "start": 1012, "end": 1042, "surface": "Demographic and Health Surveys", "probe_tag": "confusion", "probe_score": 0.772, "luna_label": 1, "luna_reason": "Named surveys cited as evidence in the article title."}]}, {"key": "aj2-167", "text": " State by weighing specific statistical information from these policy areas. The\nstatistical information utilised covers the three years preceding the date on which the Fund is\nestablished, using the latest annual statistics produced by the European Commission (Eurostat).\n\nThe chapter presents a **simulated application of the proposed Asylum & Migration Fund distribution**\n**key**, using data for the three-years 2015-17 period, leading to several significant differences in the\ndistribution of funding across MS when compared to the current AMIF. These differences include a\nsubstantial increase for Germany (from 10.31% to 30.08%), and reduced allocations for 22 Member\nStates (the most substantial for Spain, Greece and Italy).\n\n**The distribution key does not assess Member State capacities and resources for the management of**\n**migration** . In the simulation of allocations using the 2015-17 data, Germany and France would\ntogether account for 43.4% of the total initial Asylum & Migration Fund allocations to Member States.\nBoth could, however, be argued to be significantly better positioned to meet migratory challenges\n\n\n1 The EC interim evaluation indicates that 78% (€5.4bn) of current AMIF resources were ultimately allocated to MS via shared\nmanagement ( _AMIF Interim Evaluation,_ p3)\n\n\nOCTOBER 2018  11", "source": "reliefweb", "subset": "annotate_aj_part2", "spans": [{"key": "reliefweb:001185:10:2:1", "start": 895, "end": 907, "surface": "2015-17 data", "probe_tag": "confusion", "probe_score": 0.8783, "luna_label": 1, "luna_reason": "Used to calculate simulated allocations and the 43.4% combined share."}]}, {"key": "aj2-168", "text": "**Acceptance Rates of UNHCR Submissions by**\n**Resettlement Countries in 2009**\n\n\nGlobal average acceptance rate <sup>1</sup> : 88.3%\n\n\n\nAcceptance rates of resettlement countries by\ntop ten country of origin\n\nCountry of origin submissions % accept.\n\n\n\n\n\nAcceptance rates of resettlement countries by\nUNHCR resettlement criteria\n\n\n\nResettlement criteria % accept.\n\n\n\n\n\n\n\n**53**\n\n\n\n\n\n\n\n\n\n1 _Acceptance rates are based on resettlement decisions reported by resettlement States to UNHCR field_\n_offices. A decline decision by resettlement country does not necessarily mean the case is ineligible for resettlement_\n_submission according to UNHCR policy. UNHCR may resubmit the case to another resettlement country._\n\n\nUNHCR Projected Global Resettlement Needs 2011", "source": "reliefweb", "subset": "annotate_aj_part2", "spans": [{"key": "reliefweb:000480:54:0:0", "start": 2, "end": 39, "surface": "Acceptance Rates of UNHCR Submissions", "probe_tag": "confusion", "probe_score": 0.2273, "luna_label": 0, "luna_reason": "Standalone table title, not an independently used data resource."}, {"key": "reliefweb:000480:54:0:1", "start": 714, "end": 760, "surface": "UNHCR Projected Global Resettlement Needs 2011", "probe_tag": "confusion", "probe_score": 0.1002, "luna_label": 1, "luna_reason": "Named UNHCR report cited alongside the acceptance-rate data table."}]}, {"key": "aj2-169", "text": "**_Table 1_** _– Reasons for not receiving care for chronic diseases_ management amongst Syrians.\n\n**Reproductive health** coverage has maintained at 100% of deliveries in\n### Zaatari and Azraq in 2018 attended by a skilled attendant. However, Reproductive\n\nboth complete antenatal care coverage (at least four visits) and tetanus\n### toxoid coverage need improvement. The proportion of deliveries in girls Health\n\nunder the age of 18 was 11.1 % for 2018, which represents an increase **ـــــــــــــــــــــــــــــــــــــــــــــــــــــــ**\ncompared to the average for 2017 of 10%. Girls under 18 are more likely - **100% of deliveries in**\nto experience obstetric and neonatal complications. A cross sectional **Zaatari and Azraq in 2018**\nhealth survey was conducted among Syrian refugees living in Jordan, to **attended by a skilled**\nassess refugee access and utilization of key health services. Key findings **attendant**\n\n                                                      - **Amongst non-camp**\n\nhighlighted that 51% of household members were female and 17% of the\n\n**refugees 100% delivered**\n\nwomen were pregnant in the last two years, compared to only 15% in\n\n**in a health facility, of**\n\n2017; women had difficulty accessing ANC services. UNFPA reproductive\n\n**which 46% were in a**\n\nhealth needs assessment survey in Zaatari recommended continuation\n\n**private facility**\n\nof community outreach activities with an emphasis on family planning\n\n                                                      - **Deliveries in girls under**\n\nprogramming and improving health care seeking behavior to address\n\n**18 years old has**\n\nreproductive", "source": "reliefweb", "subset": "annotate_aj_part2", "spans": [{"key": "reliefweb:001452:5:0:0", "start": 1303, "end": 1344, "surface": "health needs assessment survey in Zaatari", "probe_tag": "confusion", "probe_score": 0.4274, "luna_label": 1, "luna_reason": "Existing survey informed recommendations on community outreach and family planning."}]}, {"key": "aj2-170", "text": " LA Rios Rivera, I Sarr, P Waita, and K Yoshimura.\n2021a. “Monitoring Social and Economic Impacts of COVID-19 on Refugees in Uganda:\nResults from the High-Frequency Phone Survey - First Round”. Washington, D.C.: World\nBank Group.\n\n\nAtamanov, A, N Yoshida, C Alemi, T Beltramo, J Ilukor, LA Rios Rivera, I Sarr, A Hamud\nSaid, P Waita, and K Yoshimura. 2021b. “Monitoring Social and Economic Impacts of\nCOVID-19 on Refugees in Uganda: Results from the High-Frequency Phone Survey –\nSecond Round”. Washington, D.C.: World Bank Group.\n\n\nAtamanov, A, N Yoshida, C Alemi, T Beltramo, J Ilukor, LA Rios Rivera, I Sarr, A Hamud\nSaid, P Waita, and K Yoshimura. 2021c. “Monitoring Social and Economic Impacts of\nCOVID-19 on Refugees in Uganda: Results from the High-Frequency Phone Survey – Third\nRound”. Washington, D.C.: World Bank Group.\n\n\nAtamanov, A., Beltramo, T., Reese, B. C., Rios Rivera, L.A., and Waita, P. 2021d. One\nYear in the Pandemic: Results from the High-Frequency Phone Surveys for Refugees in\nUganda (English). Washington, D.C.: World Bank Group.\n\n\nCefalà, L, M Gechter, N Tsivanidis, and N Young. 2020. “Economic impacts of COVID-19\nlockdowns: An examination of recoveries in Jordan.” IGC Policy Brief JOR-20081,\n\n\nDempster, H, T Ginn, J Graham, M Guerrero Ble, D Jayasinghe, and B Shorey. 2020", "source": "reliefweb", "subset": "annotate_aj_part2", "spans": [{"key": "reliefweb:000604:44:1:0", "start": 958, "end": 1009, "surface": "High-Frequency Phone Surveys for Refugees in\nUganda", "probe_tag": "confusion", "probe_score": 0.5271, "luna_label": 0, "luna_reason": "Named survey title appears within a bibliography reference entry."}]}, {"key": "aj2-171", "text": " using\n\nchildren in hostile situations. Indiscriminate bombardment\n\nand shelling have created mass civilian casualties and\n\nspread terror among civilians. Furthermore, parties have\n\nenforced sieges on towns, villages and neighbourhoods,\n\ntrapping civilians and depriving them of food, medical\n\ncare and other necessities. Parties to the conflict also have\n\ndisregarded the special protection accorded to hospitals,\n\nand medical and humanitarian personnel.\n\n\n3 For the latest data on Syrian refugees consult the Inter-agency Information\nSharing Portal, hosted by UNHCR at http://data.unhcr.org/syrianrefugees/\nregional.php. The latest data on IDPs within Syria is available at\nhttp://www.unocha.org/syria.\n\n\n\nIncreased levels of poverty, <sup>4</sup> [^4: In 2014, four out of every five Syrians lived in poverty. Governorates with\nintensive conflict, and that had higher historical rates of poverty, suffered\nmost. Almost two-thirds of the population (64.7 per cent) lived in extreme\npoverty: being unable to secure basic food and non-food items necessary\nfor the survival of the household. This was particularly acute in the conflict\nzones. Thirty per cent of the population fell into abject poverty: being unable\nto meet the basic food needs of their households. See Syrian Centre for Policy Research (SCPR), _Syria – Alienation and Violence: Impact of Syria Crisis_\n_Report 2014_] loss of livelihood, soaring\n\nunemployment, <sup>5</sup> [^5: Syria’s unemployment rate increased from 14.9 per cent in 2011 to 57.7\npercent by the end of 2014. Almost three million people have lost their jobs\nduring the conflict. See Syrian Centre for Policy Research (SCPR), _Syria –_\n_Alienation and Violence: Impact of Syria Crisis Report 2014_] and limited access to food, water,\n\nsanitation, housing, health care and education, have\n\nall had a devastating impact on the population. <sup>[29]</sup> The\n\nsituation is particularly dire for", "source": "reliefweb", "subset": "annotate_aj_part2", "spans": [{"key": "reliefweb:001389:11:1:0", "start": 475, "end": 498, "surface": "data on Syrian refugees", "probe_tag": "confusion", "probe_score": 0.5573, "luna_label": 0, "luna_reason": "Directs readers to consult data without presenting or analyzing a finding."}, {"key": "reliefweb:001389:11:1:1", "start": 634, "end": 659, "surface": "data on IDPs within Syria", "probe_tag": "confusion", "probe_score": 0.6453, "luna_label": 0, "luna_reason": "Only states where latest IDP data are available, without showing data use."}]}, {"key": "aj2-172", "text": "results show, more 12 to 24 year old girls and young\nwomen than boys and young men, as well as their older\ncounterparts in both refugee and host communities,\ntend to undergo significant challenges at the household\nlevel. This includes eating less preferred food, borrowing\nfood, relying on help from friends and relatives, limiting\n\n\n**<u>3.10 Priority Needs</u>**\n\n\n\nportion size at mealtimes, and sacrificing meals in order\nfor other family members to eat. Further research is\nneeded to fully comprehend the various vulnerabilities\nas well as the coping mechanisms of different groups\nof people in the refugee and host communities, and the\nimpact these have on their broader well-being.\n\n\n\n**_Our immediate priority is to have employment and livelihood opportunities for our male family_**\n**_members, our husbands and fathers (FGD, Rohingya Female Group). Our priority is to become self-_**\n## _“_\n**_reliant, to have control over our lives, and to look after our families (FGD, Rohingya Girls Group)._**\n\n\n**Refugee Community**\n\n\nIn order to identify key priorities for different groups in a comprehensive manner, women and men were given three sets\nof choice and asked to rank their top three priority needs from each choice. Refugee women who participated in the HH\nsurvey in this research ranked food (52%) first, then protection (19%), and followed by health care (10%) as their top three\npriorities among the first choice (Figure 29). The priority needs for women from the second choice included food (33%),\nhealth care (24%), and sanitation (12%) (Figure 30). The third choice included sanitation (21%), livelihoods (18%), and food\n(15%) (Figure 31). Broadly, refugee women’s priority needs included food, protection", "source": "reliefweb", "subset": "annotate_aj_part2", "spans": [{"key": "reliefweb:000732:52:0:0", "start": 1269, "end": 1278, "surface": "HH\nsurvey", "probe_tag": "confusion", "probe_score": 0.8225, "luna_label": 1, "luna_reason": "Survey findings directly support reported priority rankings and percentages."}]}, {"key": "aj2-173", "text": "**TCHAD** | Octobre 2023\n\n### **RÉSUMÉ**\n\n\nLe contexte humanitaire au Tchad a été largement\nimpacté par la crise liée au déplacement forcé à la suite\ndu conflit sociopolitique que connaît le Soudan,\nentrainant d’importants mouvements de population à\nl’intérieur du pays ainsi qu’au-delà de ses frontières. L’Est\ndu Tchad est confronté à une situation humanitaire\ncomplexe aux impacts à la fois d’ordre démographique et\nsocioéconomique. Il accueillait déjà environ 600,000\nréfugiés répartis dans quatre provinces et le plan de\nréponse humanitaire 2023 avait identifié 1,9M de\npersonnes vulnérables dans cette zone. A cette situation,\nles affrontements armés entre les Forces Armées\nSoudanaises et les Forces de Soutien Rapide, qui ont\ndébuté le 15 avril 2023, ont entrainé d’importants\nmouvements de population au Tchad, fragilisant ainsi les\nefforts de recherche de solutions engagés par le\ngouvernement et ses différents partenaires.\n\n\nLa nouvelle crise du Soudan est une crise de protection\net ses effets affectent directement des vies et davantage\ncelles des femmes, des enfants et des personnes\nprésentant des besoins spécifiques, aussi bien des\ncommunautés des réfugiés, des retournés que des\npopulations hôtes. Les nouveaux arrivants sont signalés\nau quotidien depuis le mois d’avril 2023. La capacité\nd’accueil reste limitée et l’accès aux services sociaux de\nbase difficile", "source": "reliefweb", "subset": "annotate_aj_part2", "spans": [{"key": "reliefweb:000417:1:0:0", "start": 518, "end": 550, "surface": "plan de\nréponse humanitaire 2023", "probe_tag": "confusion", "probe_score": 0.8513, "luna_label": 1, "luna_reason": "2023 humanitarian response plan identified 1.9 million vulnerable people."}]}, {"key": "aj2-174", "text": "Page 7 of 15 \n \nAdditional Data Sources:  \n \n• \nIDMC will be collecting data in Beledweyne for a comparative analysis of displaced and host \ncommunities, using language as a proxy. This data may be useful; however, note below the \nlimitations of language as a proxy. Data to be available in first quarter of 2021. \n• \nIOM LORI: the Protection Cluster provided inputs into the tool which includes questions on \naccess to services and whether specific population groups face any impediments. Data to be \navailable in first quarter of 2021. \n• \nThe Protection Cluster met with UNFPA in which UNFPA raised their intentions to carry out a \ncensus. The cluster should consider the value of including minority, ethnic, or clan data in the \ndemographic data.  \n• \nThe cluster should also discuss with the World Bank incorporation of indicators on access \nbarriers for minority populations in their data collection tools, such as the high frequency \nsurveys. \n• \nREACH Hard to Reach Assessments: based on discussions it may be possible for the cluster to get \nsettlement-based data, this could be useful for triangulation with SPMS. \n \nProxy Indicators Use and Reliability: \n \nGiven real and perceived protection concerns and sensitivities around collection of ethnic group or clan \naffiliation, some studies rely on the use of proxy indicators to identify minority groups; however, proxies \nfor have significant limitations. Proxies include language, area of origin (not pre-displacement are of origin), \nand to a lesser extent occupational group. From a review of community and household level data sets, \nproxies seem to be more reliable at the community level than at the household or individual level.  \n \nSignificant limitations unique to each of the proxy indicators are detailed below:  \n \nLanguage spoken:  \n \n• \nAt the Site Level: From the DSA data 16 sties of 48 (one third) with minority access issues (the \nmost concrete indicator on minority presence) reported that “Standard/Northern Somali” was \nthe only language used in the site. Of all sites identifying minorities in any of the multiple \nindicators,", "source": "reliefweb", "subset": "annotate_aj_part2", "spans": [{"key": "reliefweb:000445:6:0:1", "start": 1051, "end": 1072, "surface": "settlement-based data", "probe_tag": "confusion", "probe_score": 0.2415, "luna_label": 0, "luna_reason": "Potentially obtaining data is future and no existing finding is attached."}, {"key": "reliefweb:000445:6:0:2", "start": 1557, "end": 1596, "surface": "community and household level data sets", "probe_tag": "confusion", "probe_score": 0.2049, "luna_label": 1, "luna_reason": "Reviewed datasets support a concrete comparison of proxy reliability."}]}, {"key": "aj2-175", "text": "br>6,912<br>3<br>-<br>18,138<br>16,915<br>1,830<br>2,027<br>389<br>13,357<br>2<br>377<br>1<br>20<br>555|\n\n\n\n**40** UNHCR Global Trends 2011 UNHCR Global Trends 2011 **41**", "source": "reliefweb", "subset": "annotate_aj_part2", "spans": [{"key": "reliefweb:001077:20:7:1", "start": 115, "end": 139, "surface": "UNHCR Global Trends 2011", "probe_tag": "drop", "probe_score": 0.047, "luna_label": 0, "luna_reason": "Repeated page-header report title, with no shown data use or source citation."}]}, {"key": "aj2-176", "text": "**GROUPE 2 : FAIBLESSES**\n\n\n  - La non diversification des bailleurs pour le financement des activités de lutte antimines\n\n\n  - Contrainte de mobilité des bailleurs\n\n\n  - Insuffisance de financement\n\n\n  - Faible coordination entre le GTLAMH et le RRM\n\n\n  - Insuffisance de staff dédié à la lutte antimines\n\n\n  - Peu d’effet aux actions de plaidoyer\n\n\n  - Insuffisance de suivi des référencements\n\n\n  - Insuffisance de données désagrégées (Handicap)\n\n\n  - Insuffisance de support de communication IEC, de budget dédié pour les besoins spécifiques\n\n\n  - Lenteur dans le transfert des compétences aux acteurs étatiques\n\n\n  - Faibles implémentations du NEXUS\n\n\n**GROUPE 3 : OPPORTUNITÉS**\n\n\n  - Existence d’acteurs disponibles dans le monitoring de protection (Accès à l’information)\n\n\n  - Système amélioré de collecte et de gestion des données (IMSMA Core) en développement\n\n\n  - Acceptance de l’action humanitaire (activité LAMH) par les communautés (adhésion)\n\n\n  - Plus grande implication du Secrétariat permanent de la Commission Nationale de Lutte contre la\nProlifération des Armes légères et de Petit Calibre (SP- CNLPAL)\n\n\n  - Existence de médias comme les canaux d’information et de sensibilisation\n\n\n  - Intérêt du système éducatif aux activités LAMH\n\n\n  - Intérêt des ONG nationales à la LAMH\n\n\n  - Existence de mécanismes communautaires de protection contre les ALPC\n\n\n**GROUPE 4 : MENACES**\n\n\n*", "source": "reliefweb", "subset": "annotate_aj_part2", "spans": [{"key": "reliefweb:000862:6:0:0", "start": 842, "end": 852, "surface": "IMSMA Core", "probe_tag": "drop", "probe_score": 0.0288, "luna_label": 0, "luna_reason": "The data-management system is still being developed, not an existing data resource used."}]}, {"key": "aj2-177", "text": " weaving, embroidery and clothes-making.\n\n\nScarce and poorly paid livelihood opportunities\nwere often indicated as having prompted further\nmigration. In FGDs both in Kabul and Mazar,\nreturnees explained that several male youth,\nmarried and unmarried, in their community had\ndecided to return to Pakistan soon after return\nbecause of extremely limited job opportunities.\nOne male returnee in Kabul estimated that around\n60% of male youth had returned to Pakistan.\nOther FGD participants added that they had male\nrelatives who were currently in Pakistan but “were\ntrying to go to Iran and even Europe”. In parallel,\nthe great majority of returnees stated that they\nwere receiving regular remittances from relatives\nabroad, including males that had returned to\nPakistan. This phenomenon is also captured in the\nreturnee monitoring report of November 2017. Due\nto lack of livelihood opportunities, 8% of the sample\n\n\n\n15", "source": "reliefweb", "subset": "annotate_aj_part2", "spans": [{"key": "sample:reliefweb:000080:16:2:0", "start": 153, "end": 157, "surface": "FGDs", "probe_tag": "drop", "probe_score": 0.0001, "luna_label": 1, "luna_reason": null}, {"key": "sample:reliefweb:000080:16:2:1", "start": 808, "end": 834, "surface": "returnee monitoring report", "probe_tag": "confusion", "probe_score": 0.1948, "luna_label": 1, "luna_reason": null}]}, {"key": "aj2-178", "text": "### **Better use of disaggregated data**\n\nIn order to understand and respond appropriately to\npeople’s vulnerabilities, needs, capacities and ensure\naccess to life-saving services, humanitarian agencies\nneed to collect information based on sex and age. <sup>15</sup>\nWithout this data, they are unable to effectively\nunderstand and respond to the priorities of older men\nand women. However, the humanitarian system still\ndoes not age-disaggregate its data collection and\nanalysis across all stages of emergency response.\n\n\n**Case study: Myanmar**\n\nOn 2 May 2008, Myanmar was struck by Cyclone\nNargis. High winds, heavy rainfall and tidal surges\nkilled nearly 85,000 people, with roughly 54,000 people\nleft missing and a further 20,000 injured. The cyclone\naffected 2.4 million people – just under one third of\nthe estimated 7.35 million people living in the affected\ntownships. Of these, approximately 200,000 were\n55 years or older at the time of the disaster. <sup>16</sup>\n\nAs part of multi-agency and sector monitoring, from\nSeptember 2008 to August 2009 the Tripartite core\ngroup involving the Association of Southeast Asian\nNations (ASEAN), the United Nations (UN) and the\ngovernment of Myanmar carried out three reviews\nof sector responses to generate data to inform targeted\nassistance, determine future assessments and\naccelerate appropriate response and recovery\nactivities. <sup>17</sup>\n\nWithin the protection element of the review, the\nHelpAge ageing expert seconded to the Global\nProtection Cluster (see page 1) observed gaps in\ninformation gathering about older people. Working with\nprotection agencies, the expert helped to revise the\nmonitoring questions used in the review. This resulted\nin a more holistic analysis and inclusion of information\non older men and women. The new format included\nstandardising the definition of an older person as\nsomeone aged 60+, and disaggregating protection", "source": "reliefweb", "subset": "annotate_aj_part2", "spans": [{"key": "reliefweb:001104:5:0:0", "start": 20, "end": 38, "surface": "disaggregated data", "probe_tag": "drop", "probe_score": 0.0243, "luna_label": 0, "luna_reason": "Generic data concept is discussed, without an attributed finding or concrete analytical use."}]}, {"key": "aj2-179", "text": " self-reliance and human capital, a context-relevant, market-based approach is critical. At the\n\nend of a humanitarian program, skills will remain but without a market, the ‘livelihoods’ will stop. There is a\n\nprejudice that the private sector is only interested in profit and that humanitarian actors risk their principles by\n\nengaging with them, and a fear that engaging with more actors will further complicate coordination, however,\n\nthis does not have to be the case. Small, local businesses have lots of advantages compared to outsiders around\n\nmarket-based livelihoods, but these actors often have voice in the self-reliance conversation. We need to get\n\nbetter at engaging with them. To this end, the Humanitarian Private Sector Partnership Platform (HPPP) has been\n\ndeveloped. The HPPP fosters different forms of collaboration at different levels. Collaboration with development\n\nactors is also helpful in understanding market needs and sustainable opportunities. We need to map and\n\nengage the most relevant actors (including private and public sectors for specific initiatives); build on existing\n\ntechnological capacities, and build new rights-based approaches with longer term commitments.\n\n\nWe also need to work on building the evidence base; there is currently minimal evidence that displaced people\n\ncan be assets rather than burdens nor that self-reliant people are better placed to attain solutions. Most data on\n\nself-reliance does not contain a displacement component.\n\n\nTo harvest the potential of the CRRF, we must become much better at humanitarian diplomacy. In many\n\ncountries, the legal framework is unclear or non-existing, so advocacy on the lifting of legal barriers (right to\n\nwork, freedom of movement, etc.) is important. If self-reliance is to expand beyond niche markets and home\nbased initiatives to larger scale economic activities with global reach, engaging governments and businesses is\n\ncritical. As a humanitarian community we are not good at doing advocacy at the national level – national\n\nxenophobia is often much stronger than our advocacy. Within advocacy efforts,", "source": "reliefweb", "subset": "annotate_aj_part2", "spans": [{"key": "reliefweb:000146:36:1:0", "start": 1423, "end": 1445, "surface": "data on\n\nself-reliance", "probe_tag": "drop", "probe_score": 0.0429, "luna_label": 1, "luna_reason": "Existing data are characterized as lacking a displacement component."}]}, {"key": "aj2-180", "text": ">Men (51%)<br>Women (49%)|**Hosts**<br>(KIHBS<br>2015)<br>Men (52%)<br>Women (48%)|**Hosts**<br>(KIHBS<br>2015)<br>Men (52%)<br>Women (48%)|\n||Gender|Gender|Gender|Gender|Gender|Gender|Gender|\n||Age|Below 18:<br>71%<br>Above 64:<br>0.6%|Below 18:<br>61%<br>Above 64:<br>0.4%|Below 18: 60%<br>Above 64: 0.4%|Below 18:<br>45%<br>Above 64:<br>1.8%|Below 18: 32%<br>Above 64:<br>0.7%||\n||Dependency<br>ratio|1.9|1.2|1.4|0.6|0.4||\n||Women-<br>headed<br>households|66%|56%|47%|41%|32%|➢ Women and girls’ empowerment programmes in camps and urban<br>areas can help alleviate barriers to accessing socioeconomic<br>opportunities and build and maintain human capital.<br>➢ Financial inclusion programmes coupled with entrepreneurship skills,<br>business training and cash grants targeting women, especially those<br>with young dependents, can be a starting point to unlock refugee<br>women’s socioeconomic potential.|\n||Improved<br>housing|5%|3%|8%|82%|78%|➢ Scaling up permanent shelters in Kalobeyei with", "source": "reliefweb", "subset": "annotate_aj_part2", "spans": [{"key": "sample:reliefweb:000574:5:1:0", "start": 40, "end": 45, "surface": "KIHBS", "probe_tag": "drop", "probe_score": 0.0011, "luna_label": 1, "luna_reason": null}, {"key": "sample:reliefweb:000574:5:1:1", "start": 97, "end": 102, "surface": "KIHBS", "probe_tag": "drop", "probe_score": 0.0006, "luna_label": 1, "luna_reason": "Named household survey cited as the source for demographic figures."}]}, {"key": "aj2-181", "text": "research seminars**\n**and workshops**, both in Addis and in different parts of the country, to promote dialogue and discussion.\nAnother could be an **online portal** for refugee-related research, designed to make it easy to access and\nnavigate all the research that exists. Thought would need to be given as to how to embed this appropriately\nin Ethiopian institutions to increase the chances of this being a sustainable initiative.\n\n\nConsideration should also be given to developing a **centralised repository** for research data, in line with\nthe global initiative being carried out by the World Bank and UNHCR. If such data could be made more\navailable, this should reduce the need for duplication of effort and allow for greater triangulation of research.\nWhile privacy and data sharing considerations would need to be carefully considered to protect all parties,\nthis should not be an obstacle to developing an appropriate solution.\n\n\nIdeally, all of this work should sit within a **common framework** that both enables joint monitoring of effort\nand progress, and allows for flexibility. Such a framework should also encourage more joint evaluations and\nstudies to reduce overlapping efforts.\n\n\nThere is a need for all involved in research to reflect on the linkages and interdependencies that exist\nbetween the specific research work they are conducting and wider research on similar topics and the policy\nenvironment. By so doing, it could be possible to understand the specific issues at hand in a more **holistic**\n**manner** . The greater emphasis on area-based planning envisaged by the NCRRS suggests work that\nconsiders these linkages more fully will be increasingly important.\n\n\n\n11 12", "source": "reliefweb", "subset": "annotate_aj_part2", "spans": [{"key": "sample:reliefweb:001587:9:4:0", "start": 517, "end": 530, "surface": "research data", "probe_tag": "drop", "probe_score": 0.0335, "luna_label": 0, "luna_reason": "Proposed repository development is future data infrastructure, not existing data use."}]}, {"key": "aj2-182", "text": "#### **9.4 Average monthly temperatures 2015 – 2023**\n\nThe table presented below represents the maximum and minimum temperatures for each of\nthe specified locations. It tries to illustrates the temperature decrease observed during the\nmonth designated as the shelter cluster Cold winter period.\n\n\n23\n\n\n|Col1|Col2|JAN|FEB|MAR|APR|MAY|JUN|JUL|AUG|SEP|OCT|NOV|DEC|\n|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n||**Kiev**|-1|2|7|17|21|25|27|28|23|12|6|3|\n||**Kiev**|-8|-5|-1|5|9|14|15|15|11|3|0|-2|\n||**Odessa**|2|5|10|15|21|27|31|31|26|15|11|7|\n||**Odessa**|-5|-2|1|6|12|17|18|19|14|7|3|-1|\n||**Lviv**|0|4|8|15|20|24|26|28|22|12|7|4|\n||**Lviv**|-7|-3|-1|4|9|13|13|13|10|4|0|-2|\n||**Vinnytsia**|-1|3|8|16|21|24|26|27|23", "source": "reliefweb", "subset": "annotate_aj_part2", "spans": [{"key": "sample:reliefweb:000363:23:0:0", "start": 11, "end": 51, "surface": "Average monthly temperatures 2015 – 2023", "probe_tag": "drop", "probe_score": 0.0385, "luna_label": 0, "luna_reason": null}]}, {"key": "aj2-183", "text": " year\nbefore. This is the highest number since the early 70,000\n\n60,000\n\n1990s. By nationality, the main beneficiaries of the 50,000\nUNHCR-facilitated resettlement programmes in 2008 40,000\nwere refugees from Myanmar (23,200), Iraq (17,800), 30,000\nBhutan (8,100), Somalia (3,500), Burundi (3,100), and 20,000\n\n10,000\n\nthe Democratic Republic of the Congo (1,800). 0\n\n'92 '94 '96 '98 '00 '02 '04 '06 '08\n\nSome 85 UNHCR country offices were engaged in\nfacilitating resettlement during 2008. The largest number of refugees who were resettled with\nUNHCR assistance departed from Thailand (16,800), Nepal (8,200), the Syrian Arab Republic\n(7,300), Jordan (6,700), and Malaysia (5,900). These five UNHCR offices together accounted for\n7 out of every 10 resettlement departure assisted by the organization in 2008.\n\n<u>Local integration</u>\n\nThe degree and nature of local integration are difficult to measure in quantitative terms, though\nthis is the final and crucial step towards obtaining the full protection of the asylum country. In\nthose cases where refugees acquire the citizenship through naturalization, statistical data is often\nvery limited, as the countries concerned generally do not distinguish between refugees and others\nwho have been naturalized. Moreover, national laws in many countries do not permit refugees to\nbe naturalized. Therefore, the naturalization of refugees is both restricted and under-reported.\n\nThe limited data on naturalization of refugees available to UNHCR show that during the past\ndecade more than 1.1 million refugees were granted citizenship by their asylum country. The\nUnited States of America alone accounted for two thirds of them, even though their 2008\nnumbers are not yet available. Azerbaijan and Armenia also granted citizenship to a significant\nnumber of refugees during the same period", "source": "reliefweb", "subset": "annotate_aj_part2", "spans": [{"key": "sample:reliefweb:000784:11:1:0", "start": 1108, "end": 1124, "surface": "statistical data", "probe_tag": "drop", "probe_score": 0.0411, "luna_label": 0, "luna_reason": null}, {"key": "sample:reliefweb:000784:11:1:1", "start": 1437, "end": 1471, "surface": "data on naturalization of refugees", "probe_tag": "confusion", "probe_score": 0.1559, "luna_label": 1, "luna_reason": null}]}, {"key": "aj2-184", "text": "944\n116’311\n-4%\n 16.1 \n 16.4 \n 16.3 \nTotal\n368,085\n347,131\n715,216\n 100.0 \n 100.0 \n 100.0 \n* Figures include Kosovo.\nOrigin of asylum applications lodged in 44 industrialized countries | 2009 and 2010\nCovering all 44 countries which provided monthly data to UNHCR.\nAll data are provisional and subject to change.\nTable 3", "source": "reliefweb", "subset": "annotate_aj_part2", "spans": [{"key": "reliefweb:000381:16:3:0", "start": 242, "end": 254, "surface": "monthly data", "probe_tag": "drop", "probe_score": 0.0475, "luna_label": 1, "luna_reason": "Existing monthly data provided to UNHCR underlies the reported table coverage."}]}, {"key": "aj2-185", "text": "br>51<br>950<br>2,910<br>32<br>2,416<br>-<br>37<br>45<br>1,107<br>4,596<br>502<br>101<br>7,468<br>-<br>847<br>6,012<br>1<br>4,052<br>367<br>16,760<br>23,981<br>9<br>509<br>40<br>475<br>40<br>519<br>745<br>1,509<br>3<br>121<br>1,559<br>23<br>152<br>1,354<br>164<br>1,953<br>1,505<br>-<br>120<br>1<br>18<br>2,829<br>121<br>2<br>397<br>-|\n\n\n\n**42** UNHCR Global Trends 2011 UNHCR Global Trends 2011 **43**", "source": "reliefweb", "subset": "annotate_aj_part2", "spans": [{"key": "reliefweb:001077:21:10:1", "start": 346, "end": 370, "surface": "UNHCR Global Trends 2011", "probe_tag": "drop", "probe_score": 0.0327, "luna_label": 0, "luna_reason": "Standalone report title in page header, with no shown citation or data use."}]}, {"key": "aj2-186", "text": " forced family separation,\ndestruction of property, forced evictions, lack of access to justice,\ndiscriminatory practices against persons with minority clan\naffiliations, and concerns regarding the protection of civilians.\n\n**<u>Methodology</u>**\n\nThis report was prepared through a desk review of various sources,\nmost notably, the protection monitoring systems in Somalia,\nincluding: the Somalia Protection Monitoring System (SPMS), the\nProtection and Return Monitoring Network (PRMN) and the\nEviction tracker.\n\n**<u>Limitations</u>**\n\nData available in Somalia is limited to areas that are accessible by\nhumanitarian actors. Those that are not accessible are under the\ncontrol of Al-Shabaab <sup>3</sup> [^3: “Al-Shabaab has engaged in acts that directly or indirectly threaten\nthe peace, security, or stability of Somalia, including but not limited to] . A limited data set is collected from\nindividuals that flee Al-Shabaab controlled territories by REACH,\ntitled ‘Hard-to-Reach’ data. The information in this report was\ncollected using existing reports and data collection methodologies.\n\n\nacts that threaten the Djibouti Agreement of August 18, 2008, or the political process; and\nacts that threaten the Transitional Federal Institutions (TFIs), the African Union Mission\nin Somalia (AMISOM), or other international peacekeeping operations related to Somalia.\nAl-Shabaab has also obstructed the delivery of humanitarian assistance to Somalia, or\naccess to, or distribution of, humanitarian assistance in Somalia.”\n[https://www.un.org/securitycouncil/sanctions/751/materials/summaries/entity/al-](https://www.un.org/securitycouncil/sanctions/751/materials/summaries/entity/al-shabaab)\n[shabaab](https://www.un.org/securitycouncil/sanctions/751/materials/summaries/entity/al-shabaab)", "source": "reliefweb", "subset": "annotate_aj_part2", "spans": [{"key": "sample:reliefweb:000833:2:1:0", "start": 390, "end": 426, "surface": "Somalia Protection Monitoring System", "probe_tag": "drop", "probe_score": 0.0285, "luna_label": 1, "luna_reason": null}, {"key": "sample:reliefweb:000833:2:1:1", "start": 495, "end": 511, "surface": "Eviction tracker", "probe_tag": "confusion", "probe_score": 0.0654, "luna_label": 1, "luna_reason": null}]}, {"key": "aj2-187", "text": " At least 30% of general\npublic aware of NSAP                  - Public opinion survey\nprogram and results.\n\n\n**3(c)** **Performance** **of** 3c.1 M&E reports used for - NaCSA M&E data - NaCSA maintains lean and\n**community** **sub-projects and** decision-making by NaCSA; efficient organizational\n**NSAP** **partners monitored** structure\n**and evaluated** **in order to**\n**improve** **program**\n**effectiveness.**\n\n\n**3(d)** **Technical** **Assistance** 3d. 1 NaCSA staff indicate - IDA aide-memoires and\n**services** **effectively** **provided** satisfaction with technical project status reports\n**to support program** assistance, including skill\n**implementation** transfer activities\n\n\n**3(e)** NaCSA **management** 3e. 1 Project management - IDA Project Status reports\n**systems** **functioning** costs (NaCSA staff salaries at (including disbursement\n**effectively** **to ensure** all levels as well as operating reports);\n**program success** expenditures) are 13.5% or - NaCSA proposed annual\nless than total budgeted annual work program and budget\nexpenditures;                 - Annual audit reports;\n3e.2 NaCSA staff and                  - GOSL semi-annual PETS\npartners indicate satisfaction reports\nwith the performance of\nNaCSA's management;\n3e.3 NaCSA performance in\n\n\n                                  - 27", "source": "refugee_pads", "subset": "annotate_aj_part2", "spans": [{"key": "refugee_pads:000129:31:1:0", "start": 170, "end": 184, "surface": "NaCSA M&E data", "probe_tag": "confusion", "probe_score": 0.149, "luna_label": 0, "luna_reason": "Names project monitoring data without an attributed finding or substantive data use."}]}, {"key": "aj2-188", "text": "**The World Bank**\nChad Energy Access Scale Up Project (P174495)\n\n\n\n\n\n\n\n|Col1|Col2|Col3|reports of<br>PIU|Col5|Col6|\n|---|---|---|---|---|---|\n|People provided with access to clean<br>cooking, out of which||Quarterly<br>|<br>Reports of<br>verification<br>agents,<br>progress<br>report of PIU<br> <br>|Data provided by PIU<br>and verified by an<br>independent<br>verification agent<br>|PIU of the Ministry of<br>Petroleum and Energy<br>|\n|Refugees||Quarterly<br>|<br>Reports of<br>verification<br>agents,<br>progress<br>report of PIU<br> <br>|Data provided by PIU<br>and verified by an<br>independent<br>verification agent<br>|PIU of the Ministry of<br>Petroleum and Energy<br>|\n|Host communities<br> <br>||Quarterly<br>|<br>Reports of<br>verification<br>agents,<br>progress<br>report of PIU<br>|Data provided by PIU<br>and verified by an<br>independent<br>verification agent<br>|PIU of the Ministry of<br>Petroleum and Energy<br>|\n\n\n|Monitoring & Evaluation Plan: Intermediate Results Indicators|Col2|Col3|Col4|Col5|Col6|\n|---|---|--", "source": "jdc_operational", "subset": "annotate_aj_part2", "spans": [{"key": "jdc_operational:000051:58:0:0", "start": 301, "end": 321, "surface": "Data provided by PIU", "probe_tag": "confusion", "probe_score": 0.1367, "luna_label": 0, "luna_reason": "Standalone project monitoring table cell, not an independent data resource."}]}, {"key": "aj2-189", "text": "**1. Project Context, Development Objectives and Design**\n\n1. Ethiopia is one of the most populous countries in Sub-Saharan Africa and also\none of the poorest. When this project was being prepared, Ethiopia’s per capita gross\nnational income (GNI) was at US$160, significantly less than the Sub-Saharan Africa\naverage of $765.3 <sup>1</sup> [^1: GNI per capita, Atlas Method (current US$) was $160 for Ethiopia in 2005 compared to 765.3 for Sub-Saharan\nAfrica (developing only). Source: World Development Indicators.] . Although the country had abundant resources and good potential\nfor development, poverty was pandemic and often linked to environmental and natural\nresource degradation. Approximately 44 percent of the population fell below the basic\nneeds poverty line in the comprehensive national survey (1999/00).\n\n2. During the decade preceding the project, the Government of Ethiopia (GoE)\nwas implementing a reform program aimed at poverty reduction through rapid\neconomic growth and macroeconomic stability. The program was making good\nprogress in poverty reduction in the 1990s, but was interrupted by the conflict with\nEritrea. The GoE resumed its efforts following the conclusion of the conflict by\ndeveloping the Sustainable Development and Poverty Reduction Program (SDPRP) in\n2002. Despite exogenous shocks, such as the drought in 2002-2003, implementation\nof the SDPRP resulted in important gains, especially on human development\nindicators, transport, the investment climate, small town development, and food\nsecurity. Pro-poor spending as a share of the budget rose from 28 percent in\n1999/2000 to 57 percent in 2004/05. The World Bank Country Economic\nMemorandum 2006 (CEM) on Growth and Governance found that important progress\nhad been achieved, largely driven by improved institutions, including at regional and\nlocal levels, which were able to deliver required services and infrastructure.\n\n3. In 2006, the GoE launched an ambitious new poverty reduction strategy,\ncalled the Plan for Accelerated and Sustained Development to End", "source": "fcv_pads_east_africa", "subset": "annotate_aj_part2", "spans": [{"key": "fcv_pads_east_africa:009846:13:0:0", "start": 779, "end": 808, "surface": "comprehensive national survey", "probe_tag": "confusion", "probe_score": 0.7245, "luna_label": 1, "luna_reason": "Survey supports the reported 44 percent poverty finding."}]}, {"key": "aj2-190", "text": "**Table S16. Relationship between the Economic Complexity Index and ODIN, Open Data**\n**Barometer, and Global Data Barometer scores, 2013-2022**\n\n\n\n<u>ODIN -</u> <u>ODIN -</u> <u>ODIN -</u> <u>ODB -</u> <u>ODB -</u> <u>ODB -</u> <u>GDB -</u>\n<u>Model 1</u> <u>Model 2</u> <u>Model 3</u> <u>Model 1</u> <u>Model 2</u> <u>Model 3</u> <u>Model 1</u>\n\n<u><mark>ODIN Score</mark></u> <u><mark>0.036***</mark></u> <u><mark>0.002*</mark></u> <u><mark>0.002</mark></u>\n<mark>(0.00)</mark> <mark>(0.00)</mark> <mark>(0.00)</mark>\nOpen Data Barometer\n0.028*** 0.000 0.000\nScore\n\n<mark>(0.00)</mark> <mark>(0.00)</mark> <mark>(0.00)</mark>\nGlobal Data Barometer\n0.035***\nScore\n\n\n\n<u>ODIN -</u>\n<u>Model 1</u>\n\n\n\n<u>ODIN -</u>\n<u>Model 2</u>\n\n\n\n<u>ODIN -<", "source": "general_prwp", "subset": "annotate_aj_part2", "spans": [{"key": "prwp:001471:66:0:0", "start": 103, "end": 124, "surface": "Global Data Barometer", "probe_tag": "confusion", "probe_score": 0.8317, "luna_label": 0, "luna_reason": "Standalone table title fragment naming an indicator series."}]}, {"key": "aj2-191", "text": "##### FEMALE-HEADED HOUSEHOLDS ON THE RISE\n\nThere has been a high prevalence of single females heading their households within areas in the North East most\n\naffected by the conflict. The UNHCR Vulnerability Screening (December 2017) found that 63% of vulnerable households\nwere female-headed. The breakdown of the 62,113 female-headed households (FHH) screened included 2,283 women\n\nreporting to have been widowed, 1,589 reporting to be lactating and 405 reporting to be pregnant. <sup>1</sup> [^1: UNHCR North East Nigeria: Vulnerability Screening Report (December 2017), available at:\n<u>[https://reliefweb.int/report/nigeria/unhcr-north-east-nigeria-operational-vulnerability-screening-report-december-2017](https://reliefweb.int/report/nigeria/unhcr-north-east-nigeria-operational-vulnerability-screening-report-december-2017)</u>] The highest numbers\nof FHH identified in the Vulnerability Screening were in Dikwa LGA (14,142), Ngala LGA (9,520), Monguno LGA (8,537)\n\nand Damasak, Mobbar LGA (5,578) in Borno State and Gulani LGA (5,458) in Yobe State.\n\n\nIn 2018, with every new arrival of IDPs, IDP returnees and refugee returnees, protection monitors have noted high\n\nnumbers of female-headed households.\n\n##### THEMATIC REPORT METHODOLOGY\n\n\nThis thematic report analyses information gathered by UNHCR protection monitors through numerous focus group\ndiscussions with females heading their households throughout May and June 2018 in sites in which UNHCR is\n\nconducting protection monitoring. This includes interviews with 1,722 females heading their households to provide\n\ndisaggregated data analyzed in the report. This report seeks to identify particular protection issues affecting women\nheading their households to enable evidence-based programming and response.\n\n\n1 UNHCR North East Nigeria: Vulnerability Screening Report (December 2017), available at:\n<u>[https://reliefweb.int/report/nigeria/unhcr-north-east-nigeria-operational-vulnerability-screening-report-december-2017](https://reliefweb.int/report/nigeria/unhcr-north-east-nigeria-operational-vulnerability-screening", "source": "reliefweb", "subset": "annotate_aj_part2", "spans": [{"key": "reliefweb:000488:0:0:1", "start": 1580, "end": 1598, "surface": "disaggregated data", "probe_tag": "confusion", "probe_score": 0.482, "luna_label": 0, "luna_reason": "The report's own interviews generated the disaggregated data."}]}, {"key": "aj2-192", "text": " of linking information on students with population register\ndata and financing data of the Ministry of Finance (MoF) is currently lacking. The current EMIS and\nestablished data reporting practices provide a solid foundation for the development of an integrated EMIS\n\n\n22 Under support of the completed World Bank-financed Moldova Education Reform Project.\n\n\nPage 8 of 68", "source": "refugee_pads", "subset": "annotate_aj_part2", "spans": [{"key": "refugee_pads:000185:17:2:0", "start": 70, "end": 84, "surface": "financing data", "probe_tag": "confusion", "probe_score": 0.2769, "luna_label": 0, "luna_reason": "States financing data is lacking without using it for analysis or estimates."}]}, {"key": "aj2-193", "text": " risks\nand opportunities for actions that strengthen labor standards. Compliance with ILO and Jordanian labor and\nenvironmental standards varies across sectors, companies, and SEZs.\n\n\n11. Transparent reporting will be achieved through the publication of factory-level compliance\ninformation on selected issues assessed by “Better Work”. As part of public reporting, garment factories\nare identified by name along with their compliance findings, and the information is made public on the\nBetter Work website.\n\n\n12. Experience in other Better Work countries has shown that public reporting on compliance can\naccelerate change toward a more responsible and competitive garment industry. Specifically, experience\nshows that public reporting facilitates the following:\n\n\n(a) Raises the compliance levels across the sector. Research on Better Factories Cambodia has\n\nshown that transparent reporting significantly lowered the probability of noncompliance.\n\n\n(b) Helps high-compliance factories distinguish themselves from those with a weaker compliance\n\ncommitment.\n\n\n26", "source": "jdc_operational", "subset": "annotate_aj_part2", "spans": [{"key": "jdc_operational:000045:34:1:0", "start": 254, "end": 290, "surface": "factory-level compliance\ninformation", "probe_tag": "confusion", "probe_score": 0.1554, "luna_label": 1, "luna_reason": "Existing Better Work compliance findings are used for factory-level public reporting."}]}, {"key": "aj2-194", "text": "PED,<br>MoLG<br>|Guidance for establishment ad functioning of grievance redress in LGs including:<br>- A grievance handling system<br>- Grievance Redress committees to handle grievances and disputes at each LG and at implementing<br>agencies (MoES, MoH, MAAIF and MWE and co-opting MoFPED, PPDA, MoPS and MoGLSD as may<br>be required) in line with Public Service Negotiating, Consultative, and Dispute Settlement Machinery.<br>- Functional Grievance Redress Committees in place and communities aware of the GRM mechanisms.<br>- Establishing a complaints log with clear information and reference for onward action (a clear complaints<br>referral path); in addition, all contractors will be required to a workers’ complaints mechanism at the Site;|\n\n\n48", "source": "fcv_pads_east_africa", "subset": "annotate_aj_part2", "spans": [{"key": "fcv_pads_east_africa:012399:48:2:0", "start": 543, "end": 557, "surface": "complaints log", "probe_tag": "confusion", "probe_score": 0.1531, "luna_label": 0, "luna_reason": "The project is establishing the complaints log as a future grievance mechanism."}]}, {"key": "aj2-195", "text": "March 1, 2015, March 17, 2015, and April 2, 2015. There is no evidence of smoke on March\n\n\n1 image. Smoke plumes from the three oil production sites are visible in the March 17, 2015\n\n\nimage and portions of the sites display smoke on April 2. Large-scale smoke, evidence of\n\n\nfighting, is visible over the area on 18 April 2015 Landsat.\n\n\nTable A.4: Ajil field\n\n\n**<u>Dates Removed</u>** **<u>Temperature (K)</u>**\n<u>March 5, 2015</u> <u>1356</u>\n<u>March 6, 2015</u> <u>1297</u>\n<u>March 7, 2015</u> <u>1350</u>\n\n\nFirst, Ajil is situated northeast of Tikrit near the Hamrin Mountains in Iraq. Daesh took\n\n\ncontrol of the field in June 2014 and continued production without interruption until January\n\n\n2015. The field was set on fire by the group to counter an attack by Iraqi forces in starting\n\n\nMarch 5, 2015 [9] and Daesh ceded control of the site on March 8, 2015. Fires reportedly\n\n\ncontinued for a few weeks as Iraqi engineers worked to put the site back to production and data\n\n\ncorroborate this activity at the site: temperature observations after Daesh lost control generally\n\n\nremain below 1400 degrees K until 19th March 2015.\n\n\nTable A.5: Hamrin area 1\n\n\n**<u>Dates Removed</u>** **<u>Temperature (K)</u>**\n<u>March 5, 2015</u> <u>1270</u>\n<u>March 6, 2015</u> <u>1282</u>\n\n\nSecond, we reached similar conclusions for nearby Hamrin sites. Like Aj", "source": "general_prwp", "subset": "annotate_aj_part2", "spans": [{"key": "prwp:007190:36:0:0", "start": 1028, "end": 1052, "surface": "temperature observations", "probe_tag": "confusion", "probe_score": 0.7995, "luna_label": 1, "luna_reason": "Temperature observations support a concrete finding about post-fire site conditions."}]}, {"key": "aj2-196", "text": "|Theme|Sub-­Theme|QUESTIONS FOR THE HOUSEHOLD SURVEY|Col4|Col5|Col6|\n|---|---|---|---|---|---|\n|Theme|Sub-Theme|#|Questions|Answer options|Responding<br>population|\n|Migration history and future plans (cont.)||I12|[If yes] why did this person(s) move?|1. Better employment opportunities<br>2. Availability/better quality of education opportunities<br>3. Availability/better quality of health services<br>4. Availability of humanitarian assistance<br>5. To join other family members<br>6. Relatives/friends are also there<br>7. Marriage<br>8. Cost of living/ rent is lower<br>9. Location there is safer<br>10. Bigger/better home there<br>11. Do not feel comfortable here/experience discrimination/hostility<br>12. Has land and/or house there<br>13. Other|All<br>With moved<br>members within last<br>12 months|\n|Migration history and future plans (cont.)|Future<br>plans|I13|Does anyone in your household have<br>firm plans to change (permanent)<br>residence from your current location<br>within the next six months? [For all<br>households]|1. Yes<br>2. No|All|\n|Migration history and future plans (cont.)|Future<br>plans|I14|[If yes] Where are you/other household<br>members planning to go? [if more<br>members are moving to different places,<", "source": "reliefweb", "subset": "annotate_aj_part2", "spans": [{"key": "reliefweb:001035:70:0:0", "start": 36, "end": 52, "surface": "HOUSEHOLD SURVEY", "probe_tag": "confusion", "probe_score": 0.5433, "luna_label": 0, "luna_reason": "Standalone table header naming a survey instrument, not cited data use."}]}, {"key": "aj2-197", "text": " necessary knowledge and\ncapacity to make better decisions on WASH and nutrition practices and ECD support, thereby improving household\nwelfare and contributing to their and their children’s human capital development. Third, the SNSOP will contribute to\nachieving gender parity by ensuring meaningful female participation in local community structures established by the\nproject. Specifically, all community structures must have at least 45 percent female participations which will lead to\npromoting women’s voices and agency in community. Indeed, community structures will play a key role in\ncommunications and awareness raising on gender issues, which is why active female participation will be essential. Lastly,\nin addition to the Results Indicators (Beneficiaries of social safety net programs – Female; Number of beneficiaries\nreceiving cash for performing labor intensive public works who are female; Number of beneficiary households receiving\nDirect Income Support who have a female primary beneficiary; Number of beneficiaries receiving Economic\nOpportunities who are female youth; Increased participation by women in community level governance and coordination\nstructures), all M&E activities will employ gender-disaggregated data to monitor the participation and performance of\nfemale beneficiaries. Finally, Component 2 will support female youth to support them with livelihood and income\ngenerating activities and help empower them economically.\n\n84. **Gender Based Violence.** The SNSOP will conduct due diligence to mitigate GBV-related risks due to project\nactivities, <sup>40</sup> and identify activities throughout the project cycle that can be leveraged to increase awareness and\nencourage behavior change on gender issues and GBV, building on current efforts. <sup>41</sup> This will include awareness raising\nduring project activities, such as community engagement and cash payments, and employing a gender lens in the\ndevelopment and implementation of all project activities. Behavioral change communication provided to beneficiaries\n\n\n39 Studies on the impact of social interventions focused on nutrition, ECD and WASH targeted at mothers and caregivers show improvements in\ndietary diversity and reduced stunting among children.", "source": "refugee_pads", "subset": "annotate_aj_part2", "spans": [{"key": "refugee_pads:000153:42:1:0", "start": 1215, "end": 1240, "surface": "gender-disaggregated data", "probe_tag": "confusion", "probe_score": 0.2371, "luna_label": 0, "luna_reason": "Planned M&E use of data, with no existing dataset or finding cited."}]}, {"key": "aj2-198", "text": " NPTP|Component 1: Administration of the NPTP|Component 1: Administration of the NPTP|Component 1: Administration of the NPTP|Component 1: Administration of the NPTP|Component 1: Administration of the NPTP|3.89|3.89|3.89|3.89|3.89|\n|Component 2: Provision of Social Assistance|Component 2: Provision of Social Assistance|Component 2: Provision of Social Assistance|Component 2: Provision of Social Assistance|Component 2: Provision of Social Assistance|Component 2: Provision of Social Assistance|Component 2: Provision of Social Assistance|Component 2: Provision of Social Assistance|Component 2: Provision of Social Assistance|Component 2: Provision of Social Assistance|Component 2: Provision of Social Assistance|3.76|3.76|3.76|3.76|3.76|\n|Component 3: Fiduciary Operations Team|Component 3: Fiduciary Operations Team|Component 3: Fiduciary Operations Team|Component 3: Fiduciary Operations Team|Component 3: Fiduciary Operations Team|Component 3: Fiduciary Operations Team|Component 3: Fiduciary Operations Team|Component 3: Fiduciary Operations Team|Component 3: Fiduciary Operations Team|Component 3: Fiduciary Operations Team|Component 3: Fiduciary Operations Team|0.55|0.55|0.55|0.55|0.55|\n|. <br>**Institutional Data**|. <br>**Institutional Data**|. <br>**Institutional Data**|. <br>**Institutional Data**|. <br>**Institutional Data**|. <br>**Institutional Data**|. <br>**Institutional Data**|. <br>**Institutional Data**|. <br>**Institutional Data**|", "source": "jdc_operational", "subset": "annotate_aj_part2", "spans": [{"key": "sample:jdc_operational:000047:6:13:0", "start": 1208, "end": 1226, "surface": "Institutional Data", "probe_tag": "confusion", "probe_score": 0.2474, "luna_label": 0, "luna_reason": "Standalone table heading, not a cited or analyzed data resource."}]}, {"key": "aj2-199", "text": "Annex 1\nPage 3 **of** 3\n\n\n**Key Performance**\n**Hierarchy of Objectives** **Indicators** **Monitoring &** **Critical Assumptions**\n**Evaluation**\n**Project Components / Sub-** **Inputs: (budget for each** **Project reports:** **(from Components to**\n**components:** **component)** **Outputs)**\n\n\nImprove Access: provision of US$5.8 million MOE monitoring Capacity within the\nclassrooms. Number of schools reports construction sector to handle\nconstructed per year; the volume of school\nimproved design and construction.\nefficiency.\nCreate Conditions for Quality US$1.1 million School surveys; student Good textbook distribution;\nImprovement: access to Number of textbooks per learning achievement management training\neducational materials; student; autonomous school reports (MOE effectiveness; Government\nimproved school management; salaries paid on monitoring reports). commitment to paying\nmanagement; teacher a timely basis teacher salaries.\nmotivation.\n\n\nImprove Government's US$4.1 million Project monitoring Purpose and integrity\nCapacity to Manage Sector: Project effectively reports; study reports. maintained within project\ncapacity building within the implemented and management; stakeholder\nMOE and its related services; management improved; participation in pilot studies.\npilot studies. reports with implementable\nresults.\n\n\n**Annexe 1 Attachment: Program and Project Monitorin** **Tar** **ets**\n**_Year_** _2001-02 2002-03_ **_2003-04 2004-05 2005-06 2006-07 2007-08 2008-09 2009-10_**\nPrimary Enrollment Boys 19,125 21,506 24,300 26,627 29,867 31,696 34,457 37,217 40,129\nPrimary Enrollment Girls 14,875 17,994 20,", "source": "fcv_pads_east_africa", "subset": "annotate_aj_part2", "spans": [{"key": "fcv_pads_east_africa:017438:31:0:0", "start": 577, "end": 591, "surface": "School surveys", "probe_tag": "confusion", "probe_score": 0.1078, "luna_label": 0, "luna_reason": "Standalone table cell in project monitoring framework"}]}, {"key": "aj2-200", "text": " experiment and this approach can identify the dimensions of het\n\nerogeneity in the prevalence of a sensitive behavior.\n\n\nFuture research on this topic could take several directions. Firstly, additional research\n\n\ncould be conducted measuring levels of tax evasion in Indonesia to validate our findings\n\n\nby analyzing tax administrative data with third-party information and/or survey data that\n\n\ndirectly captures tax evasion and tax morale. In addition, there may be value in exploring\n\n\n17", "source": "general_prwp", "subset": "annotate_aj_part2", "spans": [{"key": "prwp:001427:19:1:0", "start": 318, "end": 341, "surface": "tax administrative data", "probe_tag": "confusion", "probe_score": 0.4076, "luna_label": 0, "luna_reason": "Future research proposes analyzing tax administrative data."}]}, {"key": "aj2-201", "text": "<mark>TABLE 6</mark> **Asylum applications lodged in Central Europe** <sup>*****</sup> **by origin\u0003**\n| First quarter 2012 to second quarter 2014\n\n***** See Table 1 for the 11 countries included. Top-40 ranking of countries based on applications lodged during second quarter of 2014.\n\n\n\n\n\nOrigin\n\n\n\n\n\nSerbia (and Kosovo:\nS/RES/1244 (1999))\n\n|2012|Col2|Col3|Col4|2013|Col6|Col7|Col8|2014|Col10|First semester change|Col12|Col13|‘14-’13|\n|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n|Q1<br> 98<br> 390<br> 49<br> 807<br> 60<br> 549<br> 110<br> 287<br> 37<br> 114<br> 69<br> 19<br> 31<br> 3<br> 18<br> 6<br> 21<br> 26<br> 121<br> 1<br> 3<br> 63<br> 39<br> 31<br> 3<br> 12<br> 5<br> 11<br> 6<br> 45<br> -<br> 8<br> 20<br> 5<br> 2<br> 17<br> 39<br> 2<br> 12<br> 2<br> 208|Q2<br> 142<br> 397<br> 46<br> 808<", "source": "reliefweb", "subset": "annotate_aj_part2", "spans": [{"key": "reliefweb:000864:22:0:0", "start": 23, "end": 67, "surface": "Asylum applications lodged in Central Europe", "probe_tag": "confusion", "probe_score": 0.2108, "luna_label": 0, "luna_reason": "Standalone table title, not an independent data-use mention."}]}, {"key": "aj2-202", "text": "6\n\n\nThere is strong support in the Government for increasing resources for education, and the Government\nmade a commitment to increase education's share of budget from 16% in 2001-02 to 25% in 2009-10.\n\n\nOne of the reasons for choosing an APL with a ten-year perspective is that the education budget\nshortages will continue to be a constraint in the next few years. Over this period, Government\n\nexpenditures in non-priority areas will be brought under control and Government expenditures on\neducation can be expected to increase significantly. Despite the manageability in the long-run, the\nshort-run prospects on the budget are more challenging and donors will need to finance some recurrent\ncosts. The proposed APL will be implemented in three phases with distinct triggers (see Section B. 4).\nAs a result, a 10-year projection of enrollments and education costs has been developed (which is the\noverall framework for the APL), and a detailed five year plan and project proposals have been\nprepared (which is the framework for the first phase of the APL).\n\n\n3. Sector issues **to be addressed by the project and strategic choices**\n\nThe project will directly address all the issues below except for higher education.\n\n\n_Issues/Sector Problems_ _Government strategy and project proposal_\n\n**School Places**\n\nThe immediate problem in Djibouti City and The Government's strategy includes a combination\nsurrounding suburbs and other towns is the lack of of building more schools and continuing with the\nschool places due to the strong demand for schooling. double-shifting policy. The project will finance new\nclassrooms, sanitation services, and school furniture.\n\n**Equity, Gender, Disparities**\n\nChildren from poorer families, rural children, and The Government will construct schools in underespecially girls do not always attend school. The served areas, particularly in poorer parts of Djiboutirecent Household Expenditure Survey states that Ville where almost 70% of the population lives.\nmajor reasons for the", "source": "refugee_pads", "subset": "annotate_aj_part2", "spans": [{"key": "refugee_pads:000097:9:0:0", "start": 1906, "end": 1934, "surface": "Household Expenditure Survey", "probe_tag": "confusion", "probe_score": 0.8798, "luna_label": 1, "luna_reason": "Recent survey is cited for the concrete population-location finding."}]}, {"key": "aj2-203", "text": "8 percent on average from 1993 to 2015, the volatility around that average\nwas large at 3.7 percent (one standard deviation). The services sector—historically a key growth driver <sup>2</sup>\n—has been severely impacted by the Syria conflict and has contributed significantly to Lebanon’s low\ngrowth in recent years. Tumbling growth since 2011 and the large fiscal burden associated with Syrian\nrefugees’ access to public services and infrastructure have pushed the debt‐to‐GDP ratio higher again\n(around 140 percent as of end‐2015), resulting in a marked deterioration of the country’s macroeconomic\nenvironment. Meanwhile, the growth outlook remains subdued given the ongoing conflict in Syria and the\ndomestic political impasse. The World Bank projects real growth between 2 to 2.5 yearly over the medium\nterm.\n\n\n3. **Lebanon faces stark and pressing development challenges, however, the reform efforts to**\n**improve the quality of institutions and promote growth have been limited.** The difficulty in reaching\nconsensus in Lebanon delays decision‐making processes and leaves Lebanon vulnerable to external\ninfluences. This has left important economic reforms and projects unaddressed, and has resulted in\nmissed reform opportunities especially since in many cases the technical solutions are well known. This is\nclearly visible in the deteriorating infrastructure sectors, the poor quality of public institutions and service\ndelivery, and a challenging macroeconomic environment.\n\n\n4. **Lebanon’s pressing reform and development needs are particularly evident in its very poor**\n**infrastructure which represents a key constraint to growth.** Despite being an upper middle‐income\ncountry, Lebanon’s infrastructure is in a very bad condition. According to the World Economic Forum’s\n\n\n1 The World Bank Group. Lebanon Country Partnership Framework (CPF). 2016.\n2 Between 1997 and 2011—latest utilized final national accounts—the services sector accounted for an average of 74 percent of\nreal GDP.\n\n\nPage 10 of 90", "source": "jdc_operational", "subset": "annotate_aj_part2", "spans": [{"key": "jdc_operational:000008:13:1:0", "start": 1905, "end": 1928, "surface": "final national accounts", "probe_tag": "confusion", "probe_score": 0.621, "luna_label": 1, "luna_reason": "Existing national accounts support the attributed 74 percent GDP finding."}]}, {"key": "aj2-204", "text": "- 8 \n\nhas been approved by the Association; and (c) take into account lessons learned\nfrom the experience in the pilot before implementing Part 1.3 activities in other\nareas with the agreement of the Association.\n\n\n_Indexation of benefits_\n\n\n6. On an annual basis, beginning July 2021, the Recipient shall adjust (increase or\ndecrease) the benefits paid to Beneficiaries and Urban Destitute by multiplying\nthe benefit level with the year-on-year increase in food consumer prices of the\npreceding year, as measured by the food Consumer Price Index published yearly\nby CSA.\n\n\n**C.** **Project Implementation Manual**\n\n\n1. The Recipient shall prepare and furnish to the Association for approval, a Project\nImplementation Manual, setting out rules, methods, guidelines, and procedures\nfor the carrying out of the Project, which manual should be prepared in\naccordance with terms of reference satisfactory to the Association, including:\n\n\n(a) a detailed description of Project activities and institutional arrangements\nfor implementing the Project activities, as well as location of activities;\n\n\n(b) operational procedures, administration and coordination; monitoring and\nevaluation; financial, procurement and accounting procedures; social and\nenvironmental safeguards; and corruption and fraud mitigation measures;\n\n\n(c) eligibility criteria and procedures to be applied for the selection of\nBeneficiaries, including re-certification criteria and procedure for PDS\nBeneficiaries in UPSNP Cities, as well as schedules and modalities of\ndelivering benefits to the Beneficiaries, and the monitoring and\nevaluation of benefits delivered;\n\n\n(d) operational procedure governing implementation of Part 1.1 of the\nProject, including sequencing of activities, sectoral coordination, roles\nand responsibilities of one-stop shops and private implementing entities;\n\n\n(e) operating procedures governing Public Works Sub-projects under Part\n1.1 of the Project, including, _inter alia_, specific criteria for PW Subprojects to be eligible for financing under the Project, selection criteria\nfor PW Beneficiaries to participate in PW Sub-projects; and guidelines", "source": "fcv_pads_east_africa", "subset": "annotate_aj_part2", "spans": [{"key": "fcv_pads_east_africa:014206:8:0:0", "start": 521, "end": 546, "surface": "food Consumer Price Index", "probe_tag": "confusion", "probe_score": 0.3431, "luna_label": 1, "luna_reason": "CSA-published index is used to calculate annual benefit adjustments."}]}, {"key": "aj2-205", "text": " in the context\n\n\nof welfare prediction. In each case, we specify models at the sub-area level, which in these contexts refers to\n\n\nhighly disaggregated administrative areas akin to groups of villages. We then aggregate predictions to obtain\n\n\nestimates at the target area for each country.\n\n\nFor predictors, we use satellite-derived geospatial indicators that are available across much of the globe,\n\n\nmeaning that the methods and data evaluated here are widely applicable in cases where geolocated survey\n\n\ndata are available. We use shapefiles from the seven countries to pull geospatial data from multiple sources,\n\n\nwhich is then combined with samples drawn from the unit-level census data. In each country, we simulate\n\n\n100 two-stage samples - first randomly selecting enumeration areas and then randomly selecting households\n\n\nbased on survey designs of actual household surveys in each country - and compare the overall performance\n\n\nacross simulations, ensuring that the results are derived from one hundred possible samples rather than a\n\n\nsingle sample. Under these conditions, XGBoost and Cubist regression tend to outperform EBP and BRF in\n\n\nterms of accuracy, as measured both by Pearson correlations and Mean Squared Deviation. This can be seen\n\n\nclearly in the first two rows of Table 1.\n\n\nA key contribution of the paper is the evaluation of a two-stage residual block bootstrap to estimate uncertainty\n\n\n2See Das and Haslett (2019) for a comparative analysis of several poverty mapping methods including the ELL method, EBP,\nand M-quantile. Pratesi and Spagnolo (2023) offer a recent overview of small area estimation methods for measuring poverty.\nAnother potential SAE method is ESPREE (Isidro et al., 2016). However, we know of no readily available software packages\nthat implement either M-quantile or ESPREE.\n\n\n3", "source": "general_prwp", "subset": "annotate_aj_part2", "spans": [{"key": "prwp:001079:4:1:3", "start": 672, "end": 694, "surface": "unit-level census data", "probe_tag": "confusion", "probe_score": 0.4794, "luna_label": 1, "luna_reason": "Existing census data provide samples for the welfare prediction analysis."}]}, {"key": "aj2-206", "text": "**ACKNOWLEDGMENTS**\n\n\nThis paper was developed by colleagues from\nUNHCR Innovation Service and UN Global Pulse, an\ninnovation initiative of the United Nations. UN Global\nPulse would also like to thank the Government of the\nNetherlands for supporting its network of Pulse Labs\nand the activities under this project.\n\n\n\n**SUMMARY**\n\n\nThis white paper summarizes the initial findings\nand lessons learned from a project conducted by\nUNHCR’s Innovation Service and UN Global Pulse <sup>1</sup> to\ninform on the viability and value of social media analytics to complement understandings of the Europe\nRefugee Emergency.\n\n\nOngoing conflicts and violence around the world <sup>2</sup>\nled over 1.4 million people to seek refuge in Europe\nbetween 2015 and the first part of 2017.\n\n\nData from social media offers a wealth of information\nthat can be parsed to better understand what people\nthink, and how people feel about things affecting their\nlives, such as the displacement and movement of\nlarge volumes of people. Researchers in turn, can use\nthis data to inform topics of interest; decision makers\ncan use such data as evidence on which to inform for\nexample, programmatic responses and alterations.\n\n\nThe paper outlines the process, questions and methodology used to develop the project and presents preliminary observations on how aspects of the Europe\nRefugee Emergency are related on Twitter. The paper\ndescribes ten _quantitative social media mini-studies_\nthat were developed as part of the project.\n\n\nThe project team initially set out to explore the\nvalue of social media both for monitoring Persons of\nConcern’s (PoC), sentiment towards the provision of\nservices, and their interactions with service providers <sup>3</sup> . However, based on inconclusive initial results\nand anticipating an increase in negative public views\ntowards PoC following the 2015-2016 terrorist attacks\nin Europe, the project refocused on the analysis of\nhost communities’ sentiment towards PoC in reaction\nto incidents taking", "source": "reliefweb", "subset": "annotate_aj_part2", "spans": [{"key": "reliefweb:001252:2:0:0", "start": 773, "end": 795, "surface": "Data from social media", "probe_tag": "confusion", "probe_score": 0.6883, "luna_label": 1, "luna_reason": "Social media data is parsed and used as evidence for understanding and programmatic decisions."}]}, {"key": "aj2-207", "text": "* Popular Benchmarks\n**children.**\n\n\n**Project** **Development** **Outcome** **/** **Impact** **Project reports:** **(from** **Objective** **to Goal)**\n**Objective:** **Indicators:**\n**Assist** **war affected** - Improved social capital and - Initial Social Assessment - Communities in the NSAP\n**communities** **to restore** organizational development; (to establish indicators and target areas are assisted to\n**infrastructure,** **services** **and** - Increased access to and use methodologies for social ensure a reduced risk of\n**build** **local** **capacity for** of social and economic capital and organizational conflict\n**collective** **action.** Priority infrastructure and services development)\nwill be given to areas not - Proportion of NSAP - Annual social assessments; - NACSA complements and\npreviously serviced by investments targeted to newly - NaCSA M&E data; extends the work of other\ngovernment, newly accessible accessible areas, & areas - M&E data of relevant line agencies and rninistries\nand the most vulnerable previously not served, and mninistries; in support of the PRSP's\npopulation groups within those vulnerable people within these - Beneficiary Assessment poverty reduction and\nareas. areas; (BAs) biannually; decentralization objectives\n\n                  - Proportion of sub-projects                   - Participatory evaluation\nthat reflect priorities of reports for a random sample of                   - NACSA is fully integrated\ntargeted communities and assisted conmmunities; into national planning and\nbeneficiaries; and                  - Technical audits resource allocation\n\n                  - Proportion of sub-projects frameworks (such as the\noperative 24emonths after National Recovery Strategy,\ncorpletion. the PRSP, and", "source": "refugee_pads", "subset": "annotate_aj_part2", "spans": [{"key": "refugee_pads:000052:29:1:0", "start": 862, "end": 876, "surface": "NaCSA M&E data", "probe_tag": "confusion", "probe_score": 0.2118, "luna_label": 0, "luna_reason": "Project M&E verification source, not an existing finding or analysis"}]}, {"key": "aj2-208", "text": "\n(b) Factories receive a draft of the full assessment report regarding compliance on all assessment\n\nquestions, including information on whether the issues subject to public reporting are in\nnoncompliance.\n\n\n(c) When the assessment report is finalized, the factory’s compliance with the 29 publicly\n\nreported issues is published online, on the Better Work Transparency Portal (for all factories\nthat have had at least two assessments).\n\n\n(d) In response, factories can upload documents and photos on the public reporting website\n\n(including information from assessment reports).\n\n\n(e) A factory’s compliance findings remain on the website until a new assessment report is\n\npublished, at which point the website is updated to reflect the factory’s most recent assessment\ndata.\n\n\n(f) Every time a new assessment is completed for a factory, new compliance data replaces old\ndata.\n\n\n(g) Compliance data on factories that had not yet had two assessments when public reporting was\n\nlaunched is published following a factory’s second assessment.\n\n\n27", "source": "jdc_operational", "subset": "annotate_aj_part2", "spans": [{"key": "sample:jdc_operational:000045:35:1:0", "start": 759, "end": 774, "surface": "assessment\ndata", "probe_tag": "drop", "probe_score": 0.0491, "luna_label": 0, "luna_reason": null}, {"key": "sample:jdc_operational:000045:35:1:1", "start": 842, "end": 857, "surface": "compliance data", "probe_tag": "confusion", "probe_score": 0.1116, "luna_label": 0, "luna_reason": null}]}, {"key": "aj2-209", "text": "**Kenya Informal Settlements Improvement Project: Machakos Region**\n<u>Resettlement Action Plan Report for Swahili Informal Settlement</u>\n\n\n**7.14** **Monitoring and Evaluation**\n\n**I.** **Brief on What is Monitoring and Evaluation**\n\nMonitoring focuses on what is happening. It is a routine process of collecting and managing\nproject data that provides feedback as pertains to the progress of a project. The process involves\nmeasuring, assessing, recording, and analysing the project information on a continuous basis,\nand communicating the same to those concerned <sup>25</sup> [^25: Mulwa, Francis W; and, Simon N Nguluu. 2003. Participatory Monitoring and Evaluation: A Strategy for\nOrganisation Strengthening (Second Revised Edition). PREMESE-Olivex Publishers, Nairobi, Kenya] .\n\nOn the other hand, evaluation focuses on what has happened. It is an episodic process that\ndetermines the impact of an intervention. The process involves reviewing both actions and\nassumptions behind an intervention, to determine as systematically and objectively as possible,\nthe relevance, effectiveness, and impact in light of their objectives <sup>26</sup> [^26: _ibid_] .\n\n<u>And, the relationship between monitoring and evaluation can be summarised as follows</u> <sup>27</sup> [^27: _ibid_] <u>:</u>\n\n\n**<u>ITEM</u>** **<u>MONITORING</u>** **<u>EVALUATION</u>**\n\n\nb) **Main action** Keeping track or overview Assessment\n\n\n\nd) **Focus** Inputs, outputs, process outcomes,\nwork plans\n\n\n\nEffectiveness, relevance, impact, costeffectiveness\n\n\n\nf) **Undertaken**\n**by**\n\n\n\n**Project manager, and ***beneficiary\ncommunity\n\n\n\n\n\n**Project manager, ****supervisor,", "source": "fcv_pads_east_africa", "subset": "annotate_aj_part2", "spans": [{"key": "fcv_pads_east_africa:020520:67:0:0", "start": 328, "end": 340, "surface": "project data", "probe_tag": "confusion", "probe_score": 0.1471, "luna_label": 0, "luna_reason": "Project data is being routinely collected and managed through monitoring."}]}, {"key": "aj2-210", "text": " goods, and among imports from different regions, allows for two-way trade in each product\n\n\ncategory, depending on the ease of substitution between products from different regions. Factor inputs of\n\n\nland, capital, skilled and unskilled labor, and in some sectors a natural resource factor, are included in\n\n\nthe analysis. The model includes the explicit treatment of international trade and transport margins, a\n\n\n“global” bank designed to mediate between world savings and investment, and a relatively sophisticated\n\n\nconsumer demand system designed to capture differential price and income responsiveness across\n\n\ncountries.\n\n\nThe constant returns to scale version of the GTAP model was adjusted to incorporate China’s duty\n\n\nexemptions—which have been a key reason for the rapid integration of China into global production\n\n\n4 This applied general equilibrium model is documented comprehensively in Hertel (1997) and in the GTAP Data Base\ndocumentation (Dimaranan 2006).\n\n\n8", "source": "general_prwp", "subset": "annotate_aj_part2", "spans": [{"key": "prwp:003511:10:1:0", "start": 929, "end": 943, "surface": "GTAP Data Base", "probe_tag": "confusion", "probe_score": 0.539, "luna_label": 1, "luna_reason": "Named existing database cited as documentation for the applied equilibrium model."}]}, {"key": "aj2-211", "text": "ing 37 European countries which provided monthly data to UNHCR (excluding Italy).<br>Total<br>2007<br>No. of applications (excluding Italy)<br>Change (%)<br>Share (%)<br>including<br>Origin<br>Q1<br>Q2<br>Q3<br>Q4<br>Total<br>Q2-Q1 Q3-Q2 Q4-Q3<br>Q1<br>Q2<br>Q3<br>Q4<br>Italy|\n|**Table 10. Origin of asylum applicants in Europe by quarter, 2007**<br>Covering 37 European countries which provided monthly data to UNHCR (excluding Italy).<br>Total<br>2007<br>No. of applications (excluding Italy)<br>Change (%)<br>Share (%)<br>including<br>Origin<br>Q1<br>Q2<br>Q3<br>Q4<br>Total<br>Q2-Q1 Q3-Q2 Q4-Q3<br>Q1<br>Q2<br>Q3<br>Q4<br>Italy|**Table 10. Origin of asylum applicants in Europe by quarter, 2007**<br>Covering 37 European countries which provided monthly data to UNHCR (excluding Italy).<br>Total<br>2007<br>No. of applications (excluding Italy)<br>Change (%)<br>Share (%)<br>including<br>Origin<br>Q1<br>Q2<br>Q3<br>Q4<br>Total<br>Q2-Q1 Q3-Q2 Q4", "source": "reliefweb", "subset": "annotate_aj_part2", "spans": [{"key": "reliefweb:000427:22:6:1", "start": 41, "end": 53, "surface": "monthly data", "probe_tag": "confusion", "probe_score": 0.861, "luna_label": 0, "luna_reason": "Phrase appears in table coverage text, not as an independently used data resource."}]}, {"key": "aj2-212", "text": " and middle\nPrivate sector share in middle schools.\nschools increases to 12%.\n\n\nHigher promotion rates at the Promotion rates at the end of Year books and reports. Assumes enough space at the\nend of the primary school the primary cycle should rise middle schools to\ncycle. from 36% in 1999 to 83% in accommodate the primary\n2010. cycle graduates.\nIncrease participation of girls Enrollment rate for girls Random surveys of Economic situation worsens\nand children from poorer increases faster than boys. school students making it more difficult to\ngroups More children from poorer including a baseline in provide incentives to the poor\ngroups in school. 2001 and follow up to attend.\nsurveys in 2005 and\n2010.", "source": "refugee_pads", "subset": "annotate_aj_part2", "spans": [{"key": "refugee_pads:000161:29:1:0", "start": 405, "end": 419, "surface": "Random surveys", "probe_tag": "confusion", "probe_score": 0.188, "luna_label": 0, "luna_reason": "Baseline and follow-up surveys are planned monitoring activities, not existing data use."}]}, {"key": "aj2-213", "text": " investments financed through the discretionary Municipal Grants provided by the Project\nare likely to yield higher rates of return over time. For example, evaluations of similar projects in\ncountries like India, Bangladesh and Uganda have yielded robust positive rates of return.\n\n59. Since the spending choices of municipalities cannot be determined _a priori_, a framework\napproach will be adopted to estimate the economic efficiency of sample investments financed by\nMunicipal Grants. The Bank will conduct economic analysis of a sample of about 5-10 percent\nof municipal investments in local roads, solid waste management, water and sanitation, and\ndrainage at the mid-term and end of the Project. Smaller investments (<US$500,000) will be\nsubject to standard cost effectiveness analysis, while larger ones (>US$500,000) will be sampled\nfor cost benefit analysis. The Project will also examine if municipalities are making better\nallocative choices which respond to their constituent priorities by surveying citizen satisfaction\nwith municipal services and by matching citizen preference with actual municipal expenditure\npatterns.\n\n60. Public sector provision and financing of emergency local services are appropriate in this\ncontext for a number of reasons: one, the social benefits of the chosen subprojects under the\nProject are likely to outweigh their costs because of the robust social accountability mechanisms\ninvolved and the social capital it can generate; two, improving access to and quality of the basic\npublic goods and services in these participating municipalities is likely to benefit the poor the\n\n\n16", "source": "jdc_operational", "subset": "annotate_aj_part2", "spans": [{"key": "jdc_operational:000026:27:1:0", "start": 1003, "end": 1057, "surface": "surveying citizen satisfaction\nwith municipal services", "probe_tag": "confusion", "probe_score": 0.156, "luna_label": 0, "luna_reason": "Planned project survey will generate new citizen satisfaction data."}]}, {"key": "aj2-214", "text": "**The World Bank** Implementation Status & Results Report\nStrengthen Ethiopia’s Adaptive Safety Net (P172479)\n\n\n**Risks**\n\n\n**Systematic Operations Risk-rating Tool**\n\n\nRisk Category Rating at Approval Previous Rating Current Rating\n\n\nPolitical and Governance High High High\n\n\nMacroeconomic Substantial Substantial Substantial\n\n\nSector Strategies and Policies Moderate Moderate Moderate\n\n\nTechnical Design of Project or Program Moderate Moderate Moderate\n\nInstitutional Capacity for Implementation and\nModerate Moderate Moderate\n<u>Sustainability</u>\n\nFiduciary Substantial Substantial Substantial\n\n\nEnvironment and Social Substantial Substantial Substantial\n\n\nStakeholders Moderate Moderate Moderate\n\n\nOther -- -- -\n\nOverall Substantial Substantial Substantial\n\n\n**Results**\n\n\n**PDO Indicators by Objectives / Outcomes**\n\n\n\n\n\n\n\n\n\n\n\n\n\n8/20/2021 Page 2 of 14", "source": "fcv_pads_east_africa", "subset": "annotate_aj_part2", "spans": [{"key": "fcv_pads_east_africa:010515:1:0:0", "start": 807, "end": 821, "surface": "PDO Indicators", "probe_tag": "confusion", "probe_score": 0.0826, "luna_label": 0, "luna_reason": "Standalone table heading, not a cited or used data resource."}]}, {"key": "aj2-215", "text": "important to test for. If the investment climate affects the relative productivity of exiting\n\n\nfirms, this has implications on the efficiency of the allocation of resources in a country and\n\n\nthus on its overall level of productivity.\n\n\n_Firm size_\n\n\nThe literature consistently finds that small firms are more likely to exit than larger\n\n\nfirms (Roberts and Tybout (1996); Haltiwanger et al. (2004)). Small firms are more likely to\n\n\nlack the scale needed to be more efficient and compete with larger competitors. As many\n\n\nsmall firms are also new, they do not have the same experience or proven track record of\n\n\nsucceeding in business.  The question here is whether investment climate conditions\n\n\nexacerbate these trends – or whether there are dimensions of the investment climate that\n\n\naffect them less. Costs, particularly fixed costs that will be relatively higher for small firms,\n\n\nare likely to hurt smaller firms more. Access to credit as well as property rights are touted as\n\n\nthe benefits of firms formalizing and thus should be relatively more beneficial for SMEs\n\n\ncompared to microfirms.\n\n\nOne issue when looking at the effects of size is that the data source can matter.\n\n\nStudies that rely on census data can have truncated samples. Many censuses only target firms\n\n\nof a certain size, typically 10 employees or more. What is then recorded as ‘exit’ is a mixture\n\n\nbetween those firms that truly end operations and those that dip down below 10 employees\n\n\nbut who remain in business. The surveys used here also have a cutoff – but it is at 2\n\n\nemployees. Thus, all the firms in the original sample in 2002 have 2 employees or more. In\n\n\n2005, those with only a single employee are still recorded as surviving, although they were\n\n\nnot re-interviewed. This makes it possible to look at the whole range of sizes of firms, with a\n\n\n12", "source": "general_prwp", "subset": "annotate_aj_part2", "spans": [{"key": "prwp:004277:13:0:0", "start": 1215, "end": 1226, "surface": "census data", "probe_tag": "confusion", "probe_score": 0.697, "luna_label": 1, "luna_reason": "Census data are linked to studies’ concrete finding of truncated samples."}]}, {"key": "aj2-216", "text": " which escalated during the brutal military\ncrackdown in Myanmar’s Rakhine State in August\n2017. As of the end of 2024, more than 1.1 million\nRohingya have been forced to flee abroad and of the\nreported 619,400 Rohingya in Myanmar, 41 per cent\nwere internally displaced by the end of 2024.\n\n\nGlobally, 58 per cent of all reported stateless people\nare in the Asia and the Pacific region (2.5 million).\nSome 21 per cent are in West and Central Africa\n(931,100), 10 per cent are in Europe and 8 per cent are\nin the Middle East and North Africa. However, the vast\nmajority of reported stateless people reside in just a\nfew countries, with nearly 90 per cent of them in just\nten countries (see figure 22).\n\n\n\nUNHCR > **GLOBAL TRENDS 2024** 57", "source": "reliefweb", "subset": "annotate_aj_part2", "spans": [{"key": "reliefweb:001242:56:1:0", "start": 714, "end": 732, "surface": "GLOBAL TRENDS 2024", "probe_tag": "confusion", "probe_score": 0.1391, "luna_label": 0, "luna_reason": "Standalone report heading, not a cited or analyzed data resource."}]}, {"key": "aj2-217", "text": "testing, implementing a national survey to identify the poor with the participation of local communities,\nand building institutional capacity. The aim is to increase the number of beneficiaries from 1 million\nhouseholds currently to 1.5 million households to include all those under the national poverty line.\n\n\n105. However, resources to implement such reform program are insufficient, and additional resources\nand technical assistance are needed to support it. The current food price crisis has highlighted the\nlimitations of the current system to support the poor when faced with risk and the importance of building\na Social Safety Net (SSN) for the long run that could both be scaled up in times of crisis as well as\nproviding incentives for human capital accumulation and economic advancement.\n\n\n**111.** **The Social Welfare Fund: Opportunities and Challenges**\n\n\n106. The SWF, established in 1996 by Presidential Law, is the only public cash-transfer based social\nsafety net in Yemen. The SWF has expanded its coverage from 100,000 beneficiaries at its start to almost\n\n1 million poor and vulnerable Yemeni households over a ten-year period. The Fund?s budget has grown\nfrom US$4 million at the outset to US$200 million in 2008/2009. In response to the food crisis, in 2009\nthe government doubled the maximum SWF benefits to YR 4,000 (US$20) per case per month and has\ndecreed that the number of beneficiaries will be increased to at least 1.5 million households, permitting\ncoverage of nearly all those below the poverty line. Initially, based on government policy, beneficiaries\nwere defined by social categories (i.e. widows, single females with no male support, elderly, etc.) without\nreference to economic circumstances resulting in low coverage of the poor and little impact on overall\npoverty.\n\n\n107. In response to its expansion in coverage, the SWF expanded in staffing and regional presence. As\nof December 2009, the SWF has 1775 staff operating through a three-", "source": "refugee_pads", "subset": "annotate_aj_part2", "spans": [{"key": "refugee_pads:000080:30:0:0", "start": 24, "end": 39, "surface": "national survey", "probe_tag": "confusion", "probe_score": 0.571, "luna_label": 0, "luna_reason": "Survey is being implemented to identify poor beneficiaries."}]}, {"key": "aj2-218", "text": "**The World Bank**\nStrengthening Lebanon’s Covid-19 Response (P178587)\n\n\n**Table 5. Pre-registration and vaccination according to nationality (as of April 11, 2022)** <sup>**9**</sup> [^9: IMPACT COVID-19 vaccine national platform accessed on April 11, 2022]\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Nationality|# of individuals<br>pre-registered|percent of total<br>individuals<br>pre-registered by<br>nationality*|# of individuals<br>who received at<br>least one dose of<br>a COVID-19<br>vaccine|percent of pre-<br>registered who<br>received at least<br>one dose of a<br>COVID-19<br>vaccine|# of individuals<br>who received at<br>least 2 doses of a<br>COVID-19<br>vaccine|percent of pre-<br>registered who<br>received at least<br>two doses of a<br>COVID-19<br>vaccine|\n|---|---|---|---|---|---|---|\n|Lebanese<br>|2,831,959<br>|75%<br>|2,022,381<br>|71%<br>|1,826,011<br>|64%<br>|\n|Palestinian<br>|120,160<br>|3%<br>|73,638<br>|61%<br>|62,829<br>|52%<br>|\n|Syrian<br>|559,274<br>|15%<br>|316,127<br>|57%<br>|223,525<br", "source": "jdc_operational", "subset": "annotate_aj_part2", "spans": [{"key": "jdc_operational:000000:24:0:0", "start": 189, "end": 230, "surface": "IMPACT COVID-19 vaccine national platform", "probe_tag": "confusion", "probe_score": 0.7869, "luna_label": 1, "luna_reason": "Platform is cited as the source for vaccination figures presented in the table."}]}, {"key": "aj2-219", "text": " employability” is rated MU** due to slow progress toward achieving target\nnumbers of beneficiaries (31,245 out of 70,000 in year 5 of the Project) and the slow progress in engaging the private\nsector employers to support placement in internship and employment. The slow progress is partly due to attrition, which\ncontinues to be an issue: Through the five program Cycles implemented and completed, a total of 40,935 out of 55,184\nyouth targeted completed Job Specific Skills Training (JSST) under Component 1, representing a 74 percent completion\nrate.\n\n\n3. **Component 2 on support to self-employment and job creation is progressing well and is rated MS.** It also\ncontinues to show high employment results. Cycles 1, 2 and 3 beneficiaries of business grants exhibit 93 percent\nemployment rate (mostly in self-employment). These results are based on the tracer study conducted on Cycle 1\nbeneficiaries and bulk SMS surveys on Cycles 2 and 3 beneficiaries. The MbeleNaBiz business plan competition (BPC) is\nwell under way and has been able to disburse the first tranche of business awards. Similarly, the Future Bora Initiative,\nwhich aims to identify interventions for hard-to-serve youth, is on track and will be unveiling the successful awardees early\nin FY 22. The challenge in this Component emanates from the slow progress in the digital learning for Access to\nGovernment Procurement Opportunities (AGPO) and catalytic funds, which targets over 180,000 individuals and has not\nbeen able to meet its targets within the required time frame.\n\n\n4. **Component 3** **has made some progress but continues to keep a slow implementation pace.** This Component\ncompleted the Informal Service Sector Occupational Survey (ISSOS), has established the Labor Market Observatory (LMO)\nand prepared a road map for the Kenya Labor Market Information System (KLMIS). There has been progress on updating\nthe Kenyan National Occupational Classification (KNOC", "source": "fcv_pads_east_africa", "subset": "annotate_aj_part2", "spans": [{"key": "fcv_pads_east_africa:008597:3:1:2", "start": 1673, "end": 1716, "surface": "Informal Service Sector Occupational Survey", "probe_tag": "confusion", "probe_score": 0.6074, "luna_label": 0, "luna_reason": "Survey completion reports project activity, not use of existing survey data."}]}, {"key": "aj2-220", "text": "affected by the HIV/AIDS epidemic (such as Lesotho, Swaziland and Zimbabwe) where the\n\n\nwidowhood rate is considerably higher and the share of remarried widows lower.\n\n\nThere is naturally a strong positive age gradient in the likelihood of being widowed.\n\n\nThe top panels of Figures 1 and 2 display the gradient by age and by marriage duration in\n\n\nPSF1, respectively. In Figure 1, we graph the proportion of all women of a given age (with no\n\n\nmore than a single marital dissolution) who are ever-widowed. As expected, the share of\n\n\nwidowed women steadily rises and at an increasing rate to reach close to 40% of women aged\n\n\n50-70 and almost 80% of those aged 70 and older. In Figure 2, the y-axis gives the widowhood\n\n\nrate for a given marriage duration, among marriages that survived for at least that period of\n\n\ntime.\n\n\nThe bottom panels of these figures show the equivalent computations for divorce rates.\n\n\nHere, the age patterns show a peak around the age of 40. However, divorce rates by marriage\n\n\nduration make it clear that those most at risk are recent marriages, since the rate of divorce is\n\n\nhighest in the first five years of marriage. <sup>13</sup> [^13: These results echo findings from the sparse literature (Antoine and Dial 2003; Locoh and Thiriat 1995; Smith et\nal. 1984).] This is driven by divorce in urban areas, where the\n\n\ndivorce rate among recent marriages is more than twice as high as in rural areas, reaching an\n\n\naverage of 1.4% per annum during the first five years (against 0.6% in rural areas). One\n\nquarter of divorces happen within the first three years of marriage, while the median duration\n\n\nof marriages that ended with a divorce is 7.5 years. Divorces happen more rapidly for the\n\n\nyounger generation, as the first quartile of the distribution of marriage duration is only two\n\n\nyears for women under 40 against six years for women older than 40 (the corresponding\n\n\nmedians", "source": "general_prwp", "subset": "annotate_aj_part2", "spans": [{"key": "prwp:007189:11:0:0", "start": 349, "end": 353, "surface": "PSF1", "probe_tag": "confusion", "probe_score": 0.267, "luna_label": 1, "luna_reason": "PSF1 data underpin widowhood and divorce-rate computations shown in figures."}]}, {"key": "aj2-221", "text": "**SECTION 4**\n\n\nThis section provides an analysis of data per theme, including a summary table of assessment coverage by\ntarget group and geography.\n\n**4.** **ANALYSIS PER THEME**\n\n\n**4.1  Living Conditions**\n\n\n**Summary of assessment findings:** the available data shows that there are considerable differences\nregarding shelter options for the different target population groups, for example while only 59% of\nregistered Syrian refugees were identified as living in apartments/houses (Vulnerability Assessment of\nSyrian Refugees in Lebanon 2013 Report, VASyR), 70% of Lebanese returnees (International Organization\nfor Migration study), and 92% of PRS were resident in this shelter type (UNWRA). While informal tented\nsettlements (ITS) are present across the country, they are most prevalent in the Bekaa Valley and the\nNorth. The number of people being forced to rely on this shelter situation increased dramatically between\nJune 2013 and February 2014, where a 154% (Interagency ITS identification and mapping platform)\nincrease in ITS settlements throughout the country was identified. According to available assessment data\nthe average rent paid by the target population for their shelters ranges from USD 150 - 300 per month\n(VASyR, UNHCR Second Shelter Survey, UNRWA PRS Assessment, American Near East Refugee Aid\nNeeds Assessment, IOM Returnees Assessment), depending on the population group. With high rental\ncosts in mind, and given the depletion of the housing stock in Lebanon, 51% of the registered Syrian\nrefugee population has been categorised by the SWG as being at-risk with regards to shelter (UNHCR\nShelter survey).\n\n\nThe following table shows which target groups and geographic regions are covered by the assessments used\nin this section. It does not, however, show the quality of the assessments or the extent of the coverage.\n\n\n_Table [2]: Assessment coverage by geographic area and target population_\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Ge", "source": "reliefweb", "subset": "annotate_aj_part2", "spans": [{"key": "reliefweb:000410:10:0:1", "start": 971, "end": 1022, "surface": "Interagency ITS identification and mapping platform", "probe_tag": "confusion", "probe_score": 0.7124, "luna_label": 1, "luna_reason": "Platform data supports the reported 154% increase in ITS settlements."}, {"key": "reliefweb:000410:10:0:2", "start": 1114, "end": 1129, "surface": "assessment data", "probe_tag": "keep", "probe_score": 0.9253, "luna_label": 1, "luna_reason": "Assessment data supports the cited average-rent finding."}, {"key": "reliefweb:000410:10:0:7", "start": 1613, "end": 1633, "surface": "UNHCR\nShelter survey", "probe_tag": "keep", "probe_score": 0.9821, "luna_label": 1, "luna_reason": "Named UNHCR survey cited as source for the 51% shelter-risk finding."}]}, {"key": "aj2-222", "text": "**” when DPI ecosystem participants: (1) adhere to the applicable privacy-<br>by-design principles; (2) adhere to the applicable data minimization principles; (3) integrate accessible,<br>available, secure, and transparent data audit logging, as applicable, to provide people with transparency<br>about how their data is used.<br>Data sharing is considered “**_people-centric_**” when DPI ecosystem participants: (4) integrate consent-based<br>data sharing by default when sharing personal data; (5) integrate people-centric, standards-based, digitally<br>verifiable credentials as a data sharing mechanism, as applicable; and (6) integrate adequate grievance<br>redress.<br>A DPI ecosystem means all DPI providers and at least five DPI relying parties. A DPI provider means MODEE<br>and any other entity that provides digital identification, data sharing, or other trust services to DPI relying<br>parties. A DPI relying party is any public- or private-sector entity that relies on a digital identification or other<br>trust service for verification, or on an authoritative data source for shared data, as provided by a DPI provider.|\n|Data source/ Agency|(a) Annual reports on DPI implementation from MODEE, sectoral ministries, and the private sector, (b)<br>MODEE’s software documentation and testing reports, and (c) Third-party assessment reports.|\n\n\nPage | XLII", "source": "refugee_pads", "subset": "annotate_aj_part2", "spans": [{"key": "refugee_pads:000181:51:1:0", "start": 1161, "end": 1197, "surface": "Annual reports on DPI implementation", "probe_tag": "confusion", "probe_score": 0.8009, "luna_label": 1, "luna_reason": "Existing annual implementation reports are identified as data sources."}]}, {"key": "aj2-223", "text": " third of\ncountries for the HDI’s life-course gender gap <sup>19</sup> and women’s empowerment. <sup>20</sup> Local governance and\naccess to services in South Sudan take on specific gendered dimensions, such that women and girls are\naffected disproportionately compared to men and boys. A steeped patriarchal structure leads to male\ndecision-makers or gatekeepers in local community leadership structures, customary law and restorative\njustice settings, policy and security forces, and within homes. One survey shows the civic and political\n\n\n13 United Nations Population Fund, 2019 figures.\n14 UNOCHA. 2020 _. Humanitarian Snapshot April 2020._\n15 International Organization for Migration (IOM), Displacement Tracking Matrix (DTM), Round 6 (op cit.)\n16 Checchi, F., et. al. 2018. _Estimates of Crisis-attributable Mortality in South Sudan, December 2013–April 2018: A Statistical_\n_Analysis._ London School of Hygiene and Tropical Medicine.\n17 IPC = Integrated Food Security Phase Classification.\n18 IPC. 2019. _<mark>South Sudan: Acute Food Insecurity and Acute Malnutrition Situation (August 2019–April 2020).</mark>_\n19 HDI’s life-course gender gap compiles 12 indicators that analyze gender gaps in choices and opportunities across the life-span\nincluding education, labor and work, political representation, time use, and social protection. HDI’s women’s empowerment\ndashboard compiles 13 woman-specific empowerment indicators in three categories: reproductive health and family planning,\nviolence against women and girls, and socioeconomic empowerment.\n20 UNDP. 2018. _Human Development Indices and Indicators: 2018 Statistical Update - South Sudan._\n\n\nJune 22, 2020 Page 5 of 23", "source": "jdc_operational", "subset": "annotate_aj_part2", "spans": [{"key": "jdc_operational:000058:4:2:0", "start": 697, "end": 725, "surface": "Displacement Tracking Matrix", "probe_tag": "confusion", "probe_score": 0.8301, "luna_label": 1, "luna_reason": "Named DTM source cited for the survey-based civic and political finding."}]}, {"key": "aj2-224", "text": " are subjected to harassment, violence, detention, and even murder if they\nprotest against “land grabbing”. The Requesters allege that they have documented 23 incidents of\ncommunity members having been extrajudicially executed that have never been investigated\nofficially nor made public. They claim that between January 2020 and June 2021 they recorded\nnine cases of community members killed by game rangers or UWA. The Requesters allege that\nUWA has been harassing, beating, tear gassing, and intimidating people who attempt to return to\nthe land that was delineated.\n\n\n11. Third, the Requesters claim that the initial stakeholder engagement under the Project,\ncarried out by UWA, was inadequate as it failed to identify this longstanding, underlying conflict.\nThey further claim that, considering the fact that the accused entity is the same entity entrusted with\nthis important stakeholder engagement process, a considerable amount of important information\nwas never disclosed. The Requesters claim that the land conflict was never mentioned nor reported\npublicly nor made clear to the Bank in stakeholder engagement reports, and therefore that no\nmeasures were taken to redress this situation. The Requesters claim that when they refused to sign\noff on consultation documents, which they claim are not representative, they were threatened and\nintimidated by UWA.\n\n\n12. Fourth, the Requesters claim that some communities were discriminated against during\nemployment, which they allege is a breach of ESS2.", "source": "fcv_pads_east_africa", "subset": "annotate_aj_part2", "spans": [{"key": "fcv_pads_east_africa:011975:2:1:0", "start": 1098, "end": 1128, "surface": "stakeholder engagement reports", "probe_tag": "confusion", "probe_score": 0.7546, "luna_label": 0, "luna_reason": "Project engagement reports are cited as omitted disclosures, not substantive data evidence."}]}, {"key": "aj2-225", "text": " between households of female owners and households of male owners.\n\n\n(See columns 4 through 6 of Table 4). We do find significant differences in the rate at\n\n\nwhich household durable goods ownership increases, and in financial assets. Column 7 of\n\n\nTable 4 takes as the dependent variable the first principal component of a vector of 17\n\n\nhousehold assets, including landline and cellular telephones, television, autos, bicycles\n\n\nand gold jewelry. The weights in the index are derived from baseline data. Asset\n\n\nownership increases generally in the sample, but the regression results reported in column\n\n\n7 shows that the increase is significantly larger in households of male enterprise owners\n\n\n                               - - 17", "source": "general_prwp", "subset": "annotate_aj_part2", "spans": [{"key": "sample:prwp:003950:18:1:0", "start": 492, "end": 505, "surface": "baseline data", "probe_tag": "confusion", "probe_score": 0.7136, "luna_label": 1, "luna_reason": null}]}, {"key": "aj2-226", "text": "COMMUNITY PERCEPTION SURVEY ANALYSIS 2024\n\n### **Community Perceptions Survey Findings**\n\n#### **Risk 1: Exclusion and Denial of Access to Assistance**\n\n###### Analysis of Vulnerable Groups\n\n\n\nThe survey findings provide a window into\ncommunity perspectives on who they perceive as\nthe most vulnerable and the barriers these groups\nface in accessing critical aid, shedding light on local\nperceptions of risk, inclusion, and support gaps.\n\n\nAccording to communities, **the elderly emerged as**\n**the most frequently identified vulnerable group**,\nwith 55.26% of respondents recognizing their\nheightened needs. This aligns with findings from the\nfocus group discussions (FGDs) that indicate elderly\nindividuals often face significant physical and\nmobility barriers, making access to aid distribution\npoints or community services challenging. **Persons**\n**with disabilities** were the second most commonly\nidentified vulnerable group (46.4%), which also\nechoes insights from FGDs about their struggles\nwith mobility and lack of accessible distribution\nservices. The data suggests that accessibility issues\nfor both groups are further compounded by\ncommunication gaps, limited outreach, and logistical\nchallenges, leaving them doubly disadvantaged in\nnavigating the humanitarian assistance process.\n\n\n**Newly displaced individuals**, identified by 46.80%\nof respondents, also stand out as a high-risk group,\na finding that mirrors FGDs where newly displaced\npersons were noted to face immediate integration\nchallenges, language barriers, and heightened risks\nof exclusion due to a lack of familiarity with existing\naid services. Similarly, **persons from minority clans**\n(35.01%) face unique vulnerabilities tied to both\nsocial exclusion and language difficulties,\ncontributing to their marginalization. The\nidentification of **women-at-risk** (29.06%),\nparticularly pregnant women (74.93%), singlefemale-headed households (66.79%), and lactating\nwomen (", "source": "reliefweb", "subset": "annotate_aj_part2", "spans": [{"key": "reliefweb:000151:6:0:0", "start": 0, "end": 27, "surface": "COMMUNITY PERCEPTION SURVEY", "probe_tag": "confusion", "probe_score": 0.6661, "luna_label": 1, "luna_reason": "Survey findings provide quantitative evidence about perceived vulnerable groups."}]}, {"key": "aj2-227", "text": " (305 in Koboko District, 423 in Moyo District and\n1,780 in Yumbe District). There are 741 structures located in the proposed RoW; they include permanent/semipermanent buildings and others such as gates, soak pits, pit latrines, fences and perimeter walls etc. It is also\nestimated that about 266 households will be physically displaced as a result of the Project while another 2002\nPAPs across the three districts will be economically displaced. Taking into account that project preparation\ntimelines are relatively short, there will be particular attention to ensure adequate quality of the RAP especially\nin terms of (i) designing Livelihood Restoration Plans, (ii) appropriate measures to support PAPs from vulnerable\ngroups and those with disabilities, and (iii) carrying out a comprehensive census. PAPs will continue to be engaged\nthroughout the RAP processes and particularly during its implementation to address any issues that might have\nbeen missed out in earlier studies. Additional measures may include thorough screening at project preparation,\nthe project proponent’s commitment to monitoring, implementing agreed measures and institutional\nstrengthening measures. All affected properties will be subjected to a transparent valuation process and will be\npromptly and adequately compensated. A Livelihood Restoration Plan has been developed as part of the RAP\n\n\nPage 43 of 80", "source": "refugee_pads", "subset": "annotate_aj_part2", "spans": [{"key": "refugee_pads:000146:47:2:0", "start": 783, "end": 803, "surface": "comprehensive census", "probe_tag": "confusion", "probe_score": 0.1062, "luna_label": 0, "luna_reason": "Census is planned as part of project preparation, not existing data use."}]}, {"key": "aj2-228", "text": "**The World Bank**\nLebanon: Wheat supply emergency response project (P178866)\n\n\n(ESSP) and UN-administered cash transfer programs for displaced Syrians, addressing demand-side constraints\nregarding economic access of the poor and most vulnerable including refugees to food and food security.\n\n\n**II.** **PROJECT DESCRIPTION**\n\n\n**A. Project Development Objective**\n\n\n**PDO Statement**\n\n\n20. The Project Development Objective (PDO) is to ensure the availability of wheat in Lebanon, in response to the\nglobal commodity market disruptions, and to maintain access to affordable bread by poor and vulnerable households.\n\n\n**PDO Level Indicators**\n\n21. Progress toward the PDO will be monitored through the following key indicators: (1) the cumulative amount of\nwheat procured through the project and delivered in the ports of Beirut and Tripoli (target 250,000 tons); and (2)\nvulnerable beneficiaries with access to affordable bread <sup>6</sup> [^6: The vulnerable beneficiaries (poor Lebanese population and refugees, respectively) will be drawn and sampled based on the current\nWFP and UNHCR databases, respectively. The indicator will track bread consumption, specifically, rather than food security more broadly;\nthe actual values will be determined through the high frequency surveys foreseen during project implementation.] (target: 95 percent vulnerable beneficiaries; vulnerable host\ncommunities: 95 percent; refugees: 95 percent; vulnerable women: 99 percent).\n\n\n22. The project will also track progress through the following Intermediate Results Indicators:\n\n**-** Monthly amounts of wheat procured through the project and delivered in the ports of Beirut and Tripoli\n(target: monthly average of 50,000 tons for the first 5 months of project implementation). <sup>7</sup> [^7: This is based on an assumed wheat price of US$ 500 per ton.]\n\n**-** Percentage of beneficiaries’ feedback addressed through the Grievance Mechanism (GM) within the", "source": "jdc_operational", "subset": "annotate_aj_part2", "spans": [{"key": "sample:jdc_operational:000019:17:0:0", "start": 1263, "end": 1285, "surface": "high frequency surveys", "probe_tag": "confusion", "probe_score": 0.7175, "luna_label": 0, "luna_reason": "Future surveys will determine indicator values during project implementation."}]}, {"key": "aj2-229", "text": "- 7 \n\n**SCHEDULE**\n**Implementation Program**\n\n\n<u>Section I.</u> <u>Implementation Arrangements</u>\n\n\n1. (a) DLC shall: (i) prepare and furnish to the Association, a Project\nImplementation Plan for Part B of the Project, in form and substance satisfactory to the\nAssociation; (ii) carry out Part B of the Project in accordance with said PIP; and (iii)\nexcept as the Association shall otherwise agree, not amend, abrogate or waive any\nprovision of said PIP which, in the opinion of the Association, may materially and\nadversely affect the implementation of Part B of the Project or the achievement of the\nobjectives thereof.\n\n\n(b) Without limitation upon the provision of Paragraph 1 of this Section, the\nPIP shall include: (i) a Project implementation plan; (ii) a Project monitoring and\nevaluation plan; (iii) a Project procurement plan; (iv) a Project financial management\nmanual; and (v) such other administrative, financial, technical and organizational\narrangements as shall be required for Part B of the Project.\n\n\n2. (a) DLC shall prepare a Business Plan, in form and substance satisfactory to\nthe Association, which shall set out in such detail as the Association shall reasonably\nrequest, market data, budget and sources of financing, training and other services to be\nprovided under Part B of the Project, sources and programming of training, pricing policy\nfor different types of training and financial projections in the form of a budget, operating\naccount and marketing strategy.\n\n\n(b) DLC shall, no later than November 15 of each year, furnish the Business\nPlan for the following year to its Board for approval and to the Association for review\nand comments. DLC shall update the Business Plan annually and promptly furnish each\nupdated plan to its Board for approval and to the Association for review and comments.\n\n\n(c) DLC shall prepare and furnish", "source": "fcv_pads_east_africa", "subset": "annotate_aj_part2", "spans": [{"key": "fcv_pads_east_africa:010097:7:0:0", "start": 1199, "end": 1210, "surface": "market data", "probe_tag": "confusion", "probe_score": 0.0578, "luna_label": 0, "luna_reason": "Generic market data is named in a business plan without demonstrated use or finding."}]}, {"key": "aj2-230", "text": " their type.\nBoschini et al. (2007) find results indicating that when countries are rich in diamonds and\nprecious metals, both the positive and negative effects of natural resources are larger. This\nresult can be explained by ‘appropriability’ characteristics (i.e. high value, easy storage, easy\ntransportation or smuggling, and quick sale), which make these types of natural resources more\nprone to rent-seeking behaviour, corruption, and conflict. Easily appropriable point-source\nresources, such as oil, diamonds, and minerals, are more likely to be harmful to institutional\nquality and growth than diffuse resources such as agriculture (rice, wheat, and animals), whose\nrents are spread throughout the economy (Auty 1997; Isham et al. 2005; Mavrotas et al. 2011;\nWoolcook et al. 2001).\n\n\nMost of the previous studies are cross-country analyses. A distinctive feature of our paper is\nthat we use panel data on mineral deposits to estimate inequality at district level during 2001–\n2012, a period also characterized by relatively high growth in Africa. Gennaioli et al. (2014)\nargue that there are large regional differences within countries that need to be understood; the\nuse of subnational panel data therefore accounts for intra- and inter-regional differences that\ncan confound estimates. From an estimation standpoint, our study is also free from omitted\nvariable bias emanating from the large unobservable differences that are usually present in\ncross-country studies. <sup>8</sup>\n\n\n8 Lederman and Maloney (2008) consider cross-country heterogeneity a key reason for the elusiveness of\nempirical evidence on the resource curse.\n\n6", "source": "general_prwp", "subset": "annotate_aj_part2", "spans": [{"key": "prwp:006956:7:1:1", "start": 1184, "end": 1206, "surface": "subnational panel data", "probe_tag": "confusion", "probe_score": 0.4475, "luna_label": 1, "luna_reason": "Panel data are used to account for regional differences in estimation."}]}, {"key": "aj2-231", "text": "a Digital del permiso laboral: La DGME en\ncoordinación con Ministerio de Trabajo y Seguridad Social y con\nel apoyo del ACNUR, creará un mecanismo digital de consulta\nque permita a las personas refugiadas certificar ante posibles\nempleadores la validez de su permiso laboral.\n\n- Programa intermediación laboral para personas refugiadas:\n(a) El Ministerio de Trabajo y Seguridad Social brindará acceso\nefectivo a los programas de intermediación laboral como www.\nbuscoempleo.go.cr; Programa EMPLEATE, Mi Primer Empleo\ny PRONAE 4x4, además de los programas de apoyo a la\nmicroempresa. (b) La Inspección Nacional del Trabajo contemplará\nen sus procedimientos a las personas refugiadas con el objetivo\nde asegurar que sus derechos laborales y las obligaciones\npatronales sean reconocidos en igualdad de condiciones que los\nnacionales. (c) También se llevarán a cabo acciones informativas\nsobre la legislación vigente para mejorar el reconocimiento de\nlos documentos de identidad de las solicitantes de refugio y\nrefugiadas y reducir la discriminación y xenofobia durante los\nprocesos de reclutamiento y selección de personal.\n\n- Proyecto fomento del emprendedurismo: El Ministerio de\nEconomía, Industria y Comercio incluirá los emprendimientos\nliderados por personas refugiadas en el Registro de\nEmprendedores y fomentará su participación en encuentros\nempresariales y otras actividades organizadas por el Ministerio\npara fortalecer la micro y peque", "source": "reliefweb", "subset": "annotate_aj_part2", "spans": [{"key": "reliefweb:000936:72:4:0", "start": 1279, "end": 1304, "surface": "Registro de\nEmprendedores", "probe_tag": "confusion", "probe_score": 0.5646, "luna_label": 0, "luna_reason": "Named registry is mentioned as a mechanism, without showing its data being used."}]}, {"key": "aj2-232", "text": " will also take into account the experience\nof PRODERMO which is supporting the mainstreaming of community health, nutrition, and water intervention.\n\n**<u>Component 2</u>**\n\nThe project will reinforce the capacity of the Government by financing technical assistance and social protection\nsystem investments that will support the achievement of the project objectives. Specifically, the component will\nfinance effective and efficient implementation of the expanded PNSF program targeting and delivery system.\nInvestment in the targeting of the program will include refinement of the PMT methodology developed under the\nSSNP and its application through the PNSF program’s MIS and the social registry. The national social registry, from\nwhich the eligible program beneficiaries will be drawn, will be strengthened based on the lessons of experience\nto date. This will include making the necessary modifications to incorporate refugees in the social registry with a\nmarker to denote their refugee status, given that they have become eligible for a number of social programs in\nDjibouti. The program’s corresponding MIS will support the program in enrollment, payment, grievance and\nredress management, and monitoring as well as referral of potential beneficiaries to other services. The\ncomponent will also support the expansion of the information system’s hardware and software capacity to absorb\nadditional households (including in-take and assessment of needs and conditions).\n\nAdditional technical improvements and investment in the program’s delivery will include:\n\n\n   - **Communication and outreach** . the project will support the development of a PNSF communication plan\nand campaign with proposed communication channels, messages and timeline. The communication plan\nwill provide information and awareness raising of the program at multiple level including: (i) potential and\nactual program beneficiaries; (ii) the public (including non-beneficiaries; (iii) internal communication\nwithin government (including relevant partner ministries such as finance, health, and education); and (iv)\ndevelopment partners and donors. In addition to communication and awareness raising, potential\n\n\nPage 36", "source": "refugee_pads", "subset": "annotate_aj_part2", "spans": [{"key": "refugee_pads:000154:40:1:1", "start": 704, "end": 728, "surface": "national social registry", "probe_tag": "confusion", "probe_score": 0.1736, "luna_label": 1, "luna_reason": "Existing registry data will determine eligible program beneficiaries."}]}, {"key": "aj2-233", "text": "53. Under the Uganda rainfall condition, the frequency of flooding in most municipalities is between\n10 to 15 times in a year lasting 3 to 4 hours per flooding. Private and commercial vehicles are disrupted\nleading to loss of time and income. Improved drainage also leads to improvements to the environment and\nhealth benefits from reduced incidence of water borne disease. The internal rate of return obtained in\nprevious studies in similar environments was used to estimate the stream of benefits generated by improved\ndrainage. The EIRR of drainage under USMID was calculated at 6%.\n\n**Increase in Property Values**\n\n54. Improvements in urban roads in all the municipalities sampled has led to increases in value of\nproperties (land, buildings) and rental prices of properties in the adjacent areas of the constructed roads\nranging from 20% to 100% as per the table below. In Hoima municipality, the sharp increase in both rent\nand land values can also be attributed to speculations about oil extraction impact on the local economy.\n\n**Table 9: Changes in Rent and Land values**\n\n\n**Employment Creation**\n\n55. Construction of urban roads created direct and indirect jobs during construction. However, most of\nthe urban road infrastructure projects visited had been completed or partially completed. It was only\nNyakana road in Fort Portal where construction was still ongoing and therefore data on employment was\nobtained. The construction of Nyakana road in Fort Portal with a length of 0.94km, was directly employing\n56 workers out of which, 10% were highly skilled, 10% were skilled and 80 % unskilled. The highly skilled\nworkers, skilled workers and unskilled workers were earning UGX35,000, UGX25,000 and UGX12,000\nper day respectively. The construction of the road was also indirectly employing approximately 70 workers.\nThe construction of the road was expected to last for one year and three months.\n\n56. It can therefore be estimated from this data that construction of one kilometer creates", "source": "jdc_operational", "subset": "annotate_aj_part2", "spans": [{"key": "sample:jdc_operational:000006:69:0:0", "start": 1393, "end": 1411, "surface": "data on employment", "probe_tag": "confusion", "probe_score": 0.4287, "luna_label": 0, "luna_reason": null}]}, {"key": "aj2-234", "text": "br>select potential investors including DFIs and/or sovereign wealth funds (if they meet the<br>PCM definitions under the MDB methodology). In addition, the indictor will account for<br>private capital mobilized by beneficiaries as part of their matching upfront contributions for<br>co-investments under Component 2. The PIU will track the numbers through reports from<br>KDC and its own records on coinvestments.<br>PCM is expected to be generated as the first cohort of coinvestments are rolled out under<br>Component 2.|This indicator will track the total volume of additional private capital into the Component 3<br>Green Investment Fund (GIF) by private limited partners investing alongside KDC, as well as<br>select potential investors including DFIs and/or sovereign wealth funds (if they meet the<br>PCM definitions under the MDB methodology). In addition, the indictor will account for<br>private capital mobilized by beneficiaries as part of their matching upfront contributions for<br>co-investments under Component 2. The PIU will track the numbers through reports from<br>KDC and its own records on coinvestments.<br>PCM is expected to be generated as the first cohort of coinvestments are rolled out under<br>Component 2.|This indicator will track the total volume of additional private capital into the Component 3<br>Green Investment Fund (GIF) by private limited partners investing alongside KDC, as well as<br>select potential investors including DFIs and/or sovereign wealth funds (if they meet the<br>PCM definitions under the MDB methodology). In addition, the indictor will account for<br>private capital mobilized by beneficiaries as part of their matching upfront contributions for<br>co-investments under Component 2. The PIU will track", "source": "fcv_pads_east_africa", "subset": "annotate_aj_part2", "spans": [{"key": "fcv_pads_east_africa:003209:3:1:1", "start": 389, "end": 413, "surface": "records on coinvestments", "probe_tag": "confusion", "probe_score": 0.2266, "luna_label": 0, "luna_reason": "Project's own records used for indicator tracking, not substantive external data reuse."}]}, {"key": "aj2-235", "text": "|settlements|process CCEs and publically<br>fund claims on an ex-post basis|Early non-repayable ‘on account’ part-payment up<br>to a value of 25% of ‘likely claims’ to be made in<br>cases where weather indices and other local<br>information suggest that a large loss has been<br>incurred.|\n|---|---|---|\n|Risk<br>classification<br>|Both premium rates and<br>threshold yields determined<br>based on simple formulae.<br>Wide variation in the actuarial<br>value of NAIS products within<br>a state.|Actuarial design and ratemaking based on a<br>statistically robust Experience-Based Approach.<br>Probable yields are based on 7 year moving<br>average of actual yield, with Bühlmann credibility<br>smoothing between nearby insurance units.<br>Indemnity levels and commercial premium rates<br>are determined at the district level for each crop<br>using ten years of actual yield data. Farmer<br>premium rates are increasing in the commercial<br>premium rate (Figure 5).|\n|Data quality|A lack of standardization,<br>trained personnel, and<br>monitoring for CCEs exposes<br>the NAIS to significant delays,<br>basis risk and the risk of<br>manipulation.|Use of technology, standardization and<br>monitoring to improve the quality of CCEs. CCEs<br>to be video recorded with GPS-tagged footage.<br>Data to be provided to the insurer by SMS at the<br>time of the CCE to allow real time monitoring.<br>Remote sensing data to be used to target the<br>number", "source": "general_prwp", "subset": "annotate_aj_part2", "spans": [{"key": "prwp:005162:16:0:0", "start": 859, "end": 876, "surface": "actual yield data", "probe_tag": "confusion", "probe_score": 0.4487, "luna_label": 1, "luna_reason": "Ten years of yield data determine district crop indemnity and premium rates."}]}, {"key": "aj2-236", "text": "considered to be the most at-risk across the affected provinces. <sup>8</sup>\nEvidence from global humanitarian crises confirm that GBV risks are\nexacerbated during such situations. Although the MSRNA was not\nintended to estimate GBV prevalence, the PDHS provides a baseline\nto assess the pre-existing GBV situation in the country.\n\nAdolescent girls during the current crisis situation are vulnerable and\n#### % of KIs who said women, girls, men, boys are most at risk of violence (top 5 women & girls)\n\n\nWomen Girls Men Boys\n\n\n0% 20% 40% 60% 80% 100%\n\n\nSHAHEED BENAZIR ABAD\n\n\nLARKANA\n\n\nDADU\n\n\nSANGHAR\n\n\nKHAIRPUR\n\n\nat increased risk of coercion, GBV and child marriage. Moreover, due\nto the disruption to the education system and damage to the\ninfrastructure <sup>9</sup> [^9: 23,900 schools were damaged or destroyed in the floods, with more than 5,000 still used as\nrelief camps (UNICEF Sit Rep - Sep, 2022)] caused by flooding, a substantial increase in the\n\n\n8 The PDHS 2017-18 interviewed households, 94% of ever-married women aged 15-49 in\nPakistan, 97% in Azad Jammu and Kashmir, and 94% in Gilgit Baltistan were interviewed. In the\nsubsample of households selected for the male survey, 87% of ever-married men aged 15-49\nin Pakistan, 94% in Azad Jammu and Kashmir, and 84% in Gilgit Baltistan were successfully\ninterviewed.\n\n\n\nnumber of out of school adolescents <sup>10</sup> [^10: 22.8m adolescents aged 5-16 are out of school in Pakistan (Pakistan Education Statistics 201617)] is expected, leaving them\nwithout a routine and more vulnerable to psychological issues\n(trauma, stress, anxiety etc.) and protection risks. Furthermore,\nwithout essential information about their sexual and reproductive\nhealth, their health and wellbeing will be at risk.\n\n#### % of KIs reporting top risks for women and girls\n\n\n0% 10% 20% 30% 40%", "source": "reliefweb", "subset": "annotate_aj_part2", "spans": [{"key": "reliefweb:001618:6:0:2", "start": 1181, "end": 1192, "surface": "male survey", "probe_tag": "confusion", "probe_score": 0.8698, "luna_label": 1, "luna_reason": "Past male survey reports interviewed proportions in the PDHS subsample."}]}, {"key": "aj2-237", "text": " by the MOEHE’s MED within the Directorate\nGeneral of Planning using the PAF indicators prepared by this unit to monitor EDSP\nimplementation.\n\n_Component 1 – Strengthening “school-based practice” of pre-service teacher education_\n_programs_\n\n157. MOEHE’s DSQ will appoint a team that would consist of four persons, including a team\nleader. This team will oversee day-to-day implementation of this component. The TEIP would\nfund two local consultants (one to be based in Gaza) and an international institution with a\nproven track record of designing and implementing “school-based practice” programs to support\nthe MOEHE team.\n\n158. Responsibilities of MOEHE’s DSQ team will include:\n\n(a) Selection of consultants (1 international institution experienced in “school-based\n\npractice” programs. The selection process will include the definition of criteria to\nguide the selection process (in consultation with the selected institutions), the\nevaluation and screening criteria of candidates and the technical selection process\nof consultants (the PCU will assist on the procurement aspects of this process);\n(b) With support from selected local and international consultants, provide intensive\n\ntraining to TPTs (detailed responsibilities defined below) relevant to the aims and\nobjectives of the “school-based practice” program.\n(c) Assist the TPTs in reviewing current arrangements for teaching practice in their\n\nown institutions and identify changes taking into account international experience\nin “school-based programs”.\n(d) In collaboration with the MOEHE’s _Assessment and Evaluation Centre,_ and\n\nadvice from the international consultant, develop a ‘readiness to teach’ index of\n\n\n43", "source": "refugee_pads", "subset": "annotate_aj_part2", "spans": [{"key": "refugee_pads:000171:50:1:0", "start": 73, "end": 87, "surface": "PAF indicators", "probe_tag": "confusion", "probe_score": 0.7046, "luna_label": 0, "luna_reason": "Indicators support project monitoring, not an existing analytical finding or substantive data use."}]}, {"key": "aj2-238", "text": "23. Jordanian economy is disaggregated into 10 sectors to reflect the major produced and traded\ncommodities, mainly grains and crops, meat and livestock, extraction industries, processed food, textile\nand apparel, light manufacturing, heavy manufacturing, utilities and construction, transports and\ncommunication, and other service sectors. Skills in the labor market are presented as managers and\nlegislators, service providers and sales personnel, professionals, clerks, or elementary occupations.\n\n\n**_Cost-Benefit Analysis_**\n\n\n24. The baseline reflects the Jordanian economy in 2015 following the World Bank statistics and\nmedium-term growth programs without the PforR reforms. In the baseline, the standard GTAP dataset\nand parameters are fine-tuned based on the most recent national statistics to reflect the current economic\nframework. The simulation is defined as expected medium-term impacts of implementing three sets of\nreform, mainly work permits, business environment and trade reform, and investment promotion.\n\n\n25. The simulation results compared to the 2015 baseline shows the net benefits from trade reforms\nand other enabling business environment that are proposed by the DLIs.\n\n\n**Box 4.1. GTAP-CGE Model for Jordan: Reform Scenarios**\n\n\nThe cumulative effect of all of these actions is an additional 6 percent increase in real GDP by 2026, that is, a 0.6\npercent additional annual increase in GDP for the next 10 years.\nThis is in addition to an increase in investment by 25 percent (above the baseline), thus resulting in an accelerated\ngrowth path.\nWith regard to balance of payment, the increase in exports to the EU will more than double (107 percent increase).\nEstimated welfare increase (in equivalent variation) is around US$2.5 billion (8 percent increase compared to the\nbaseline in 2015).\nThe overall net benefits from the proposed reforms (cost US$300 million) are estimated to help the GoJ to reach the\n<mark>DLI targets. The results are likely", "source": "jdc_operational", "subset": "annotate_aj_part2", "spans": [{"key": "jdc_operational:000045:64:0:0", "start": 713, "end": 725, "surface": "GTAP dataset", "probe_tag": "confusion", "probe_score": 0.8768, "luna_label": 1, "luna_reason": "Named dataset used as the baseline input for economic simulation and reform analysis."}, {"key": "jdc_operational:000045:64:0:1", "start": 781, "end": 800, "surface": "national statistics", "probe_tag": "confusion", "probe_score": 0.819, "luna_label": 1, "luna_reason": "Existing national statistics fine-tune GTAP parameters for the economic simulation."}]}, {"key": "aj2-239", "text": "**Independent Evaluation Group (IEG)** Implementation Completion Report (ICR) Review\nEthiopia Enhancing Shared Prosperity (P151432)\n\n\nImproved development information and data for service delivery.\n\n\n**Rationale**\nThis DLI was expected to ensure adequate capacity for evidence-based analysis as a means of promoting\nquality development data and ensuring high-quality verification of PforR results. The DLI included milestones\nfor implementation of data quality assessments, as well as execution of a Demographic Health Survey and a\nHousehold Income Consumption and Expenditure Survey. Originally, this was the only DLI representing a\nfourth results area: ensuring quality data access and results. It would also have contributed to the objective of\nstrengthening accountability systems at decentralized levels. However, due to data gathering challenges\nrelated to COVID-19, as well as the desire to repurpose funds to address COVID-related challenges for\nEthiopians living in poverty, this DLI was dropped at the second AF in 2021.\n\n\n**Rating**\nSubstantial\n\n# **DLI 12**\n\n**DLI**\nImproved nutrition services.\n\n\n**Rationale**\nThis DLI was added at the first AF (2018) and then scaled back due to the impact of COVID-19 and the civil\nwar. The DLI was added to sharpen the program’s focus on reducing malnutrition and strengthening\nmulti-sectoral nutrition service delivery in Productive Safety Net Program (PSNP, a large national safety net\nprogram that responds not only to chronic food insecurity but also to shorter-term shocks such as\ndroughts) woredas, consistent with the government’s early years/human capital agenda. It originally included\nthree milestones, the last of which was cancelled due to the effect of COVID-19 and the Tigray conflict. The\noriginal milestones were: (1) woreda-level coordination platform is in place, consistent with agreed terms of\nreference, in woredas benefiting from", "source": "fcv_pads_east_africa", "subset": "annotate_aj_part2", "spans": [{"key": "fcv_pads_east_africa:000177:10:0:0", "start": 500, "end": 525, "surface": "Demographic Health Survey", "probe_tag": "confusion", "probe_score": 0.386, "luna_label": 0, "luna_reason": "Survey execution was a planned milestone, not use of existing data."}]}]