[{"key": "aivin2-000", "text": "filter. A rapid upward flow lifts the particles and keeps them in suspension until they\ncan be washed out.\n\n\nFollowing filtration, the water flows underground into a storage tank called a clearwell.\nWater leaving the clearwell is stabilized, fluoridated and chlorinated in-line on the way\nto the distribution pumps.\n\n\n**Chlorination**\nChlorination of public water supplies is the most important process used to produce\n[safe drinking water. A sufficient amount of Sodium Hypochlorite, essentially strong](http://www.greensboro-nc.gov/departments/Water/watersystem/chemicals.htm#chlorine)\nbleach, is added to the finished water so that a minimum amount of chlorine remains in\nthe water until it reaches the customer's tap. Chlorine is necessary for disinfection of\nwater before it is release to the consumers, chlorine will be responsible for killing all\nthe general coliforms and E – coli identified in the water by the Central Water Testing\nLaboratory sampling reports.\n\n**Distribution**\nAfter the final addition of chlorine, the water is released by gravity to the pipes that\nlead to the customer's tap. Chlorine is re-injected into the system to address issues of re\ncontamination for system running for long distances.\n\n\n64\n\n_Environmental Impact Assessment Report for Karimenu Water Scheme_", "source": "fcv_pads_east_africa", "subset": "annotate_aivin_part2", "spans": [{"key": "fcv_pads_east_africa:009667:63:0:0", "start": 920, "end": 969, "surface": "Central Water Testing\nLaboratory sampling reports", "probe_tag": "keep", "probe_score": 0.9041, "luna_label": 1, "luna_reason": "Named laboratory reports support the identified water contaminants."}]}, {"key": "aivin2-001", "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_aivin_part2", "spans": [{"key": "fcv_pads_east_africa:019700:38:1:1", "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 disparities across expenditure quintiles."}, {"key": "fcv_pads_east_africa:019700:38:1:2", "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 being withdrawn from school."}]}, {"key": "aivin2-002", "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_aivin_part2", "spans": [{"key": "fcv_pads_east_africa:017918:19:1:0", "start": 272, "end": 283, "surface": "survey data", "probe_tag": "keep", "probe_score": 0.9509, "luna_label": 1, "luna_reason": "Survey data underlie enrollment comparisons and identify disaggregation limits."}]}, {"key": "aivin2-003", "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_aivin_part2", "spans": [{"key": "fcv_pads_east_africa:018920:19:1:0", "start": 272, "end": 283, "surface": "survey data", "probe_tag": "keep", "probe_score": 0.9509, "luna_label": 1, "luna_reason": "Existing survey data support enrollment comparisons and inequity findings."}]}, {"key": "aivin2-004", "text": " take the data of 2017 as the achievement<br>within the project.<br>|<br>**Comments (achievements against targets):** <br>Baseline data was collected in December 2015. With the enhanced enforcement capacity of National Transport Safety Authority (NTSA), the<br>number of road cashes reduced by 30 percent and 22 percent, in 2016 and 2017 respectively, exceeding the original target.<br>Due to internal re-organizations occasioned by the Presidential Directive of January 2018 on Enforcement, the NTSA handed over the<br>responsibility and the enforcement gadgets to the National Police Service. Therefore, this ICR will take the data of 2017 as the achievement<br>within the project.<br>|<br>**Comments (achievements against targets):** <br>Baseline data was collected in December 2015. With the enhanced enforcement capacity of National Transport Safety Authority (NTSA), the<br>number of road cashes reduced by 30 percent and 22 percent, in 2016 and 2017 respectively, exceeding the original target.<br>Due to internal re-organizations occasioned by the Presidential Directive of January 2018 on Enforcement, the NTSA handed over the<br>responsibility and the enforcement gadgets to the National Police Service. Therefore, this ICR will take the data of 2017 as the achievement<br>within the project.<br>|<br>**Comments (achievements against targets):** <br>Baseline data was collected in December 2015. With the enhanced enforcement capacity of National Transport Safety Authority (NTSA), the<br>number of road cashes reduced by 30 percent and 22 percent, in 2016 and 2017 respectively, exceeding the original target.<br>Due to internal re-organizations occasioned by the Presidential Directive of January 2018 on Enforcement, the NTS", "source": "fcv_pads_east_africa", "subset": "annotate_aivin_part2", "spans": [{"key": "sample:fcv_pads_east_africa:016932:31:6:0", "start": 10, "end": 22, "surface": "data of 2017", "probe_tag": "keep", "probe_score": 0.9715, "luna_label": 0, "luna_reason": "Bare date-qualified data phrase lacks an identified source or attributed finding."}, {"key": "sample:fcv_pads_east_africa:016932:31:6:1", "start": 629, "end": 641, "surface": "data of 2017", "probe_tag": "keep", "probe_score": 0.9746, "luna_label": 0, "luna_reason": "Bare date-qualified data phrase cannot inherit the surrounding finding or source."}, {"key": "sample:fcv_pads_east_africa:016932:31:6:2", "start": 1248, "end": 1260, "surface": "data of 2017", "probe_tag": "keep", "probe_score": 0.9793, "luna_label": 0, "luna_reason": null}]}, {"key": "aivin2-005", "text": "108,873</mark></u>** **<u><mark>61,513,361</mark></u>**\n\n_Note:_ a. Population estimates (Source: CIESIN 2016 as local population (‘pop2015’) according to the local population density\ncalculated in 5 km buffers around the settlements.\n\n##### 4.2 Establishment of woodlots for energy and other purposes\n\nFirewood and charcoal are the main sources of energy for refugee and host communities in northern Uganda and\nthe rapid increase of population due to the arrival of refugees has inevitably increased pressure on natural\nresources and resulted in an imbalance between demand and available supply within accessible walking distance.\n\nInterventions for the establishment of woodlots are recommended over a period of at least three to five years, to\nensure sufficient time to establish adequate production capacity and proper transfer of knowledge to ensure\nsustainability. The objective should be to maximize biomass production in a short time and increase tree density\nto reach the optimum growth per unit of area. Fast-growing tree species and short-rotation coppice management\nshould be adopted to enable early harvesting for fuelwood. In addition, the use of multipurpose species can\nincrease people’s motivation to manage trees effectively because of the provision of other benefits (for example,\nbuilding poles, fence posts, non-wood forest products such as fruits and fodder, and ecosystem services such as\nsoil conservation and soil fertility). It is important to highlight that labor needed for planting and tending for trees\nis particularly intense for at least the initial three years before they produce an appreciable quantity of biomass.\nThis intervention should target\n\n  - Areas owned by host communities and individuals;\n\n  - Protected areas managed by the NFA; and\n\n  - Areas assigned to the refugees.\n\nMost species can be used for fuel, but quality varies greatly. Some species burn very fast while others produce a\nlot of smoke and are more difficult to dry. In", "source": "fcv_pads_east_africa", "subset": "annotate_aivin_part2", "spans": [{"key": "fcv_pads_east_africa:015700:36:5:0", "start": 132, "end": 139, "surface": "pop2015", "probe_tag": "keep", "probe_score": 0.9656, "luna_label": 1, "luna_reason": "CIESIN 2016 population estimates are used to calculate local population density."}]}, {"key": "aivin2-006", "text": ". The SDR amount remained the same at SDR 218,\n700,000, as was signed in the financing agreement.\n\n\n**3. Relevance of Design**\n\n\n**a. Relevance of Objectives**\n\n\n**Relevance to country context**\n\n\nWhile the combination of _strengthening the crisis response_ and _protecting the most vulnerable_ and _supporting_\n_faster economic recovery_ could be considered overly broad as an objective for a single operation, it made\nsense within the uncertain crisis context of the early days of the COVID-19 pandemic. The financing provided\nthrough this operation was urgently needed to help close a large financing gap, limiting the need for costly\ndomestic borrowing and preventing a more protracted crisis.\n\n\n**The COVID-19 outbreak added to pre-existing economic and social constraints facing Ugandans,**\n**especially the poor and vulnerable households.** Uganda recorded the first confirmed case of COVID-19 on\nMarch 21, 2020. The number of confirmed cases had risen to 460 by June 2, 2020, although a national\nlockdown had started on April 1, 2020. Over three-quarters of the cases reported and hospitalized recovered,\nbut the country’s official record of death from COVID-19 was reported to be heavily underestimated (Lancet,\n2022). With many jobs lost, and livelihoods affected for several months, poverty increased, and economic\n\n\nPage 2 of 19", "source": "fcv_pads_east_africa", "subset": "annotate_aivin_part2", "spans": [{"key": "fcv_pads_east_africa:002332:1:1:0", "start": 1131, "end": 1169, "surface": "official record of death from COVID-19", "probe_tag": "confusion", "probe_score": 0.8303, "luna_label": 1, "luna_reason": "Official COVID-19 death records are cited as heavily underestimated."}]}, {"key": "aivin2-007", "text": "women, youth, people with disabilities, ARRA, UNHCR, NRDEP delegations were participated\n\n\nand engaged. Local officials, kebele administration, host community representatives, regional\n\n\nsteering committee chairman and bureau of agriculture and natural resources and woreda office\n\n\nof environment and forest protection, WSC, WTC and respective level RPCU and WPCU of\n\n\nDRDIP specialists and coordinators were also sources of information’s during focus group\n\n\ndiscussion. A total of 546 of which 93 individuals were engaged.\n\n\nThe consultations were focused on providing information and receiving the concerns and opinions\n\n\nof the participants regarding the overall project objectives, project׳s main and sub- components\n\n\nfor which the SA was prepared. A verbal presentation of the DRDIP objectives and main\n\n\ncomponents were made to the stakeholder and community consultation participants and\n\n\ndiscussions were conducted to identify the adverse environmental and social issues affecting the\n\n\nhost communities and the environment, to capture their concerns, opinions, and to indicate the\n\n\ninstitutional capacity gaps and other constraints that may impede implementation of the SA.\n\n\nFurthermore information was also collected on the workshop by focusing on the existing\n\n\nsituations in terms of integration and collaboration in between the refugee and the host\n\n\ncommunities and hence strengthening the social cohesion among the communities and the\n\n\nresponsible stakeholders and partners. Moreover consultation with project coordination unit and\n\n\nwith stakeholders at woreda and regional level was also held by using telephone communication.\n\n\n**C. Baseline Assessment**\n\n\nThe baseline assessment, previously prepared for implementation of DRDIP I was reviewed and\n\n\nused as the main information source with updating information of newly incorporated kebeles\n\n\nand woredas and city administrations as part of the overall study to prepare this SA document.\n\n\nSecondary data was also collected from DRDIP-II project documents, project baseline survey\n\n\nand midterm impact assessment reports and from federal and regional project performance\n\n\nquarterly and annual reports . The following issues among others which are pertinent with the\n\n\ndevelopment of DRDIP-II have been addressed and incorporated in this SA preparation:\n\n  - Existing", "source": "fcv_pads_east_africa", "subset": "annotate_aivin_part2", "spans": [{"key": "sample:fcv_pads_east_africa:007033:14:0:0", "start": 2033, "end": 2056, "surface": "project baseline survey", "probe_tag": "confusion", "probe_score": 0.1957, "luna_label": 1, "luna_reason": null}, {"key": "sample:fcv_pads_east_africa:007033:14:0:1", "start": 2063, "end": 2096, "surface": "midterm impact assessment reports", "probe_tag": "confusion", "probe_score": 0.1293, "luna_label": 1, "luna_reason": null}, {"key": "sample:fcv_pads_east_africa:007033:14:0:2", "start": 2106, "end": 2177, "surface": "federal and regional project performance\n\n\nquarterly and annual reports", "probe_tag": "confusion", "probe_score": 0.2355, "luna_label": 0, "luna_reason": null}]}, {"key": "aivin2-008", "text": "**Independent Evaluation Group (IEG)** Implementation Completion Report (ICR) Review\nUG-Reproductive Health Voucher Project (P144102)\n\n\nSome of these lessons are drawn from the ICR, while others are drawn from IEG's review of the\nICR.\n\n\n**Lesson from IEG’s review of ICR:**\n\n\nShortcomings in the selection of outcome indicators -- combined with lack of follow-up to address\nthose shortcomings by improving the M&E framework during implementation -- hinder the ability to\nshow achievement of a project’s development objective. This project’s development objective\nspecified a particular target group. However, the ICR (and the M&E results framework it relied upon)\ndid not sufficiently document the extent to which the intended target group – poor women living in\nproject areas – was effectively reached. An M&E system, which would have tracked and assessed\nthe breakdown of actual beneficiaries by poor/non-poor, region, and targeting methodology, would\nhave provided a fuller assessment of PDO achievement. The project’s stated intention (PAD p. 8) to\nundertake systematic monitoring and assessment of the project’s targeting methods, in terms of its\naccuracy and cost-effectiveness in reaching the poor, was not reported on in the ICR. Future\nprojects of this nature may benefit from the review and triangulation of project data with other\navailable and relevant data sources to assess the poor/non-poor breakdown of beneficiaries (e.g.,\ndata from the Office of Auditor General's Audit of the project, and Uganda’s Bureau of Statistics subdistrict poverty maps, 2018, among others).\n\n\n**Lessons from ICR:**\n\n\nEnhanced ownership, coordination and stewardship of the MoH are critical to sustain and build on\nthe innovations and achievements made under any project, especially those piloting innovations. A\nsimilar project would benefit from a Steering Committee led", "source": "fcv_pads_east_africa", "subset": "annotate_aivin_part2", "spans": [{"key": "fcv_pads_east_africa:015291:16:0:0", "start": 1318, "end": 1330, "surface": "project data", "probe_tag": "confusion", "probe_score": 0.3797, "luna_label": 0, "luna_reason": "Future projects are merely advised to review and triangulate project data."}]}, {"key": "aivin2-009", "text": "|Actions|Responsible|Due Date|\n|---|---|---|\n|communities before commencement of the targeted refugee<br>programs||2026|\n|Enhance the GRM system to enable categorization of feedback<br>into enquiries, requests, grievances etc., analyse duration of<br>resolution, number of grievances escalated, and map<br>grievances to youth officers at the county level to enhance<br>speedy resolution|PMU|August 30,<br>2026|\n|**_Communication_**|||\n|Designate focal points from different agencies to support<br>communication team, including regular website updates|All<br>Implementing<br>Agencies|July 15, 2026|\n|Strengthen direct communication to beneficiaries|All<br>Implementing<br>Agencies|Continuous|\n\n\n**Annex 2: Status of actions from previous ISM**\n\n\n\n\n\n\n\n\n\n|Actions|Responsible|Status|\n|---|---|---|\n|**_Component 1: Improving Youth Employability_**|||\n|Development of a minimum standards guidelines for<br>childcare|MOYACES|Done|\n|Integration of childcare and Maternity Income data<br>within the existing beneficiary database|Safaricom/MOYACES|Ongoing|\n|Framework agreements for SESD service providers|MOYACES|Done<br>|\n|Conduct SESD ToT for Lot 1|MoYACES|Done|\n|Complete induction and roll out<br>SESD & OJE for Lot 1<br>|MoYACES|Done|\n|Fast-track direct selection &<br>contracting of umbrella<br>organizations<br>|MoYACES|Done,<br>", "source": "fcv_pads_east_africa", "subset": "annotate_aivin_part2", "spans": [{"key": "fcv_pads_east_africa:003715:14:0:0", "start": 942, "end": 977, "surface": "childcare and Maternity Income data", "probe_tag": "confusion", "probe_score": 0.0942, "luna_label": 0, "luna_reason": "Action-table entry describing ongoing data integration, not substantive data use."}]}, {"key": "aivin2-010", "text": "**Annex 1:** **Project** **Design** **Summary**\n\n**SIERRA LEONE:** **NATIONAL** **SOCIAL ACTION** **PROJECT**\n\n\n. **Hierarchy o.Qbijctives -'**  - . **diator** **r**, t **,P** **jCitidaI** **r!** **As's-umptIons,Y-**\n**Sector-related** **CAS** **Goal:** **Sector** **Indicators:** **Sector/ country reports:** **(from** **Goal** **to Bank** **Mission)**\nMitigate the risk of renewed 1. National conflict/security- - UNHCR/OCHA reports - Continued peace and\n**conflict** **and lay foundation** related indicators - Household Income and regional security\n**for** **poverty reduction and** 2. Inter-regional disparities in Expenditure Surveys - Economic and political\n**improvements** **in nutrition,** I-PRSP & PRSP core - PETS surveys stability\n**health, education** **and** indicators - Strategic Planning and\n**targeting** **the rural** 3. Inter-regional disparities in Action Process (SPP) reports\n**population,** women **and** Popular Benchmarks\n**children.**\n\n\n**Project** **Development** **Outcome** **/** **Impact** **Project reports:** **(from** *", "source": "fcv_pads_east_africa", "subset": "annotate_aivin_part2", "spans": [{"key": "fcv_pads_east_africa:018329:29:0:0", "start": 590, "end": 639, "surface": "Inter-regional disparities in Expenditure Surveys", "probe_tag": "confusion", "probe_score": 0.6578, "luna_label": 0, "luna_reason": "Table indicator fragment, not an analyzed or cited data resource."}, {"key": "fcv_pads_east_africa:018329:29:0:1", "start": 721, "end": 733, "surface": "PETS surveys", "probe_tag": "confusion", "probe_score": 0.8347, "luna_label": 1, "luna_reason": "Named expenditure-tracking surveys cited among reports informing sector indicators."}]}, {"key": "aivin2-011", "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": "fcv_pads_east_africa", "subset": "annotate_aivin_part2", "spans": [{"key": "fcv_pads_east_africa:009739:31:1:0", "start": 170, "end": 184, "surface": "NaCSA M&E data", "probe_tag": "confusion", "probe_score": 0.149, "luna_label": 0, "luna_reason": "Names monitoring data without an attributed finding or demonstrated analytical use."}]}, {"key": "aivin2-012", "text": "**The World Bank**\nUganda Skills Development in Refugee and Host Communities (P176263) PROJECT APPRAISAL DOCUMENT\n\n\n**I.** **STRATEGIC CONTEXT**\n\n\n**A. Project Strategic Context**\n\n\n1. **Uganda’s economy has shown resilience in recent years, rebounding strongly with a growth rate of 6.1 percent in**\n**FY24, up from 5.3 percent in FY23 and 4.7 percent in FY22.** <sup>1</sup> [^1: _Uganda Economic Update 24th Edition : Investing in Early Childhood Development for Transformation of Human Capital in Uganda_\n_(English)._ Washington, D.C. : World Bank Group.] This growth is largely driven by a robust agriculture\nsector, which employs two-thirds of the workforce, as well as increased exports resulting from eased global supply\nchain disruptions following the outbreak of the coronavirus disease (COVID-19) caused by the 2019 novel coronavirus\n(SARS-CoV-2). Despite these positive developments, Uganda remains vulnerable to external shocks. The agriculture\nsector, while a key driver of growth, is highly susceptible to natural disasters and adverse climate events.\n\n\n2. **Uganda’s labor market is characterized by scarce employment opportunities that are concentrated in the informal**\n**sector** . Only 50 percent of the working-age population participate in the labor force, and 48 percent are employed.\nWomen have lower labor force participation (40 percent) than men (56 percent), with rural areas lagging behind\nurban centers. The informal economy dominates employment, with 85 percent of workers engaged in informal\nactivities, primarily subsistence agriculture and small-scale services. <sup>2</sup> [^2: Uganda Bureau of Statistics 2021, The National Labour Force Survey 2021 – Main Report, Kampala, Uganda] Uganda needs to generate 700,000 jobs\nannually to absorb new labor market entrants, yet only 75,000 formal jobs are created each year. <sup>", "source": "fcv_pads_east_africa", "subset": "annotate_aivin_part2", "spans": [{"key": "fcv_pads_east_africa:003796:10:0:0", "start": 1652, "end": 1685, "surface": "National Labour Force Survey 2021", "probe_tag": "confusion", "probe_score": 0.4274, "luna_label": 1, "luna_reason": "Named labor force survey cited for Uganda employment and participation findings."}]}, {"key": "aivin2-013", "text": "The World Bank\n\n\n\n\n\nReport No: ISR12522\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Col1|Col2|Col3|Col4|Col5|by the schools. The response<br>rate from private schools<br>(which have 48% of<br>secondary students has been<br>low (e.g. 64% in 2008; 68% in<br>2009 compared to 100% of<br>public schools due to<br>capitation fund requirements.<br>Over the years, the sector<br>was scaling up the EMIS<br>figures through computational<br>replacements up to the year<br>2010. From 2011 this method<br>was dropped and actual<br>responses are now being<br>used for data generation in a<br>bid to improve data accuracy.<br>The sector in partnership with<br>the Uganda Bureau of<br>Statistics (UBOS) agreed to<br>use the years 2011-12 as<br>observational years for data<br>stability and restart trend<br>analysis with a new baseline<br>using 2013 data.|Col7|\n|---|---|---|---|---|---|---|\n|Boys||Percentage<br>Sub Type<br> Breakdown|Value|28.00|39.00|42.00|\n|Boys||Percentage<br>Sub Type<br> Breakdown|Date|27-Nov-2008|15-Oct-2013|31-Jul-2014|\n|Boys||Percentage<br>Sub Type<br> Breakdown|Comments||||\n|Girls||Percentage<br>Sub Type<br> Breakdown|Value|25.00|35.00|40.", "source": "fcv_pads_east_africa", "subset": "annotate_aivin_part2", "spans": [{"key": "fcv_pads_east_africa:007931:3:0:0", "start": 365, "end": 369, "surface": "EMIS", "probe_tag": "confusion", "probe_score": 0.4287, "luna_label": 1, "luna_reason": "EMIS figures are computationally adjusted and used for sector trend analysis."}, {"key": "fcv_pads_east_africa:007931:3:0:1", "start": 805, "end": 814, "surface": "2013 data", "probe_tag": "confusion", "probe_score": 0.502, "luna_label": 1, "luna_reason": "Existing 2013 data is used to establish a baseline and analyze trends."}]}, {"key": "aivin2-014", "text": "The World Bank\n\n\n\n\n\nReport No: ISR8879\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|Drug Orders processed timely by National<br>Medical Stores|Col2|Percentage|Value|55.00|100.00|80.00|\n|---|---|---|---|---|---|---|\n|Drug Orders processed timely by National<br>Medical Stores||Percentage|Date|04-Oct-2009|31-Oct-2012|31-Jul-2015|\n|Drug Orders processed timely by National<br>Medical Stores||Percentage|Comments||Source: NMS. The delivery<br>system changed and NMS<br>now delivers drugs every two<br>months without waiting for<br>orders anymore.||\n|Pregnant women receiving antenatal care<br>during a visit to a health provider (number)||Number|Value|1200000.00|1380340.00|1400000.00|\n|Pregnant women receiving antenatal care<br>during a visit to a health provider (number)||Number|Date|30-Oct-2009|31-Oct-2012|31-Jul-2015|\n|Pregnant women receiving antenatal care<br>during a visit to a health provider (number)||Number|Comments||Source: 2011/2012 AHSPR||\n|Couple years of protection||Number|Value|549594.00|1841958.00|1000000.00|\n|Couple years of protection||Number|Date|30-Oct-2009|31-Oct-2012|31-Jul-2015|\n|Couple years of protection||Number|Comments||Source: 2011/2012 AHSPR||\n|Health Center IV Performing Caesarian<br>Sections||Percentage|Value", "source": "fcv_pads_east_africa", "subset": "annotate_aivin_part2", "spans": [{"key": "fcv_pads_east_africa:021196:7:0:0", "start": 933, "end": 948, "surface": "2011/2012 AHSPR", "probe_tag": "confusion", "probe_score": 0.5155, "luna_label": 1, "luna_reason": "Named assessment source cited for antenatal-care figures."}]}, {"key": "aivin2-015", "text": "the effects of climate change. As a result of this, the potential for wind related\ndamage is strong on this hill. Removal of more trees due to construction\nactivities could further expose the environment to more wind related damage.\nOld ornamental trees could also pause a danger to property in case of high\nwinds.\n\n\n5.2.3 **Storm** **water:**\n\nMaximum rain intensity of the order of 100 mm per 24 hours has been\nreported. The trend is predicted to continue. The potential for storm water\ndamage and drainage related impacts are high. In particular storm water can\nalso impact on communities down stream of the project area.\n\n**5.2.4** **Air Pollution** **Potential** (APP)\n\nThere was no data to calculate the Air Pollution Potential (APP) for Kampala.\nConsequently data from a nearby station (Entebbe) was used to calculate the\nAPP. Air Pollution Potential (APP) of an area may be defined as the ability or\n\ninability of its atmosphere to disperse or dilute pollutants that may be emitted\ninto it. The APP was evaluated by estimating the ventilation co-efficient (VC)\nas well as the maximum mixing height through out the seasons. This is\nshown in table 1 below:\n\nTable I: Pollution Potential at the nearby station of Entebbe\n\nMonth October January April July\nVentilation Coefficients 1.4 1.1 1.6 1.4\nX 104 M2 S-1\nMaximum mixing 0.5 0.9 0.5 0.6\nheight in km\n\n\nSource: Adapted from S.A.K. Magezi, 1985\n\nAt a nearby station in Entebbe, the lowest APP is exhibited in April and\nOctober while January is the month of highest pollution potential. In all cases,\nthe pollution potential is low (VC higher than 600M2 S-1 or maximum mixing\n\nheight (MMH) < 1.0 km) although occasionally, on specific days,", "source": "fcv_pads_east_africa", "subset": "annotate_aivin_part2", "spans": [{"key": "fcv_pads_east_africa:020281:15:0:0", "start": 766, "end": 802, "surface": "data from a nearby station (Entebbe)", "probe_tag": "confusion", "probe_score": 0.8951, "luna_label": 1, "luna_reason": "Existing station data were used to calculate the Air Pollution Potential."}]}, {"key": "aivin2-016", "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_aivin_part2", "spans": [{"key": "fcv_pads_east_africa:016286:31:0:1", "start": 412, "end": 437, "surface": "NaCSA administrative data", "probe_tag": "confusion", "probe_score": 0.1197, "luna_label": 0, "luna_reason": "Names an administrative data source without showing its data being used."}, {"key": "fcv_pads_east_africa:016286:31:0:2", "start": 1188, "end": 1214, "surface": "NaCSA adrninistrative data", "probe_tag": "confusion", "probe_score": 0.4274, "luna_label": 0, "luna_reason": "Administrative data is listed as a source, without shown analytical use or findings."}]}, {"key": "aivin2-017", "text": ".** **Establishing an effective M&E system was a major challenge for the CORAF**\n**MDTF Project** . The key issue reported in the MTR was the poor quality of the original\nindicators, as discussed earlier. The indicators had to be reformulated before a baseline <sup>27</sup>\ncould finally be established at 2013 (not, ideally, before or at the start of the project). The\ndelay in establishing the baseline led to the delay in completing the restructuring paper\n(March 2014) and the 8-month lag between CORAF’s request and Bank’s approval of the\nreformulated RF. The project, however, did not wait for the officially approved new RF\n(August 2015) before implementing the recommendations of the restructuring paper\n(March 2014) and developing a new M&E manual (November 2014). The indicators in the\nmanual did not exactly follow the order in the approved RF, but their reporting\nsubsequently did.\n\n\n**44.** **The project was severely tested in the implementation of the M&E system.** The\nfirst year of operation (2012) provided no field activities to monitor and no sub-projects’\noutputs to measure. This was because all 8 initial sub-projects approved by CORAF (May\n2011) before approval of the project and officially “launched” (October-November 2011)\nbefore project’s first installment (December 2011), had been delayed for a whole year. The\nimplementation of the M&E was initiated with the arrival of a newly recruited M&E\nmanager and the development of the M&E manual (late 2014). The full implementation\nstarted in earnest in 2015 <sup>28</sup>, with a training related to the new indicators organized in\n\n\n27 The design originally suggested a baseline made of secondary data culled from various published\nreports.\n28 In previous years, the", "source": "fcv_pads_east_africa", "subset": "annotate_aivin_part2", "spans": [{"key": "fcv_pads_east_africa:012341:25:1:0", "start": 1665, "end": 1679, "surface": "secondary data", "probe_tag": "confusion", "probe_score": 0.3246, "luna_label": 0, "luna_reason": "The design only suggested using secondary data for a future baseline."}]}, {"key": "aivin2-018", "text": "<** **84** **1361** **103**\n**Shortfall in Recurrent Buget in US$** <sup>**millons**</sup>\n**-IDA** **(teacher salaries)** **0.0** **0.2** **0.6** **0.6** **0.4** **1.01** **1.0** **1.0** **1** 0 **1.0**\n\n\n\n\n - **Other Donors** **0.1** **0.1** **0.3** **0.5** **0.41** **0.4** **0.61** **0.5'** **0.8** **0.**\nFootnotes:\n\n\n\n**I.** Recurrent costs include all levels of education in addition to Ministry <sup>overheads and cost of other related bodies.</sup>\n2. **Data** in Italics are based on Government simulations as presented <sup>**to**</sup> <sup>donors.</sup>\n3. Mission estimates are **in** bold and are more conservative than **Government** <sup>simulations.</sup>\n**4.** Among other donors France provides **a** sigrnficant amount <sup>of support for Lyc&es, Teacher Training and Higher Education.</sup>", "source": "fcv_pads_east_africa", "subset": "annotate_aivin_part2", "spans": [{"key": "fcv_pads_east_africa:015526:8:5:0", "start": 494, "end": 516, "surface": "Government simulations", "probe_tag": "confusion", "probe_score": 0.7941, "luna_label": 1, "luna_reason": "Existing government simulations are cited as the basis for italicized data."}]}, {"key": "aivin2-019", "text": "**The World Bank**\nAdditional Financing Ethiopia Electrification Program (P178895)\n\n\naffordability constraints have not kept them from making new connections to date, they anticipate\naffordability may present a constraint in the medium-to-long term. Namely, as the grid reaches more\nremote areas, the cost of new connections is expected to rise (with lower population density in\nunelectrified areas) <sup>8</sup> [^8: EEU sets the customer connection fee based on an estimate which an EEU technician conducts on-site.] . Simultaneously, disposable income of potential customers in these areas will likely\ndecrease as the grid reaches increasingly remote areas. These two factors combined are expected to\npresent an affordability barrier and this requires further investigation to identify the capacity that\npotential customers will have to afford connections, as well as to identify ways to mitigate the potential\nimpact through potential cross-subsidization of the connection fee. Given that recent and reliable data on\naffordability of connection costs does not exist, both EEU and the World Bank have recognized the need\nto conduct a connection cost affordability study to be conducted in the first year of the proposed\noperation.\n\n24. **Despite the lack of utility data, a 2017 study on affordability** <sup>**9**</sup> [^9: Willingness to Pay Completion Report; USAID Ethiopia/ Beyond-the-grid (August 2017).] **can provide some approximate**\n**insight.** This survey of 150 unelectrified towns across 4 regions studied the willingness to pay (WTP) for\nelectricity services by households. The results of the survey indicate wide variability in WTP within towns\nas well as across town. Within towns, the figure below shows a steep decline in WTP after ~15 percent,\nfollowed by gradual decline thereafter. Similarly, the survey also found variability across towns. The study\ncites that a 30 percent benchmark is typically used in tariff setting for initial market penetration. At this\n30 percent mark, WTP varied across the towns from US$ 1", "source": "fcv_pads_east_africa", "subset": "annotate_aivin_part2", "spans": [{"key": "fcv_pads_east_africa:006232:11:0:0", "start": 1013, "end": 1054, "surface": "data on\naffordability of connection costs", "probe_tag": "confusion", "probe_score": 0.6204, "luna_label": 0, "luna_reason": "States reliable affordability data does not exist and only motivates future study."}, {"key": "fcv_pads_east_africa:006232:11:0:1", "start": 1261, "end": 1273, "surface": "utility data", "probe_tag": "confusion", "probe_score": 0.7635, "luna_label": 0, "luna_reason": "States lack of utility data; no finding or substitute analysis uses it."}]}, {"key": "aivin2-020", "text": "|ANNEX 3 APPENDIX 1. Question that the Team Would|AN ASSESSMENT OF THE DATA 18  Data Constraint(s)|E HOUSEHOLD SURVEY Question that the Team is Able to|\n|---|---|---|\n|_Question that  the Team Would_<br>_Like to Answer _<br>|_Data Constraint(s) _<br>|_Question that the Team is Able to_<br>_Answer _<br>|\n|<br>What were the (household)<br>characteristics of NAADS<br>beneficiaries? <br>|The team did not have access to<br>a nationally representative<br>household survey. The<br>organization that collected the<br>data has informed the ICR team<br>that before they undertook the<br>survey, they were given a list of<br>districts from which they were<br>supposed to collect the sample<br>of member and non-member<br>households. <br>|<br>What were the (household)<br>characteristics of NAADS<br>beneficiaries in the_non-_<br>_representative sample_surveyed? <br>|\n|How did the program change<br>after the distribution of inputs<br>became less equitable (i.e. post<br>2007)? <br>|<br>No household survey data is<br>available after 2007. The last<br>official (nationally<br>representative) household<br>survey is from 2005. <br>|Reports from field visits provide<br>limited (i.e. anecdotal), but useful<br>evidence. <br>|\n|How is the nature of group<br", "source": "fcv_pads_east_africa", "subset": "annotate_aivin_part2", "spans": [{"key": "fcv_pads_east_africa:019701:52:0:2", "start": 983, "end": 1004, "surface": "household survey data", "probe_tag": "confusion", "probe_score": 0.7318, "luna_label": 0, "luna_reason": "States household survey data are unavailable, without analyzed findings or substitute estimates."}]}, {"key": "aivin2-021", "text": " new\neducation law (approved in August 2000) sets in place the conditions for broadening participation in\nDjibouti's education system. It provides for setting up school management committees with parent\n\nand community involvement. The law also provides for the creation of conditions to increase private\nsector participation in education.\n\n\n_6.3 How does the project involve consultations or collaboration with NGOs or other civil society_\n_organizations?_\n\n\nThe National Educational Forum consulted all stakeholders including NGOs and civil society during\nthe initial preparation. In addition, the project foresees the increased involvement of parent\nassociations or community-based associations in the management of project activities on the ground\n(i.e., operations & maintenance).\n\n\n_6.4 What institutional arrangements have been provided to ensure the project achieves its social_\n_development outcomes?_\n\n\nThe DGEN will be responsible for monitoring the gender gap in enrollment issues, and the gap\nbetween the poorest and the richest quintiles, and related education services available to them. The\ndata collection on enrollment will be strengthened by the capacity building support provided to the\nMinistry of Education's planning unit - thus over time these issues can be effectively monitored.\nTriggers are included in the APL phasing to ensure that various social development goals are met e.g.\ndecreasing the enrollment gap between the rich and the poor, decreasing the gender gap and increasing\ncommunity participation in school management.\n\n\n_6.5 How will the project monitor performance in terms of social development outcomes?_\n\n\nThe MOE planning unit will monitor enrollment paying attention to gender gaps, socioeconomic gaps\n\nand performance of students by socioeconomic class through use of surveys of students.", "source": "fcv_pads_east_africa", "subset": "annotate_aivin_part2", "spans": [{"key": "fcv_pads_east_africa:018131:24:1:0", "start": 1811, "end": 1830, "surface": "surveys of students", "probe_tag": "confusion", "probe_score": 0.4274, "luna_label": 0, "luna_reason": "Planned monitoring through student surveys, with no existing finding or cited survey."}]}, {"key": "aivin2-022", "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_aivin_part2", "spans": [{"key": "sample:fcv_pads_east_africa:009765:62:2:0", "start": 688, "end": 697, "surface": "1999 data", "probe_tag": "confusion", "probe_score": 0.5672, "luna_label": 0, "luna_reason": null}, {"key": "sample:fcv_pads_east_africa:009765:62:2:1", "start": 758, "end": 796, "surface": "Development Economics central database", "probe_tag": "keep", "probe_score": 0.9023, "luna_label": 1, "luna_reason": null}]}, {"key": "aivin2-023", "text": "1. **Project alternatives** **considered** **and reasons for rejection:**\nDesln Alternative 1: Discontinue IDA support for the Emergency Recovery Support Fund\n(ERSF) and its successor, the National Social Action Project (NSAP). This option was rejected because\navailable evidence suggests that the on-going Community Reintegration and Rehabilitation Project\n(CRRP Cr. 3312-SL) has been successful. Although definitive audit and evaluation data are not yet\navailable, CRRP financed over 250 sub-projects that benefited extremely poor and devastated\ncommunities, including some areas of the country where security was marginal at best. NaCSA has been\nthe Government entity that has delivered much needed support to the population\n\n\nDesign Alternative 2: Withhold IDA support for NaCSA's newly-instituted Public Works\nProgram. This option was rejected for three reasons. First, the need to restore infrastructure beyond the\ncommunity sub-projects is urgent, especially in the newly accessible areas. Proposed works (e.g.\nrehabilitation of feeder roads and drainage systems) would complement other projects currently being\nimplemented by NaCSA. Second, IDA support for this program would provide an opportunity for\nNaCSA to develop a capacity building program for local administrators. This initiative, in the context of\nthe Public Works Program, would support the Government's decentralization policy and introduce a\nresults-based model of governance at the local level that would facilitate the gradual delegation of\nadditional implementation responsibilities to local authorities. Finally, labor intensive techniques will be\nused to employ ex-combatants and unemployed youth, to reduce the risk that they would turn to\nnon-legitimate income generating activities if they remain unemployed.\n\n\nDesien Alternative 3: Provide support for NaCSA's micro-credit program. The AfDB will\ncontinue to support micro-finance activities through the Government's Social Action and Poverty\nAlleviation (SAPA) program. A mnicro-finance policy", "source": "fcv_pads_east_africa", "subset": "annotate_aivin_part2", "spans": [{"key": "fcv_pads_east_africa:020366:15:0:0", "start": 418, "end": 443, "surface": "audit and evaluation data", "probe_tag": "confusion", "probe_score": 0.2983, "luna_label": 0, "luna_reason": "States data are unavailable without citing an analyzed finding or substitute use."}]}, {"key": "aivin2-024", "text": ") for Mekelle**<br>**Multi-Purpose Land Information System**<br>**(Cadastre) and LAN**|||||||\n||||||||\n|**1.20. Materials for LAN for Mekelle Multi-**<br>**Purpose Land Information System**<br>**(Cadastre)**|**UDCBO/P24-07**||**26,011**|**NS**|**Post**|**Post**|\n|**1.20. Materials for LAN for Mekelle Multi-**<br>**Purpose Land Information System**<br>**(Cadastre)**|||||||\n|**1.20. Materials for LAN for Mekelle Multi-**<br>**Purpose Land Information System**<br>**(Cadastre)**|||||||\n||||||||\n|**1.21. Hardware and software for Addis**<br>**Ababa Interfacing and Integrating digital**<br>**maps with attribute data**|**UDCBO/P25-07**||**150,000**|**NCB**|**Post**|**Post**|\n|**1.21. Hardware and software for Addis**<br>**Ababa Interfacing and Integrating digital**<br>**maps with attribute data**|||||||\n|**1.21. Hardware and software for Addis**<br>**Ababa Inter", "source": "fcv_pads_east_africa", "subset": "annotate_aivin_part2", "spans": [{"key": "fcv_pads_east_africa:014089:0:6:0", "start": 593, "end": 617, "surface": "maps with attribute data", "probe_tag": "drop", "probe_score": 0.0082, "luna_label": 0, "luna_reason": "Fragment inside a procurement table, not an independent data-use mention."}]}, {"key": "aivin2-025", "text": "Goods: 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", "source": "fcv_pads_east_africa", "subset": "annotate_aivin_part2", "spans": [{"key": "sample:fcv_pads_east_africa:001393:2:0:0", "start": 59, "end": 82, "surface": "Procurement Plan\ntables", "probe_tag": "drop", "probe_score": 0.0014, "luna_label": 0, "luna_reason": null}, {"key": "sample:fcv_pads_east_africa:001393:2:0:1", "start": 145, "end": 168, "surface": "Procurement Plan\ntables", "probe_tag": "drop", "probe_score": 0.0002, "luna_label": 0, "luna_reason": "Procurement plan tables are routine project procurement documentation, not substantive data use."}]}, {"key": "aivin2-026", "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": "fcv_pads_east_africa", "subset": "annotate_aivin_part2", "spans": [{"key": "fcv_pads_east_africa:010697:4:0:0", "start": 1106, "end": 1128, "surface": "Project Financing Data", "probe_tag": "drop", "probe_score": 0.0462, "luna_label": 0, "luna_reason": "Standalone project financing table header, not a data-use mention."}]}, {"key": "aivin2-027", "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_aivin_part2", "spans": [{"key": "fcv_pads_east_africa:014483:62:2:0", "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 concrete analytical use."}]}, {"key": "aivin2-028", "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_aivin_part2", "spans": [{"key": "fcv_pads_east_africa:010177:62:2:0", "start": 688, "end": 697, "surface": "1999 data", "probe_tag": "drop", "probe_score": 0.0227, "luna_label": 0, "luna_reason": "Generic data qualifier lacks an attributed finding or concrete analytical use."}, {"key": "fcv_pads_east_africa:010177:62:2:1", "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 producing the table's economic data."}]}, {"key": "aivin2-029", "text": "Annex 1\nPage 2 of 3\n\n\n**Project Development** **Outcome / Impact** **Project reports:** **(from Objective to Purpose'**\n**Objective:** **Indicators:**\nExpand access to basic Increased number of school Project Reports. It is assumed that\neducation. places. Government's current fiscal\nsituation will be resolved\n\n(salary payment to civil\nservants and teachers).\nEnrollment increases in MOE reports. Expansion of facilities and\nprimary schools from 35,000 quality will contribute to\nto 80,000 increased enrollment\nincluding among girls.\nIncreased availability of It is assumed that the\ntextbooks. Government maintains\ndouble-shifting.\n\n\nTrained primary school head Headteachers have autonomy\nteachers. and authority in managing the\nschools.\nBetter trained contractual Contractual teachers are\nteachers recruited early enough before\nthe school year to allow time\nfor training.\n\n\n**Output from each** **Output Indicators:** **Project reports:** **(from Outputs to Objective)**\n**Component:**\nIncreased number of school 226 classrooms will be built Monthly disbursement Availability of school places\nplaces. increasing capacity by over summary. will increase enrollment.\n20,000 based on double\nshifting.\nProvide textbooks. Numbers of textbooks per Semi-annual Provision of textbooks will\npupil increases. supervision reports. improve learning.\nTrained primary school head- Primary school head-teachers Annual audit reports; Better trained head-teachers\nteachers. trained and Guidebook for site visits. will improve school\nschool management prepared efficiency.\nand distributed.", "source": "fcv_pads_east_africa", "subset": "annotate_aivin_part2", "spans": [{"key": "fcv_pads_east_africa:009912:30:0:0", "start": 385, "end": 396, "surface": "MOE reports", "probe_tag": "drop", "probe_score": 0.0342, "luna_label": 1, "luna_reason": "Reports are cited as evidence for increased enrollment."}]}, {"key": "aivin2-030", "text": "- **_The procurement is open to eligible firms from any country;_**\n\n\n  - **_The request for bids/Proposal documents shall require that_**\n\n\n**_bidders/proposers submitting Bids/Proposal present a signed_**\n\n\n**_acceptance at the time of bidding, to be incorporated in any_**\n\n\n**_resulting contracts, confirming application of and compliance_**\n\n\n**_with the Bank’s Anti-Corruption Guidelines, including without_**\n\n\n**_limitation the bank’s right to sanction and the Bank’s inspection_**\n\n\n**_and audit right;_**\n\n\n  - **_Contracts with an appropriate allocation of responsibilities, risks_**\n\n\n**_and liabilities;_**\n\n\n  - **_Application of Standstill period and Publication of contract award_**\n\n\n**_information;_**\n\n\n  - **_Maintenance of records of the procurement process; and_**\n\n\n  - **_The Bank has the right to review procurement documentation_**\n\n\n**_and activities._**\n\n\nWhen other national procurement arrangements other than national open\ncompetitive procurement arrangements are applied by the Borrower, such\narrangements shall be subject to paragraph 5.5 of the Procurement\nRegulations.\n\n\n**_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. **_“Not Applicable”_**\n\n\n**_Procurement of Second-Hand Goods_** **_as specified under paragraph_**\n**_5.11_** of the Procurement Regulations – is allowed for those contracts identified\nin the Procurement Plan tables _“_ **_Not Applicable”_**\n\n\n**_Domestic preference as specified under paragraph 5.51_*", "source": "fcv_pads_east_africa", "subset": "annotate_aivin_part2", "spans": [{"key": "fcv_pads_east_africa:005043:1:0:0", "start": 1250, "end": 1273, "surface": "Procurement Plan tables", "probe_tag": "drop", "probe_score": 0.0126, "luna_label": 0, "luna_reason": "Routine procurement planning documentation, not substantive data use."}]}, {"key": "aivin2-031", "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": "fcv_pads_east_africa", "subset": "annotate_aivin_part2", "spans": [{"key": "sample:fcv_pads_east_africa:012483:16:0:0", "start": 379, "end": 395, "surface": "statistical data", "probe_tag": "confusion", "probe_score": 0.582, "luna_label": 0, "luna_reason": null}, {"key": "sample:fcv_pads_east_africa:012483:16:0:1", "start": 1487, "end": 1500, "surface": "random survey", "probe_tag": "drop", "probe_score": 0.012, "luna_label": 0, "luna_reason": "Project staff will carry out the survey to establish a future baseline."}]}, {"key": "aivin2-032", "text": "also be provided to properly levy, collect and account for local duties and taxes. NaCSA staff would be\ngiven an opportunity to visit Community Driven Development Projects in comparable countries to\ncapitalize on their experiences. Regional and district line ministry staff would be trained in community\nmobilization, conflict resolution, social capital building, and technical appraisal skills.\n\n\n(b) Substantial IEEC activities linked to the various sub-projects are envisaged. These activities\nwould be undertaken using existing IEC materials endorsed by the various line ministries. For example,\nin the case of the rehabilitation of a health post, IEC messages could be envisaged to inform the\npopulation on the proper use of insecticide treated bed nets as a means of preventing malaria.\n\n\n(c) Monitoring and evaluation at the community, district, regional and central levels would be\ngiven high priority, and linked regularly and directly with NaCSA decision making on NSAP policy,\nstrategy and operational matters. These activities would be directly undertaken, or commissioned by,\nstaff of NaCSA's Planning, Monitoring and Evaluation Directorate. The Project Design Matrix (logical\nframework, Annex 1) would form the basis for monitoring NSAP outputs, outcomes and impact. An\nassessment of project status would accompany each NaCSA work program and budget submitted\nsemi-annually to the NaCSA Board. Other M&E activities would include a pre-project Social\nAssessment; establishment of NSAP baseline data (in conjunction with the collection of data for the\nCRRP Implementation Completion Report); social assessments during implementation; annual technical\naudits; beneficiary assessments; incorporation of NaCSA into GOSL's semi-annual public expenditure\ntracking surveys (PETS); and independent impact assessments.\n\n\nIn addition to conventional sub-project monitoring and evaluation (incorporated in the\nsub-project cycle as outlined in the Operations Manual), a pilot participatory monitoring and evaluation\nsystem would be introduced in a representative sample of the predominant types of CDP sub-projects.\nBeneficiary communities would identify quantitative and qualitative indicators", "source": "fcv_pads_east_africa", "subset": "annotate_aivin_part2", "spans": [{"key": "fcv_pads_east_africa:014928:36:0:0", "start": 1493, "end": 1511, "surface": "NSAP baseline data", "probe_tag": "drop", "probe_score": 0.0301, "luna_label": 0, "luna_reason": "Establishing baseline data is a planned project data-production activity."}]}, {"key": "aivin2-033", "text": "Annex 1\nPage 2 of 3\n\n\n**Project Development** **Outcome / Impact** **Project reports:** **(from Objective to Purpose'**\n**Objective:** **Indicators:**\nExpand access to basic Increased number of school Project Reports. It is assumed that\neducation. places. Government's current fiscal\nsituation will be resolved\n\n(salary payment to civil\nservants and teachers).\nEnrollment increases in MOE reports. Expansion of facilities and\nprimary schools from 35,000 quality will contribute to\nto 80,000 increased enrollment\nincluding among girls.\nIncreased availability of It is assumed that the\ntextbooks. Government maintains\ndouble-shifting.\n\n\nTrained primary school head Headteachers have autonomy\nteachers. and authority in managing the\nschools.\nBetter trained contractual Contractual teachers are\nteachers recruited early enough before\nthe school year to allow time\nfor training.\n\n\n**Output from each** **Output Indicators:** **Project reports:** **(from Outputs to Objective)**\n**Component:**\nIncreased number of school 226 classrooms will be built Monthly disbursement Availability of school places\nplaces. increasing capacity by over summary. will increase enrollment.\n20,000 based on double\nshifting.\nProvide textbooks. Numbers of textbooks per Semi-annual Provision of textbooks will\npupil increases. supervision reports. improve learning.\nTrained primary school head- Primary school head-teachers Annual audit reports; Better trained head-teachers\nteachers. trained and Guidebook for site visits. will improve school\nschool management prepared efficiency.\nand distributed.", "source": "fcv_pads_east_africa", "subset": "annotate_aivin_part2", "spans": [{"key": "fcv_pads_east_africa:010477:30:0:0", "start": 385, "end": 396, "surface": "MOE reports", "probe_tag": "drop", "probe_score": 0.0342, "luna_label": 1, "luna_reason": "MOE reports support the stated enrollment increase."}]}, {"key": "aivin2-034", "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_aivin_part2", "spans": [{"key": "sample:fcv_pads_east_africa:019286:31:0:0", "start": 226, "end": 240, "surface": "NaCSA M&E data", "probe_tag": "drop", "probe_score": 0.0002, "luna_label": 0, "luna_reason": null}, {"key": "sample:fcv_pads_east_africa:019286:31:0:1", "start": 412, "end": 437, "surface": "NaCSA administrative data", "probe_tag": "drop", "probe_score": 0.0006, "luna_label": 0, "luna_reason": null}, {"key": "sample:fcv_pads_east_africa:019286:31:0:2", "start": 1188, "end": 1214, "surface": "NaCSA adrninistrative data", "probe_tag": "confusion", "probe_score": 0.4531, "luna_label": 0, "luna_reason": null}]}, {"key": "aivin2-035", "text": "**The World Bank** Implementation Status & Results Report\nENREP- Carbon Finance Programme of Activities (P155859)\n\n\n**Project Development Objective Indicators**\n\n\n\n\n\n\n\n\n\n\n\n\n\n**Intermediate Results Indicators**\n\n\n\n\n\n\n\n\n\n**Data on Financial Performance**\n\n\n12/27/2019 Page 2 of 3", "source": "fcv_pads_east_africa", "subset": "annotate_aivin_part2", "spans": [{"key": "fcv_pads_east_africa:017377:1:0:0", "start": 221, "end": 250, "surface": "Data on Financial Performance", "probe_tag": "drop", "probe_score": 0.007, "luna_label": 0, "luna_reason": "Standalone section header, not a cited or analyzed data resource."}]}, {"key": "aivin2-036", "text": "<mark>Table 1. Household surveys used for poverty measurement</mark>\n\n\n<u><mark>Country</mark></u> <u><mark>Name of survey</mark></u> <u><mark>Coverage</mark></u>\n<mark>Argentina</mark> <mark>Encuesta Permanente de Hogares-Continua</mark> <mark>Urban, 31 cities</mark>\n<mark>Bolivia</mark> <mark>Encuesta Continua de Hogares-MECOVI</mark> <mark>National</mark>\n<mark>Brazil</mark> <mark>Pesquisa Nacional por Amostra de Domicilios</mark> <mark>National</mark>\n<mark>Chile</mark> <mark>Encuesta de Caracterización Socioeconómica Nacional</mark> <mark>National</mark>\n<mark>Colombia</mark> <mark>Gran Encuesta Integrada de Hogares</mark> <mark>National</mark>\n<mark>Costa Rica</mark> <mark>Encuesta Nacional de Hogares</mark> <mark>National</mark>\n<mark>Dom. Rep.</mark> <mark>Encuesta Nacional de Fuerza de Trabajo</mark> <mark>National</mark>\n<mark>Ecuador</mark> <mark>Encuesta de Empleo, Desempleo, y Subempleo</mark> <mark>National</mark>\n<mark>El Salvador Encuesta de Hogares de Propósitos Mútiples</mark> <mark>National</mark", "source": "general_prwp", "subset": "annotate_aivin_part2", "spans": [{"key": "prwp:007087:24:0:5", "start": 594, "end": 628, "surface": "Gran Encuesta Integrada de Hogares", "probe_tag": "keep", "probe_score": 0.9142, "luna_label": 0, "luna_reason": "Survey name appears as a standalone entry in a table."}]}, {"key": "aivin2-037", "text": " the factor\nloadings. To tackle this problem, Shi and Lee (2017) develop a bias correction that\nyields an asymptotically normal, properly-centered estimator. The estimations reported\nbelow using common factors employ the bias-corrected estimator.\n\n#### **3 Data**\n\n\nWe assess the international comovement of equity returns using a balanced panel data\nset comprising 40 advanced and emerging countries over 1995:1 to 2016:3    - a total of\n3,480 quarterly observations. Because advanced countries tend to exhibit higher real\nand financial openness, as well as larger and more liquid financial markets, than other\ncountries, we consider separately a subsample of 25 advanced economies, comprising\n2,175 observations. Table A1 in the appendix provides the complete list of countries.\nFollowing Hirata, Kose, Otrok and Terrones (2013), we measure equity prices by the\nstock market price index for each country. Real equity returns are then given by the first\ndifference of the log of equity prices deflated by the consumer price index. <sup>9</sup> We collect\nthe equity price index data from the OECD Statistics Database, except in the cases of\nArgentina, Hong Kong and Peru, for which we draw the data from Investing.com. <sup>10</sup>\n\nFigure 1 depicts the cross-country average of the real equity returns. It displays very\nsimilar fluctuations over the two country samples, including a sharp decline around the\nfourth quarter of 2008, at the onset of the global crisis.\n\nAs already mentioned, we consider three covariates of equity returns: real GDP,\nshort term interest rates and private credit. The GDP data comes from the OECD\nStatistics Database and the International Financial Statistics (IFS) of IMF and\ncomplemented with national statistics sources as well as the Federal Reserve Bank of\nSt. Louis Economic Data (FRED). Credit is measured by domestic credit to the\nprivate sector,", "source": "general_prwp", "subset": "annotate_aivin_part2", "spans": [{"key": "prwp:007442:9:3:3", "start": 1195, "end": 1218, "surface": "data from Investing.com", "probe_tag": "keep", "probe_score": 0.9075, "luna_label": 1, "luna_reason": "Investing.com data provide equity price inputs for calculated real returns."}, {"key": "prwp:007442:9:3:5", "start": 1771, "end": 1818, "surface": "Federal Reserve Bank of\nSt. Louis Economic Data", "probe_tag": "keep", "probe_score": 0.9836, "luna_label": 1, "luna_reason": "Named economic database used as a source for GDP data."}]}, {"key": "aivin2-038", "text": "for European exporters. <sup>1</sup> Since 2009, trade liberalization on the Serbian side has been\n\n\nfollowing a gradual and predictable liberalization schedule and by 2013, most EU imports\n\n\nenter tariff-free. The EU is a main market for inputs for Serbian firms, and its importance is\n\n\nfurther amplified as European foreign direct investment locates in Serbia to produce for the\n\n\nEuropean market, especially after this trade agreement came into force. One key example is\n\n\nthe decision of Fiat, an Italian car manufacturer, to locate its worldwide production of the\n\n\ncar model _Fiat500_ in Serbia in 2010, which requires them to import components from many\n\n\ncountries. Serbia also signed another trade agreement with its neighbors in the Western\n\n\nBalkans regions in 2006 but these markets are less important as input sources.\n\n\nWe show that Serbian importers are increasing in their intensive and extensive margins\n\n\nbetween 2006 and 2015, using data on Serbian firms from the Business Registries Agency\n\n\n(BRA) combined with data provided by the Serbian Customs Administration. Table 1\n\n\npresents the total value of Serbian imports between 2006 and 2015 as well as the average\n\n\nimports of a firm-origin country pair and the total number of firm-origin country pairs.\n\n\nOver the period, all three measures are increasing, which suggests that the increase in total\n\n\nimports is due to both increases in the intensive margin (value of firms’ imports from each\n\n\nof their source countries) and extensive margin (number of countries firms source from).\n\n\nSerbian firms are increasingly making sourcing decisions that cross international borders.\n\n\nThe sourcing choice of the firm is significant because the basket of inputs and sources it\n\n\nchooses impact production costs, product quality, and subsequently the competitiveness of\n\n\nthe firm. Both margins are incorporated in our empirical framework, which we describe in\n\n\ndetail below. The increases in the intensive margin are incorporated into firm learning (with\n\n\na lag, as in Fernandes and Tang (2014)) because changes in other firms’ imports from a\n\n\nsource act as", "source": "general_prwp", "subset": "annotate_aivin_part2", "spans": [{"key": "prwp:001737:7:0:0", "start": 953, "end": 974, "surface": "data on Serbian firms", "probe_tag": "keep", "probe_score": 0.9269, "luna_label": 1, "luna_reason": "Firm data from Serbia’s Business Registries Agency underpin import-margin analysis."}]}, {"key": "aivin2-039", "text": ".029*** -0.030*** -0.025***\n(0.008) (0.007) (0.007)\nEconomically active [18-65] 0.787 0.749 0.037*** 0.027*** 0.022***\n(0.005) (0.005) (0.004)\nFormal employment [18-65] 0.746 0.743 0.003 0.001 -0.009\n(0.007) (0.007) (0.006)\nUnemployment [18-65] 0.061 0.061 0.000 0.001 0.001\n(0.003) (0.003) (0.003)\nHealth insurance 0.639 0.639 0.000 0.008 -0.002\n(0.007) (0.007) (0.007)\nNumber of disabilities 0.214 0.198 0.016*** 0.034*** 0.039***\n(0.005) (0.005) (0.005)\nTeen pregnancy [14-19] 0.098 0.112 -0.014 -0.014* -0.012\n<u>(0.009)</u> <u>(0.008)</u> <u>(0.008)</u>\n\n\n\nSource: REDATAM INDEC Census Argentina 2010. SE clustered at department level in parenthesis. Column 4 includes gender\nand age fixed effects and column 5 also includes department and urban fixed effects. - _p <_ 0.10, ** _p <_ 0.05, *** _p <_ 0.01.\n\n\n30", "source": "general_prwp", "subset": "annotate_aivin_part2", "spans": [{"key": "prwp:001387:31:1:0", "start": 570, "end": 605, "surface": "REDATAM INDEC Census Argentina 2010", "probe_tag": "keep", "probe_score": 0.9671, "luna_label": 1, "luna_reason": "Source line identifies the census underlying the presented regression table."}]}, {"key": "aivin2-040", "text": "_Table 3: Distribution of annual household expenditures between GLSS6 (GAMA) and Poverty-DRM sur-_\n_veys in Ghana by quartile_\n\n\nQuartile GLSS6 (GAMA) in cedis Poverty-DRM in cedis\n\n\nQ1 2,115 2,248\n\n\nQ2 3,810 3,907\n\n\nQ3 5,781 5,904\n\n\nQ4 10,715 11,988\n\n\nSource: Authors' estimation using GLSS6 and Poverty-DRM surveys\n\n\nHousehold heads in our sample are more likely to be women and have a lower education level than those\nof the GLSS6 sample for the full GAMA area. Further, households in our sample live in relatively smaller\ndwellings despite having the same number of household members, indicating that households are more\ndensely crowded in the surveyed areas than in the rest of the city.\n\n\nHouseholds surveyed appear to have a lower access to services than the rest of city. For instance, the use\nof public toilets is significantly higher for slum-dwellers than for Accra residents overall. While 32% of\nhouseholds in the GLSS6 survey reported using public toilets as their main toilet facility, the number for\nthe DRM survey is 67%. The primary source of drinking water in the slum areas is sachet water, which is\neven more prevalent (at 70%) than in the rest of the city (54%). Most households (74%) reported having\ntheir waste collected, a high level for an informal settlement.\n\n\nAlmost half of the households (44%) reported being directly affected by the 2015 flood. As expected,\nmore households in the low elevation areas were affected by the flood. However, many households in the\nhigh elevation areas (29%) were also affected. These results confirm that elevation is not a good proxy for\nflood exposure in Accra. This is because flood risk is associated with characteristics other than elevation,\nsuch as insufficient drainage infrastructure, or poor waste management", "source": "general_prwp", "subset": "annotate_aivin_part2", "spans": [{"key": "prwp:007403:13:0:1", "start": 297, "end": 316, "surface": "Poverty-DRM surveys", "probe_tag": "keep", "probe_score": 0.9428, "luna_label": 1, "luna_reason": "Source surveys underpin authors’ expenditure estimates and reported findings."}, {"key": "prwp:007403:13:0:4", "start": 1020, "end": 1030, "surface": "DRM survey", "probe_tag": "keep", "probe_score": 0.9538, "luna_label": 1, "luna_reason": "Existing survey provides the reported 67 percent public-toilet-use finding."}]}, {"key": "aivin2-041", "text": "The Central American sub-region is of interest not only because of its high levels of\nincome inequality, but also because of its heterogeneity and the fact that several countries have\nonly recently emerged from civil war. The sub-region comprises two upper middle income\ncountries (Costa Rica and Panama), two lower middle income countries (El Salvador and\nGuatemala) and two low income countries (Honduras and Nicaragua). Further, Guatemala and\nHonduras have a sizeable proportion of indigenous population, while Honduras and Nicaragua\nalso have people of Afro-Caribbean origin. Both these groups have traditionally had limited\naccess to tertiary education. Since the early 1990s, the focus in almost all countries (with the\npossible exception of Panama), especially those affected by civil war (El Salvador, Guatemala\nand Nicaragua) has been on promoting basic education, often using innovative models to expand\ncoverage. The situation regarding tertiary education is different: on the one hand, there have been\nfew policy changes with respect to public tertiary education while, on the other, the private sector\nhas expanded rapidly. There has been no systematic analysis of the progress made in tertiary\neducation, particularly for lower income and indigenous groups.\n\nOur study relies heavily on household surveys but also draws on analysis of public\nspending data and qualitative studies of the participation of indigenous people in tertiary\neducation in Nicaragua and Guatemala. <sup>6</sup> [^6: These analyses were also undertaken as part of the World Bank’s study on equity in tertiary education.] We begin by examining the growth in average education\nattainment and different measures of education inequality, as well as inter-generational and intragenerational inequality. Next, we present the progress of tertiary education attainment over time,\nenrollment and completion rates by income quintiles and the participation of indigenous people.\nThis is followed by an examination of labor market outcomes for tertiary education graduates.\nThe following section analyses the key obstacles to reaching tertiary education for students from\ndifferent backgrounds across the education cycle. Finally, we evaluate the level and role of public", "source": "general_prwp", "subset": "annotate_aivin_part2", "spans": [{"key": "prwp:005345:4:0:1", "start": 1349, "end": 1369, "surface": "public\nspending data", "probe_tag": "keep", "probe_score": 0.9267, "luna_label": 1, "luna_reason": "Existing public spending data are explicitly used as the study’s analytical source."}]}, {"key": "aivin2-042", "text": "|||||||||||||||||||\n|0<br>.5<br>1<br>1<br>.<br>D<br>e<br>n<br>s<br>ity<br>~~1~~<br>~~**3**~~<br>~~5~~<br>0<br>~~1~~<br>~~5~~<br>**Experimental Firms, mean=**<br>**Management score**|||||||||||||||||||||||\n\n\n\n**Notes:** Management practice histograms using Bloom and Van Reenen (2007) methodology. Double-blind surveys used to\nevaluate firms’ monitoring, targets and operations. Scores from 1 (worst practice) to 5 (best practice). Samples are 695 US firms,\n620 Indian firms, 1083 Brazilian and Chinese firms, 232 Indian textile firms and 17 experimental firms.\n\n\n\n\n\n\n\n\n\n\n\nthe 14 treatment plants (diamond symbol), 6 control plants (plus symbol), the 5 non-experimental plants in the treatment firms\nwhich the consultants did not provide any direct consulting assistance to (round symbol) and the 3 non-experimental plants in the\ncontrol firms (square symbol). Scores range from 0 (if none of the group of plants have adopted any of the 38 management\npractices) to 1 (if all of the group of plants have adopted all of the 38 management practices). Initial differences across all the\ngroups are not statistically significant.", "source": "general_prwp", "subset": "annotate_aivin_part2", "spans": [{"key": "prwp:004757:39:10:0", "start": 297, "end": 317, "surface": "Double-blind surveys", "probe_tag": "confusion", "probe_score": 0.3413, "luna_label": 1, "luna_reason": "Surveys are used to evaluate firms’ management practices and produce scores."}]}, {"key": "aivin2-043", "text": " from current conditions. A 2005 survey finds higher profits for peasant compared to\n\ncorporate farms -though no significant differences in total factor productivity (Lerman _et al._ 2007)- but\n\ndoes not reconcile this with expansion by super-large farms. While credit market imperfections have\n\nbeen identified as a key constraint to needed investment in new technology (Zinych and Odening 2009),\n\nthis is not translated into differences in capital costs.\n\n\n**3. Data and descriptive evidence**\n\n\nDetailed panel data illustrate three features. First, yields grew rapidly after 2006, with sunflower-, corn-,\n\nand soybean-yields almost doubling, prompting a marked shift to oilseeds. Second, transformation of the\n\nagricultural sector was due more to new entry than to existing farm growth. Most entrants cultivated\n\nfarms 1,000-3,000 ha in size, which are large by European standards but not super-large. Finally,\n\nalthough land sales are not allowed, there was massive concentration of operational holdings; area\n\nfarmed by units above 10,000 (20,000) ha expanded by more than 2 (1.5) mn. ha (or 10% of the total) in\n\n\n7A ban on sales of agricultural land (moratorium) was established in 2001 making the rental market the only instrument for land transfer among\ncultivators.\n8 The 2012 draft “Law on Land Market” is the country’s 5th attempt to lift the current moratorium on land sales since 2005. Although there is\nbroad consensus about the need to establish secure property rights to land to encourage investment, there was agreement that the Draft Law was\nworse than the status quo resulting in its withdrawal (Lapa 2011) and a decision has now been postponed until 2016.\n\n\n7", "source": "general_prwp", "subset": "annotate_aivin_part2", "spans": [{"key": "sample:prwp:005691:8:1:0", "start": 28, "end": 39, "surface": "2005 survey", "probe_tag": "confusion", "probe_score": 0.6932, "luna_label": 1, "luna_reason": null}, {"key": "sample:prwp:005691:8:1:1", "start": 507, "end": 517, "surface": "panel data", "probe_tag": "confusion", "probe_score": 0.5983, "luna_label": 1, "luna_reason": "Panel data directly support concrete findings about yields, entry, and land concentration."}]}, {"key": "aivin2-044", "text": "Wage earners eligible for tax deductions for credit card payments may submit to NTS, via their\nemployers, the credit card tax deduction application form and a credit card transaction report\nissued by their credit card companies. These materials must accompany the wage earners’ labor\nincome tax settlements filed at the end of the tax year. Credit card companies must issue credit\ncard transaction reports to their customers upon request, or they may voluntarily issue the\nreports to their customers even without the request. <sup>44</sup> [^44: Article 121‐2, Presidential Decree of Preferential Tax Control Law, effective as of Oct 30, 1999.] After TIETP was introduced, credit card\ncompanies began voluntarily sending their customers annual transaction reports at the end of\nthe tax year as a customer service. In 2000, when TIETP was fully implemented, the Act on the\nSubmission and Management of Taxation Data (ASMTD) became law. According to the act, credit\ncard companies must regularly submit member stores’ credit card or debit card transaction data\nto NTS. As of 2012, wage earners can claim TIETP tax deductions by confirming prefilled credit\ncard transactions data forms provided by NTS through its Home Tax Service, the NTS tax service\ninternet portal. This service was enabled under ASMTD, which requires credit card companies to\nsubmit credit card transaction data to NTS.\n\n\nIf the credit card tax deduction application is valid, employers, acting as the withholding tax\nagents as to wage earners’ income, subtract the taxes saved by TIETP together with other tax\ndeductions and credits from the tax due in the month following the year‐end tax settlement. <sup>45</sup> If\nthe withholding tax agents should refund overpaid taxes, they can subtract the refund amount\nfrom the taxes due in subsequent months or request a refund from the regional NTS office. <sup>46</sup>\n\n\nThe TIETP process differs completely from the receipt compensation process adopted in 1977.\nPeople who wanted to receive receipt compensation had to submit to", "source": "general_prwp", "subset": "annotate_aivin_part2", "spans": [{"key": "prwp:006938:33:0:2", "start": 1016, "end": 1058, "surface": "credit card or debit card transaction data", "probe_tag": "confusion", "probe_score": 0.1749, "luna_label": 1, "luna_reason": "Transaction data supports prefilled tax deductions and tax calculations."}]}, {"key": "aivin2-045", "text": "The fact that children’s resource shares are different for the two assignable goods is concerning\n\nand points to a rejection of some aspect of the model with regards to one or both assignable goods.\n\nOne hypothesis is that clothing may be more shareable between children than between adults, e.g.\n\nbecause children wear hand-me-downs from their siblings and/or discarded clothing items from\n\ntheir parents. If this is the case, scale economies would be larger and shadow prices smaller for\n\nchildren than for adults, which could explain the results we find here (see Lechene, Pendakur, and\n\nWolf, 2020 for further discussion). Considering this sensitivity of children’s resource share estimates\n\nto the choice of the assignable good, the concluding section of this paper outlines an agenda for\n\nfurther methodological work to further validate estimates of intra-household resource shares and\n\nthe resulting headcount poverty rates, with a focus on a comparison of alternative assignable goods\n\nand how to best measure individual consumption of these goods in household surveys. However, it\n\nis important to bear in mind that the per-capita model also requires a strong assumption - that\n\nresources are shared equally between household members - which rarely finds empirical support\n\n(Lewbel and Pendakur, 2008b; Lise and Seitz, 2011).\n\n###### **4.5 Testing the per capita model with poverty rates**\n\n\nIn a next step we use the estimated resource shares to derive poverty rates for men, women and\n\nchildren in each of the four countries. Our first objective, pursued in this section, is to test whether\n\nthe resulting poverty rates, which take into consideration unequal sharing within households, are\n\nsignificantly different from the conventional poverty estimates, which assume that resources are\n\nshared equally within households.\n\n\nAs described in section 2, poverty estimates always incorporate implicit assumption about scale\n\neconomies.A related issue are differential needs of children relative to adults, an argument that is\n\ntypically motivated by the", "source": "general_prwp", "subset": "annotate_aivin_part2", "spans": [{"key": "prwp:000267:29:0:0", "start": 1059, "end": 1076, "surface": "household surveys", "probe_tag": "confusion", "probe_score": 0.852, "luna_label": 0, "luna_reason": "Future methodological agenda proposes measuring consumption in surveys."}]}, {"key": "aivin2-046", "text": "CROP PRODUCTION AND ROAD CONNECTIVITY IN SUB-SAHARAN AFRICA\n\n\nMiller, J. 2001. “Using GIS for Global Food and Water Balance Process Modeling.” Proceedings of the\n\nESRI International User Conference 2001, (On-line).\nhttp://www.esri.com/library/userconf/proc01/professional/papers/pap556/p556.htm.\n\n\nMurray, S. 2007. “Africa Infrastructure Country Diagnostic Inception Report: Creation of a GIS Database\n\nto Support AICD Study.” Mimeo. Washington, D.C.: World Bank.\n\n\nNelson, Andy. November 2007. “Global 1 km Accessibility (Cost Distance) Model Using Publicly\n\nAvailable Data.” Mimeo. Washington, D.C.: World Bank.\n\n\n———. “United Nations Environment Programme (UNEP) Road Map.” Africa Population Database, IV\n\nVersion. UNEP.\n\n\nSiebert, Stefan, P. Döll, and J. Hoogeveen. 2001. Global Map of Irrigated Areas Version 2.0. Germany:\n\nCenter for Environmental Systems Research, University of Kassel/Rome, Italy: FAO.\n\n\nStifel, David, and Bart Minten. 2008. “Isolation and Agricultural Productivity.” Agricultural Economics\n\n39 (1): 1–15.\n\n\nThomas, T. 2007. “Notes on Making Africa Access Map.” Mimeo. Washington, D.C.: World Bank.\n\n\nYou, L., and S. Wood. 2006. “An Entropy Approach to Spatial Disaggregation of Agricultural\n\nProduction.” Agricultural Systems 90 (1–3): 329–47.\n\n\nYou, L., S. Wood, and U. Wood-Sichra. 2007a. “Generating Plausible Crop Distribution and Performance\n\nMaps for Sub-Saharan Africa Using a Spatially Disaggregated Data Fusion and Optimization\nApproach.” IFPRI Discussion Paper 725, IF", "source": "general_prwp", "subset": "annotate_aivin_part2", "spans": [{"key": "prwp:005011:37:0:0", "start": 677, "end": 703, "surface": "Africa Population Database", "probe_tag": "confusion", "probe_score": 0.0926, "luna_label": 0, "luna_reason": "Database appears only within a bibliography reference entry."}, {"key": "prwp:005011:37:0:1", "start": 776, "end": 805, "surface": "Global Map of Irrigated Areas", "probe_tag": "confusion", "probe_score": 0.3275, "luna_label": 0, "luna_reason": "Bibliographic entry naming a dataset without showing its use or findings."}]}, {"key": "aivin2-047", "text": "effects hold across most continents, reassuring that a few countries and regions do not drive the\n\naverage impacts. In particular, these findings confirm that our search terms and languages are\n\nrelevant to all regions and hence can capture demand for the important sectors and services we are\n\nstudying.\n\n\n**7. Concluding Remarks**\n\nTo uncover the impacts of the COVID-19 pandemic on various services, we assemble Google\n\nsearch data that capture the temporal and spatial evolution of consumer demand for a carefully\n\nselected list of services. These novel data provide a unique opportunity to estimate the impacts of\n\nthe pandemic in contexts where other types of conventional data sources are not available. These\n\ndata are used to predict human preferences, and responses to fast-shifting events and pandemics\n\n(Choi and Varian, 2009; Goel et al., 2010; Pavlicek and Kristoufek, 2015). We use fixed effects\n\nspecifications to quantify the impact of the COVID-19 spread across countries. We exploit\n\ntemporal variations in the spread of COVID-19, both confirmed cases and deaths, across 182\n\ncountries that are currently affected by the pandemic.\n\nWe find that demand for some services has significantly increased because of the\n\npandemic, while some services experienced significant loss. Most importantly, we quantify the\n\nimpact of the additional spread of the burden on winning and losing sectors economies. More\n\nspecifically, we find that the spread of the pandemic has significantly reduced demand for services\n\nthat require face-to-face interactions while boosting demand for services involving less in-person\n\ninteractions. The size of the impacts is quite large. For instance, countries with at least 10\n\nconfirmed cases are likely to experience a 63-79 percent reduction in demand for hotel and\n\nrestaurant services while enjoying a comparable increase in demand for ICT services. Most of\n\nthese patterns are observed in all four continents (Africa, Americas, Asia, and Europe) in our\n\nsample. Our estimates suggest that the impacts are driven both by supply-side shocks", "source": "general_prwp", "subset": "annotate_aivin_part2", "spans": [{"key": "prwp:002448:27:0:0", "start": 415, "end": 434, "surface": "Google\n\nsearch data", "probe_tag": "confusion", "probe_score": 0.8748, "luna_label": 0, "luna_reason": "Authors state they assemble the data, making this a production activity."}]}, {"key": "aivin2-048", "text": "**Figure 3: Weights on life expectancy in the old and new HDI**\n\n\n\n.007\n\n\n.006\n\n\n.005\n\n\n.004\n\n\n.003\n\n\n.002\n\n\n.001\n\n\n\n|Col1|Old HDI<br>New HDI|Col3|Col4|Col5|Col6|Col7|Col8|\n|---|---|---|---|---|---|---|---|\n|||||||||\n|||||||||\n|||||||||\n|||||||||\n|||||||||\n|||||||||\n\n\n5 6 7 8 9 10 11 12\n\n\nGross national income ($ per person per year; log scale)\n\n\n\n<u>Source (this figure and all following ones): Author’s calculation from data for 2008 provided in the 2010 HDR. The</u>\nfitted line is a locally smoothed (nonparametric) regression.\n\n\n**Figure 4: Implicit valuations in HDI and marginal costs of an extra year of life expectancy**\n\n\n\n9,000\n\n\n8,000\n\n\n7,000\n\n\n6,000\n\n\n5,000\n\n\n4,000\n\n\n3,000\n\n\n2,000\n\n\n1,000\n\n\n0\n\n\n\n|Col1|Qatar<br>Liechtenstein<br>Implicit valuation<br>in HDI<br>Marginal cost<br>(Dowrick et al.)<br>Zimbabwe|Col3|Col4|Col5|Col6|Col7|Col8|\n|---|---|---|---|---|---|---|---|\n|||||||||\n|||||||||", "source": "general_prwp", "subset": "annotate_aivin_part2", "spans": [{"key": "prwp:004670:23:0:0", "start": 424, "end": 437, "surface": "data for 2008", "probe_tag": "confusion", "probe_score": 0.8465, "luna_label": 1, "luna_reason": "Existing 2008 data from the 2010 HDR supports the author’s calculation."}]}, {"key": "aivin2-049", "text": "**<u>Variables</u>** **<u>Measures</u>** **<u>Sources</u>**\n**<u>Crisis measure:</u>**\nSignificant drop in stock market returns Basis for the crisis measure is the\npercentage change in US $ national,\ntotal return, stock market indices\nrelative to the previous month. A\nmonth is counted as a crisis month if\nthe total return drops at least 2\nstandard deviations below the sample\nmean. Subsequent months are also\ncounted as crisis months until returns\nmove back into the one standard\ndeviation band around the sample\n<u>mean.</u>\n\n\n\n2 sets of crisis measures: 1) IFC\ninvestable, total return indices,\n2) MSCI total return indices. For\nboth cases, we have to use local\nsources for Romania, Slovakia\nand Romania. To convert returns\nfrom these three national indices\ninto US dollars, we use end of\nperiod data on exchange rates\nfrom the IMF's International\nFinancial Statistics (IFS).\n\n\n\n**<u>Explanatory Variables:</u>**\nUncertainty measure Monthly data of the weighted\naverage of the standard deviations of\nthe current and following year\nforecast of GDP growth across\nsurvey respondents. In January, the\nstandard deviation of the current year\nforecast is given a weight of 11/12\nwhile the standard deviation of the\nfollowing year forecasts is given a\nweight of 1/12. In February, the\ncurrent year forecast receives a\nweight of 10/12 while the follwing\nyear forecast is weighted by 2/12.\nThis scheme continues until\nDecember where a weighting of 0/12\nis given for the current year forecast\nand 12/12 for the following year\nforecast.\n\nMean growth expectations Monthly data of the weighted\naverage of the mean forecast by\nsurvey respondents of the current and\nfollowing year GDP growth. The\nweighting scheme is the same as for\nthe standard deviation.", "source": "general_prwp", "subset": "annotate_aivin_part2", "spans": [{"key": "prwp:004188:31:0:1", "start": 838, "end": 872, "surface": "International\nFinancial Statistics", "probe_tag": "keep", "probe_score": 0.9486, "luna_label": 1, "luna_reason": "IMF exchange-rate data are used to convert national stock returns to US dollars."}, {"key": "prwp:004188:31:0:3", "start": 937, "end": 949, "surface": "Monthly data", "probe_tag": "confusion", "probe_score": 0.4886, "luna_label": 0, "luna_reason": "Generic data phrase defines a measure without an attributed finding or concrete claim."}]}, {"key": "aivin2-050", "text": "**Figure 12**\n**Firm Activity in Equity Markets, 1990-2009**\n\n\nPanel A. Number of listed firms in domestic markets\n\n\n\n6,000\n\n\n5,000\n\n\n4,000\n\n\n3,000\n\n\n2,000\n\n\n1,000\n\n\n0\n\n\n600\n\n\n500\n\n\n400\n\n\n300\n\n\n200\n\n\n100\n\n\n0\n\n\n\nAsia (5) China Eastern Europe\n\n(7)\n\n\n\nG7 (7) India LAC7 (7) Other advanced\n\neconomies (7)\n\n\n\nPanel B. Average number of firms raising equity capital per year\n\n\n\nAsia (5) China Eastern Europe\n\n(7)\n\n\n\nG7 (7) India LAC7 (6) Oth. Adv.\nEconomies (7)\n\n\n\nThis figure shows in Panel A the average number of listed firms between 1990 and 2009. Panel B shows the total number of firms issuing\nequity per year between 1990 and 2009. Numbers in parentheses show the number of countries in each region. The data source is the World\nBank's World Development Indicators (WDI) (Panel A) and SDC Platinum (Panel B).", "source": "general_prwp", "subset": "annotate_aivin_part2", "spans": [{"key": "prwp:005719:50:0:1", "start": 786, "end": 798, "surface": "SDC Platinum", "probe_tag": "confusion", "probe_score": 0.8678, "luna_label": 1, "luna_reason": "Named database supplies data for the figure's panel on firms raising equity capital."}]}, {"key": "aivin2-051", "text": " series of reforms that started with self-assessment moved on to link the fiscal and legal cadasters, and\n\n\nthen improved valuations that have more than tripled tax revenue. In Lithuania, assessed values more than\n\n\nquadrupled as a result of gradually refining the mass valuation system (Almy 2015); it is now the core of\n\n\nan elaborate private-sector-driven data information system that provides many benefits (Grover et al. 2017).\n\nWhere effective and routine systems to collect property tax are lacking, <sup>10</sup> gains from administrative\n\n\nsimplification could be much larger. In such situations, property taxation may also contribute to increasing\n\n\nstate capacity and citizens’ trust in the state, as Weigel (2017) argues to be the case in the Democratic\n\n\nRepublic of Congo (Weigel 2017).\n\n\nEven where tax maps and realistic valuations are in place, increasing collection effort may yield high returns\n\nin terms of increased revenue collection. <sup>11</sup> [^11: For a comprehensive review of experiments to increase taxes more generally, i.e., well beyond the property tax, see Hallsworth (2014).] In the U.S., where property tax contributes 30% of local\n\n\ngovernment revenue and some 73% of local taxes, the performance of local governments varies widely.\n\n\nSimple reminders, especially if combined with a description of the effect of nonpayment, have greatly\n\n\nincreased collections (Chirico et al. 2017). In Peru a reminder to pay had a persistent positive impact on\n\n\npayment; disclosure of information on neighbors’ level of compliance was even more effective (delCarpio\n\n\n2015); similarly, in Argentina, a deterrence message also heightened taxpayers’ propensity to pay (Castro\n\n\nand Scartascini 2015).\n\n\n10 Franzsen and McCluskey (2017) provide an excellent and exhaustive survey of land and property tax systems in Africa, noting that in many of\nthese the level of taxes is based on self-declaration or the payment procedure is very cumbersome.\n11 For a comprehensive review of experiments to increase taxes more generally", "source": "general_prwp", "subset": "annotate_aivin_part2", "spans": [{"key": "prwp:007372:8:1:0", "start": 337, "end": 382, "surface": "private-sector-driven data information system", "probe_tag": "confusion", "probe_score": 0.1601, "luna_label": 0, "luna_reason": "Names an information system without showing its data informing analysis or decisions."}]}, {"key": "aivin2-052", "text": "##### **Annex 3: Data Sources and Definitions**\n\nThis paper makes use of two main sources of data: the Rwanda Development Board’s (RDB)\ncompany registration database and the Rwanda Revenue Authority’s (RRA) tax records. This\nsection provides a brief description of each of the sources of data, data cleaning procedures,\nas well as the definition of basic indicators.\n\n\n**RDB business registration database**\nThe RDB records the data of every new business, business line, or branch at the time of\nregistration. It contains information on 32,250 companies, with a total of 140,146 registered\nbusiness lines. Registrations date from as early as 1900; however data before 2006 was not\nconsidered. Most of the analysis presented here is focused on the 2008‐2012 period, both\nfor purposes of alignment with tax records, and also to coincide with the establishment of\nthe one‐stop shop and the business registration drives that took place in 2008.\n\nUpon registration, companies are assigned a Taxpayer Identification Number (TIN),\ngenerated from the RRA, which is then used to match registrations and tax records.\n\nCompanies are requested to specify (to Industrial Standard International Classification [ISIC]\nlevel 4) all the activities that they will be undertaking (referred to here as business lines).\nHowever, the RDB has omitted to inquire what the main business focus of the company will\nbe. Instead, this is imputed as the broad activity that appears most often among the\nregistered activities. <sup>16</sup> [^16: In more technical terms, the main activity is the mode of the registered business lines for each\nbusiness. “Broad activities” are defined to match Rwanda national accounting practices and are\ntherefore slightly different from ISIC level 1 definitions.] In absence of a clear activity, companies are classified as operating in\nmultiple sectors. An example of how this is reported is illustrated in Table 1 below. The same\nprocess is followed", "source": "general_prwp", "subset": "annotate_aivin_part2", "spans": [{"key": "prwp:006572:37:0:4", "start": 207, "end": 218, "surface": "tax records", "probe_tag": "confusion", "probe_score": 0.1924, "luna_label": 1, "luna_reason": "Rwanda Revenue Authority tax records are explicitly used as a primary data source."}, {"key": "prwp:006572:37:0:2", "start": 371, "end": 405, "surface": "RDB business registration database", "probe_tag": "confusion", "probe_score": 0.6867, "luna_label": 1, "luna_reason": "Registration database supplies records analyzed and matched with tax data."}]}, {"key": "aivin2-053", "text": "Claire**, “Method Matters: The Underreporting of Intimate Partner Violence,” _The_ _World_\n\n_Bank_ _Economic_ _Review_, 12 2023, _37_ (1), 49–73.\n**,** **Sarthak** **Joshi,** **Joseph** **Vecci,** **and** **Julia** **Talbot-Jones**, “Female Empowerment and Male\nBacklash: Experimental Evidence from India,” _Working_ _Paper_, 2024.\n**Dhar,** **Diva,** **Tarun** **Jain,** **and** **Seema** **Jayachandran**, “Reshaping Adolescents’ Gender Atti\ntudes: Evidence from a School-Based Experiment in India,” _American_ _Economic_ _Review_, 2022,\n_112_ (3), 899–927.\n**DHS**, “Rwanda Demographic and Health Survey 2014-15’,” 2016.\n\n\n31", "source": "general_prwp", "subset": "annotate_aivin_part2", "spans": [{"key": "prwp:001263:33:4:0", "start": 570, "end": 614, "surface": "Rwanda Demographic and Health Survey 2014-15", "probe_tag": "confusion", "probe_score": 0.666, "luna_label": 0, "luna_reason": "Bibliographic reference entry, not evidence of data use."}]}, {"key": "aivin2-054", "text": "Some supporting conditions that help create solid research support for committees are:\n\n**Case 3  CANADA**\n\nIn the last parliament, the federal PAC in Canada had 9 government and 8 opposition\nmembers with an opposition chair. It produced 10-20 reports a year based mainly on the\nreports of the Auditor General of Canada. The PAC also conducted enquiries on its own,\nmost recently about international financial reporting standards for the public sector, and\ninternal audit and evaluation. The government pays close attention to PAC recommendations\nand has already implemented those made a few years ago as a result of another independent\nenquiry supporting more frequent reporting for the Auditor General.\n\nThis case concerns an independent PAC investigation about 25 years ago beginning with a\nshort reference in the Auditor General’s report to unsubstantiated payments made by Atomic\nEnergy of Canada Limited (AECL), a crown corporation. The Committee conducted a\ndetailed enquiry into more than C$20 million that AECL had paid to agents abroad in hopes\nof selling nuclear reactors it manufactured. The Committee concluded the Corporation\nfollowed totally unacceptable business practices, and reported that they suspected some of\nthe payments were used for illegal or corrupt purposes. The PAC went far beyond the audit\nreport, wrote many letters, called many witnesses including the retired company President,\nheld 17 hearings over the course of a year, and wrote a far-reaching report that recommended\nmajor changes in the accountability regime for crown corporations that were subsequently\nimplemented. During the course of the enquiry, all committee members actively crossexamined hostile witnesses. The media gave the enquiry front-page attention and were able\nto uncover additional evidence the Committee could not have obtained on its own.\n\nThis case illustrates a number of features of an effective PAC: selection of important issues, a\nfocused enquiry tenaciously pursued, and a big-picture report with recommendations that are\n<u>implemented.</u>\n\nPerhaps surprisingly, lack of resources was not mentioned too often as a problem - the survey\nresults are not conclusive", "source": "general_prwp", "subset": "annotate_aivin_part2", "spans": [{"key": "prwp:002827:16:0:0", "start": 2146, "end": 2160, "surface": "survey\nresults", "probe_tag": "confusion", "probe_score": 0.3029, "luna_label": 1, "luna_reason": "Existing survey results support the sentence’s assessment, despite being inconclusive."}]}, {"key": "aivin2-055", "text": " Europe and\nCentral Asia), while employers and professional own-account workers do much better in\nLatin America and Sub-Saharan Africa than in Europe and Central Asia. As Latin\nAmerican and the developing countries of Europe and Central Asia have similar GDP per\ncapita, it is not likely that level of development explains these regional differences.\nRegional differences may be due to different legal and regulatory environments, an issue\nwe examine in more detail in a companion paper (Gindling, Mossaad and Newhouse,\n2015).\n\n\n_For Urban Workers Only_\n\n\nMany analyses of self-employment and labor market segmentation focus on urban and nonagricultural labor markets. Therefore, it is useful to examine the results for only urban\nworkers and see if they are consistent with results found using data for all workers (urban\nplus rural). <sup>9</sup> Table 5 replicates Table 3 using data for only urban workers.\n\n\nThere are no noticeable differences between tables 3 (urban plus rural) and tables 5 (urban\nonly). The results for urban workers are similar to the results for all workers together.\n\n\n9 Results for non‐agricultural workers only are similar to those presented for urban workers only.\n\n\n14", "source": "general_prwp", "subset": "annotate_aivin_part2", "spans": [{"key": "prwp:006575:15:1:0", "start": 795, "end": 815, "surface": "data for all workers", "probe_tag": "confusion", "probe_score": 0.3571, "luna_label": 1, "luna_reason": "Data for all workers underpin comparative analysis of urban-worker results."}, {"key": "prwp:006575:15:1:1", "start": 882, "end": 909, "surface": "data for only urban workers", "probe_tag": "confusion", "probe_score": 0.4814, "luna_label": 1, "luna_reason": "Urban-worker data are used to replicate and compare regression results."}]}, {"key": "aivin2-056", "text": "Looking at the pattern of commitments in the UR by the range of commitment and degree\n\n\nof development, a similar pattern develops to that observed in trade policy on goods: the degree of\n\n\nliberalization appears to increase with the level of income -- as shown in Table 14. Lower-income\n\n\ncountries appear to have committed to much less liberalization than higher-income ones. The\n\n\nsame conclusion can be drawn by looking at the commitments of the fifty developing countries\n\n\nwhose trade regimes were analyzed more systematically. Indeed, the pattern in Table 14 has a\n\n\nstriking parallel to the pattern in Table 3 above, with the lower the developing country income,\n\n\nthe lower the number of commitments and hence the highest the remaining protection. (See also\n\n\nBorchert, Goortiiz and Mattoo 2011, p.123.) The basic justification low-income countries make\n\n\nfor not liberalizing their service sector is the same infant industry argument used for so very long\n\n\nin the areas of merchandise trade. There are obvious dangers and limits to such a strategy as many\n\n\ndeveloping countries have realized in the areas of goods. These dangers have to be seriously\n\n\nevaluated by low-income developing countries which continue to protect their service sectors.\n\n\nOn the other hand the table shows that this relationship between the extent of liberalization\n\n\nand the level of development did not hold true for the financial services sector which includes\n\n\nbanking and insurance. In this case there is basically no pattern discernible, with most groups of\n\n\ncountries liberalizing about a quarter of the maximum possible -- if one weighs partial restrictions\n\n\nin each of the modes of supply. Again the LDCs made the fewest commitments. Only nine of the\n\n\ntwenty nine LDC made any commitments. But those which did, on average made greater\n\n\nliberalizing commitments than other developing countries.\n\n\nEarlier analysis (Mattoo 1998) suggests that in the area of commitments on commercial\n\n\npresence for financial services, Latin American countries tend to limit the number of suppliers,\n\n\nwhile Asian economies limit either solely the percentage of equity", "source": "general_prwp", "subset": "annotate_aivin_part2", "spans": [{"key": "prwp:005614:65:0:0", "start": 431, "end": 476, "surface": "commitments of the fifty developing countries", "probe_tag": "confusion", "probe_score": 0.8247, "luna_label": 0, "luna_reason": "Names commitments, not an eligible data resource or source."}]}, {"key": "aivin2-057", "text": " from all origins, which is a major limitation of the analysis as it does not allow to\ndisaggregate by type of tourist. It could be assumed that tourist origins are significantly correlated\nwith their income, and then as done in the literature, European and American tourists are\nconsidered as the representatives of tourist tastes and behavior. As noted above, flight arrivals from\ndeveloped countries are connected only through Lisbon, and as such, it can be safely assumed that\nmost tourists are from Europe.\n\nExpenditures by tourists is also an outcome variable of interest. Expenditures associated with the\nactivity of visitors have been traditionally identified with the travel item of the Balance of Payments\n(BOP). In the case of outbound tourism, those expenditures associated with resident visitors are\nregistered as “debits” in the BOP and refer to “travel expenditure”. As in the case of _inbound_\n_tourism_, BOP data are used. The 2008 International Recommendations for Tourism Statistics\nconsider that “tourism industries and products” include transport of passengers. Consequently, a\nbetter estimate of the tourism-related expenditures by resident and non-resident visitors in an\ninternational scenario would be, in terms of the BOP, the value of the travel item plus that of the\npassenger transport item.\n\nA key variable for our analysis is the average spending per tourist. Given information limitations,\nthis is approximated by the ratio between Expenditure and Arrivals, measured as the log of the ratio\nExpenditure / Arrivals (LN_EA). This is a proxy of prices paid by a representative tourist. As noted\nabove, this aggregate and average measure is not rich enough to study the prices of different\ntourism services _._\n\nSupply-side information is used from airline schedules on numbers of flights and seats. This\ncorresponds to the total number of flights reported by commercial airlines among the destinations\n(including local flights within countries) and the seats that were reported available from each flight.\n\n\n8", "source": "general_prwp", "subset": "annotate_aivin_part2", "spans": [{"key": "prwp:002405:9:1:0", "start": 921, "end": 929, "surface": "BOP data", "probe_tag": "confusion", "probe_score": 0.4973, "luna_label": 1, "luna_reason": "Existing BOP data are used for tourism expenditure analysis."}]}, {"key": "aivin2-058", "text": "Database on External Trade on container identifiers (Foreign Trade Statistics of the General\n\n\nDirectorate of Customs and Indirect Excises). We combine this with data provided by the\n\n\nMadagascan customs administration on import declarations from France (labeled as country\n\n\nof provenance or origin) over the period 2014-2016. Unique features of the Madagascan data\n\n\ninclude: (i) declaration-item level measures of detailed transportation costs that we use to\n\n\nconvert reported import Cost Freight and Insurance (CIF) values to import Free on Board\n\n\n(FOB) values as described in Section 2.3; (ii) tariffs paid by declaration-item; information\n\n\non the identity of both (iii) the importer, (iv) the inspector assessing the declaration and the\n\n\nbroker submitting it on behalf of the importer. For each declaration, the customs database\n\n\nis complemented by data from GasyNet, a private-public-partnership that assists Madagas\n\ncan customs with risk analysis, on a proprietary risk score, an inspection clearance channel\n\n\nrecommendation, and the presence of a scan (see Chalendard, Fernandes, Raballand, and\n\n\nRijkers (2023) for details). Details on these data are provided in Appendix A1.2.\n\n###### **2.2 Matching export and import declarations using container IDs**\n\n\nThe crucial feature of both customs databases is the presence of container identifiers (here\n\nafter ‘container IDs’) which are used to match them. As common international practice,\n\n\ncontainer IDs follow an ISO 6346:1995 norm (hereafter ‘ISO 6346’) defined by the Interna\n\ntional Organization for Standardization (ISO) and managed by the Bureau of International\n\n\nContainers. Each container ID is unique and ISO 6346 is recognized by French and Madagas\n\ncan customs in the process of identifying containers. <sup>5</sup> Incentives to misreport container IDs\n\n\nare very limited since they are included in the bill", "source": "general_prwp", "subset": "annotate_aivin_part2", "spans": [{"key": "prwp:000558:9:0:0", "start": 0, "end": 51, "surface": "Database on External Trade on container identifiers", "probe_tag": "confusion", "probe_score": 0.8952, "luna_label": 1, "luna_reason": "Customs database data are combined and used to match declarations via container identifiers."}, {"key": "prwp:000558:9:0:3", "start": 822, "end": 838, "surface": "customs database", "probe_tag": "keep", "probe_score": 0.9312, "luna_label": 1, "luna_reason": "Existing customs database is used with declaration-level data for trade analysis."}]}, {"key": "aivin2-059", "text": " staples, range from 1.8 percentage points in Ghana to 9.6\n\n\npercentage points in Senegal. Their analysis indicates that the impact is mediated by the share of\n\n\nthe food commodities undergoing price changes in the consumption expenditure of households as\n\n\nwell as the degree of dietary diversity in food consumption. As expected, they also find significant\n\n\ndifferences in urban and rural areas, with poverty impacts being higher in urban areas in general.\n\n\nPerhaps surprisingly, in three of the countries in their sample – Ghana, Senegal and Liberia – they\n\n\nfind that the impact on poverty is higher in rural areas (Wodon & Zaman, 2008).\n\n\nAnother study utilizing data from multiple developing countries is by Ivanic & Martin (2014) who\n\n\nexamine the impact of the 2010-11 food price surge. Their sample includes 28 low and middle\n\nincome countries, but the sample is not limited to African countries and considers price changes\n\n\n8", "source": "general_prwp", "subset": "annotate_aivin_part2", "spans": [{"key": "prwp:007530:9:1:0", "start": 670, "end": 709, "surface": "data from multiple developing countries", "probe_tag": "confusion", "probe_score": 0.5284, "luna_label": 1, "luna_reason": "Existing cross-country data support analysis of food-price impacts on poverty."}]}, {"key": "aivin2-060", "text": "<u>Figure 48. Credit Card EACR (household level, LITS)</u>\n\n\nSweden\n\n\nTurkey\n\n\nGreat Britain\n\n\nHungary\n\n\nFrance\n\n\nSlovenia\n\n\nItaly\n\n\nCzech Republic\n\n\nSlovak Republic\n\n\nCroatia\n\n\nGermany\n\n\nLatvia\n\n\nMacedonia\n\n\nAll\n\n\nEstonia\n\n\nMongolia\n\n\nSerbia\n\n\nUkraine\n\n\nMontenegro\n\n\nPoland\n\n\nKosovo\n\n\nAlbania\n\n\nBulgaria\n\n\nBosnia and Herzegovina\n\n\nRomania\n\n\nLithuania\n\n\nBelarus\n\n\nRussian Federation\n\n\nArmenia\n\n\nGeorgia\n\n\nKazakhstan\n\n\nAzerbaijan\n\n\nMoldova\n\n\nTajikistan\n\n\nKyrgyzstan\n\n\nUzbekistan\n\n\n\n\n\n0 10 20 30 40 50 60 70 80 90 100\n\n\nEACR Dissimilarity Coverage\n\n\n35 countries sorted by coverage rates. Coverage rates are labeled\n_<u>Sources</u>_ <u>: LITS</u>\n\n\n50", "source": "general_prwp", "subset": "annotate_aivin_part2", "spans": [{"key": "prwp:006585:51:0:0", "start": 636, "end": 640, "surface": "LITS", "probe_tag": "drop", "probe_score": 0.0141, "luna_label": 1, "luna_reason": "Named LITS source provides data underlying the reported figure and coverage rates."}]}, {"key": "aivin2-061", "text": "hypothesized as follows:\n\n\n  - _Hypothesis_ _1_ _(Extortion_ _to_ _Fear):_ Deportees who were extorted while migrating are\n\nmore likely to avoid a range of situations out of fear in their origin country compared\n\nto deportees who were not victims of such abuse.\n\n\n  - _Hypothesis_ _1a_ _(Extortion_ _to_ _Economic_ _Hardship):_ Deportees who were extorted while\n\nmigrating are more likely to experience economic hardship in their origin country than\n\nthose who were not extorted.\n\n\n  - _Hypothesis_ _2_ _(Fear_ _to_ _Engagement):_ Deportees avoiding activities in their origin coun\ntry because of fear are less likely to be politically engaged compared to those who are\n\nnot avoiding activities out of fear.\n\n\n  - _Hypothesis_ _2a_ _(Economic_ _Hardship_ _to_ _Engagement):_ Deportees who experience eco\nnomic hardship in their origin country are more likely to be politically engaged than\n\ndeportees who do not experience economic hardship.\n\n\nIf fear and economic hardship both mediate the relationship between extortion and po\nlitical engagement, a final hypothesis should concern which mechanism plays a larger role. If\n\nthe emotional consequences of extortion are larger than the financial ones, extortion should\n\nbe correlated with decreased rather than increased levels of political engagement. However,\n\nwe have no prior reason to believe that one mechanism is more or less important than the\n\nother. Thus, any conclusions about the overall relationship between extortion and political\n\nengagement is exploratory.\n\n#### **4 Research Design: Data and Methods**\n\n###### **4.1 Deportee Survey**\n\n\nWe employ data from an original survey of recent migrants deported from from the United\n\nStates and returned to Guatemala (“deportees” or “returnees”", "source": "general_prwp", "subset": "annotate_aivin_part2", "spans": [{"key": "sample:prwp:000637:12:0:0", "start": 1581, "end": 1596, "surface": "Deportee Survey", "probe_tag": "confusion", "probe_score": 0.1532, "luna_label": 1, "luna_reason": null}, {"key": "sample:prwp:000637:12:0:1", "start": 1624, "end": 1658, "surface": "original survey of recent migrants", "probe_tag": "drop", "probe_score": 0.0079, "luna_label": 1, "luna_reason": null}]}, {"key": "aivin2-062", "text": " the associated 95 percent confidence intervals for each<br>estimate are reported.|Notes: The figures report the difference-in-difference estimate from the baseline specification using an indicator for GBV incidents<br>occurring in the past year as the dependent variable. All specifications include control variables and regional fixed effects. Control variables<br>include the number of children born in the household, the share of household members that were eligible for the women’s survey, the<br>years of total schooling, the age of the household head, and indicators for the last level of schooling obtained (partially completed primary,<br>completed primary, partially completed secondary completed secondary, or higher than secondary), for whether the respondent was the<br>head of the household,  for the respondents literacy level (illiterate, partially literate, can read a sentence out loud), and for whether the<br>head of the household was male. Standard errors are clustered at the PSU level and the associated 95 percent confidence intervals for each<br>estimate are reported.|Notes: The figures report the difference-in-difference estimate from the baseline specification using an indicator for GBV incidents<br>occurring in the past year as the dependent variable. All specifications include control variables and regional fixed effects. Control variables<br>include the number of children born in the household, the share of household members that were eligible for the women’s survey, the<br>years of total schooling, the age of the household head, and indicators for the last level of schooling obtained (partially completed primary,<br>completed primary, partially completed secondary completed secondary, or higher than secondary), for whether the respondent was the<br>head of the household,  for the respondents literacy level (illiterate, partially literate, can read a sentence out loud), and for whether the<br>head of the household was male", "source": "general_prwp", "subset": "annotate_aivin_part2", "spans": [{"key": "prwp:001388:39:58:1", "start": 479, "end": 493, "surface": "women’s survey", "probe_tag": "drop", "probe_score": 0.0165, "luna_label": 0, "luna_reason": "Only identifies survey eligibility; no survey data are used or linked to a finding."}]}, {"key": "aivin2-063", "text": " has mo�vated\nrapid adop�on of alphahull for species range analysis in the recent professional literature (Kass et al. 2022;\nGuo et al. 2022).\n\nOf the 610,694 species in our database, alphahull successfully es�mates occurrence maps for 92.9%\n(567,464). For each species of the remaining 7.1%, we employ a standard k-means algorithm to separate\noccurrence reports into spa�al clusters and draw a convex hull around each cluster. Overall, our algorithms\nes�mate occurrence maps for more than 560,000 terrestrial species and more than 41,000 marine species.\nTo our knowledge, this is the largest set of species maps that have been es�mated from open-source data.\nOur es�ma�on algorithms are designed to support expansion of GBIF species maps with the con�nuing\nincrease in occurrence reports.\n\nAs an illustra�on, Figure 1(c) displays the algorithm’s applica�on to GBIF occurrence reports for Lagidium\nviscacia. The alphahull boundary follows the curvilinear north-south orienta�on of the point set, widening\nand narrowing as the point set expands and contracts. It closely resembles the expert map produced by\nBurgin et al., while extending it to incorporate new occurrence informa�on. <sup>12</sup> [^12: Two other powerful features of alphahull are not illustrated here, but play an important role in the produc�on of\nmaps for all species covered. The first is exclusion of random outlier points that are distant from a point cluster.\nThe second is produc�on of separate bounded areas for point clusters that are distant from one another.]\n\n\n10 The convex hull is the smallest convex polygon that encloses all points in a set. A polygon is convex if it has no\ncorner that is bent inward.\n11 This algorithm is a func�on in the R programming language.\n12 Two other powerful features of alphahull are not illustrated here, but play an", "source": "general_prwp", "subset": "annotate_aivin_part2", "spans": [{"key": "prwp:001554:5:1:0", "start": 642, "end": 658, "surface": "open-source data", "probe_tag": "drop", "probe_score": 0.0294, "luna_label": 1, "luna_reason": "Existing open-source data underpins the reported species-map estimates."}]}, {"key": "aivin2-064", "text": "Swierzbinski, J. E. and Mendelsohn, R. O.: 1989, Exploration and Exhaustible\n\n\nResources: The Microfoundations of Aggregate Models, International Eco\n\nnomic Review 30(1), 175\u001586.\n\n\nToman, M. A. and Jemelkova, B.: 2003, Energy and Economic Development:\n\n\nan Assessment of the State of Knowledge, The Energy Journal (4), 93\u0015112.\n\n\nUmmel, K. and Wheeler, D.: 2008, Desert Power: The Economics of Solar\n\n\nThermal Electricity for Europe, North Africa, and the Middle East, Working\n\n\nPaper 156, Center for Global Development.\n\n\nUSGS: 2009, Minerals Yearbook, U.S. Geological Survey.\n\n\nUSGS: 2011, Mineral Commodity Summaries, U.S. Geological Survey.\n\n\nViebahn, P., Lechon, Y. and Trieb, F.: 2011, The Potential Role of Concen\n\ntrated Solar Power (CSP) in Africa and Europe  - A Dynamic Assessment of\n\n\nTechnology Development, Cost Development and Life Cycle Inventories until\n\n\n2050, Energy Policy 39(8), 4420\u00154430.\n\n\nWadia, C., Alivisatos, A. P. and Kammen, D. M.: 2009, Materials Availability\n\n\nExpands the Opportunity for Large-Scale Photovoltaics Deployment, Envi\n\nronmental Science & Technology 43(6), 2072\u00152077.\n\n\nWilliges, K., Lilliestam, J. and Patt, A.: 2010, Making Concentrated Solar\n\n\nPower Competitive with Coal: the Costs of a European Feed-In Tari\u001b, Energy\n\n\nPolicy 38(6), 3089\u00153097.\n\n\nWise, M., Calvin, K., Thomson, A., Clarke, L., Bond-Lamberty, B., Sands, R.,\n\n\nSmith, S., Janetos, A. and Edmonds, J.:", "source": "general_prwp", "subset": "annotate_aivin_part2", "spans": [{"key": "prwp:006255:29:0:0", "start": 534, "end": 551, "surface": "Minerals Yearbook", "probe_tag": "confusion", "probe_score": 0.1205, "luna_label": 0, "luna_reason": "Bibliography entry naming a publication, not data used in the passage."}, {"key": "prwp:006255:29:0:1", "start": 591, "end": 618, "surface": "Mineral Commodity Summaries", "probe_tag": "drop", "probe_score": 0.0445, "luna_label": 0, "luna_reason": "Bibliographic reference entry, not an in-text data-use mention."}]}, {"key": "aivin2-065", "text": "UN projections are adjusted to<br>reflect higher or lower refugee returns. See Section 4.1.2.<br>_(6) _United Nations (2017).<br>_(7) _Based on ILO projections up to 2030 of the labor force participation rates, held constant thereafter. <br>|\n\n\n29", "source": "general_prwp", "subset": "annotate_aivin_part2", "spans": [{"key": "prwp:000498:30:28:0", "start": 144, "end": 159, "surface": "ILO projections", "probe_tag": "drop", "probe_score": 0.0172, "luna_label": 1, "luna_reason": "ILO projections provide labor-force participation inputs for projections through 2030."}]}, {"key": "aivin2-066", "text": "|aracteristics of surveyed households|Col2|\n|---|---|\n|<br>_Characteristic_<br>|_Percent of households_|\n|<br>_Zone_<br> <br>|<br>_Zone_<br> <br>|\n|<br>1 <br>|9.8<br>|\n|<br>2 <br>|<br>14.8<br>|\n|<br>3 <br>|<br>19.4<br>|\n|<br>4 <br>|<br>25.3<br>|\n|<br>5 <br>|<br>16.6<br>|\n|<br>6 <br>|<br>14.1|\n|<br> <br>_Housing tenure at current residence_<br> <br>|<br> <br>_Housing tenure at current residence_<br> <br>|\n|<br>Within last 12 months<br>|1.8<br>|\n|<br>1–2 years<br>|<br>5.7<br>|\n|<br>3–5 years<br>|<br>11.9<br>|\n|<br>6–10 years<br>|<br>17.4<br>|\n|<br>More than 10 years<br>|<br>22.4<br>|\n|<br>Since birth<br>|<br>40.8|\n|_Caste category_<br> <br>|_Caste category_<br> <br>|\n|<br>Scheduled Tribe<br>|4.7<br>|\n|<", "source": "general_prwp", "subset": "annotate_aivin_part2", "spans": [{"key": "prwp:000176:8:0:0", "start": 1, "end": 37, "surface": "aracteristics of surveyed households", "probe_tag": "drop", "probe_score": 0.036, "luna_label": 0, "luna_reason": "Standalone table header describing surveyed household characteristics."}]}, {"key": "aivin2-067", "text": "36\n\n\n**Table 1: Infant and under-5 mortality trends in Sub-Saharan African countries with a**\n\n**Demographic and Health Survey since 2005**\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Country|DHS survey|Infant mortality rate|Under-5 mortality rate|\n|---|---|---|---|\n|Country|DHS survey|per 1000<br>live births<br>% decline<br>per year|per 1000<br>live births<br>% decline<br>per year|\n|Benin<br>2001<br> <br>2006|Benin<br>2001<br> <br>2006|89<br>67<br>5.5%|160<br>125<br>4.8%|\n|Ethiopia<br>2005<br> <br>2011|Ethiopia<br>2005<br> <br>2011|77<br>59<br>4.3%|123<br>88<br>5.4%|\n|Ghana<br>2003<br> <br>2008|Ghana<br>2003<br> <br>2008|64<br>50<br>4.8%|111<br>80<br>6.3%|\n|Guinea<br>1999<br> <br>2005|Guinea<br>1999<br> <br>2005|98<br>91<br>1.2%|177<br>163<br>1.4%|\n|Kenya<br>2003<br> <br>2008|Kenya<br>2003<br> <br>2008|77<br>52<br>7.6%|115<br>74<br>8.4%|\n|Lesotho<br", "source": "general_prwp", "subset": "annotate_aivin_part2", "spans": [{"key": "prwp:005229:37:0:0", "start": 97, "end": 126, "surface": "Demographic and Health Survey", "probe_tag": "drop", "probe_score": 0.0182, "luna_label": 0, "luna_reason": "Survey phrase is embedded in a table caption, a table artifact."}]}, {"key": "aivin2-068", "text": "0</mark> .22*\nyears\n\n<mark>(0.10)</mark>\nLabor Force Surveys: 2 or more in 10\n0.36*\nyears\n\n<mark>(0.15)</mark>\n<mark>Health Surveys: 2 or more in 10 years</mark> <mark>0.07</mark>\n<mark>(0.12)</mark>\nBusiness/Establishments: 2 or more in\n<mark>0.20*</mark>\n10 years\n\n<mark>(0.10)</mark>\n<mark>Complete Civil Registration and Vital</mark>\n\n<mark>-</mark> 0.21\nStatistics System\n\n<mark>(0.18)</mark>\nAvailability of Data at 1st Admin\n1.27**\nLevel (ODIN) Score\n\n<mark>(0.44)</mark>\n<mark>Intercept</mark> <mark>-4.45*** -4.15*** -4.14*** -4.71*** -4.37*** -4.04*** -4.26*** -4.06*** -4.73*** -4.15***</mark>\n<mark>(1.16)</mark> <mark>(1.18)</mark> <mark>(1.21)</mark> <mark>(1.25)</mark> <mark>(1.16)</mark> <mark>(1.16)</mark> <mark>(1.19)</mark> <mark>(1.19)</mark> <mark>(1.26)</mark> <mark>(", "source": "general_prwp", "subset": "annotate_aivin_part2", "spans": [{"key": "prwp:001502:38:1:0", "start": 41, "end": 60, "surface": "Labor Force Surveys", "probe_tag": "drop", "probe_score": 0.0299, "luna_label": 0, "luna_reason": "Standalone table row label, not an independently cited data source."}]}, {"key": "aivin2-069", "text": "desirable and are capable of yielding interesting results as shown by those studies that were more\ncurrent.\n\n\n<u>Table 11: Geographical coverage of regression studies</u>\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|Authors of<br>study and<br>date|Study<br>number<br>as in<br>tables<br>6 and 7|Final<br>year of<br>data set<br>used|Unit of<br>analysis if<br>not country|Number of countries in each World Bank region by study|Col6|Col7|Col8|Col9|Col10|\n|---|---|---|---|---|---|---|---|---|---|\n|Authors of<br>study and<br>date|Study<br>number<br>as in<br>tables<br>6 and 7|Final<br>year of<br>data set<br>used|Unit of<br>analysis if<br>not country|Latin<br>America<br>and the<br>Caribbean<br>LAC<br>(30)*|Eastern<br>Europe<br>and<br>Central<br>Asia<br>ECA<br>(23)|South<br>Asia<br>SA<br>(8)|East<br>Asia<br>and<br>the<br>Pacific<br>EAP<br>(23)|Middle<br>East<br>and<br>North<br>Africa<br>MNA<br>(12)|Sub-<br>Saharan<br>Africa<br>SSA<br>(42)|\n|Andrés,<br", "source": "general_prwp", "subset": "annotate_aivin_part2", "spans": [{"key": "prwp:007394:47:0:1", "start": 327, "end": 335, "surface": "data set", "probe_tag": "drop", "probe_score": 0.0148, "luna_label": 0, "luna_reason": "Standalone table header fragment naming the final year of a dataset."}]}, {"key": "aivin2-070", "text": "\n_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the_\n_exchange of ideas about development issues. An objective of the series is to get the findings out quickly,_\n_even if the presentations are less than fully polished. The papers carry the names of the authors and should_\n_be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely_\n_those of the authors. They do not necessarily represent the view of the World Bank, its Executive Directors,_\n_or the countries they represent. Policy Research Working Papers are available online at_\n_http://econ.worldbank.org._\n\n\n1 Thanks to John Gibson, Maurice Schiff, Çaglar Özden and Alan Winters for useful comments, and to\nMadhur Arora, Jason Victor, and officials at the various consular departments and ministries for help in\ncollecting the passport data.", "source": "general_prwp", "subset": "annotate_aivin_part2", "spans": [{"key": "prwp:002997:0:1:0", "start": 886, "end": 899, "surface": "passport data", "probe_tag": "drop", "probe_score": 0.0251, "luna_label": 0, "luna_reason": "The sentence describes collecting passport data, so the data is being produced."}]}, {"key": "aivin2-071", "text": " supplies required for the study at the KEMRI-Wellcome unit in\nNairobi. It includes photocopying, stationary, communication and printing over the survey period. The estimates are based on\nroutine costs charged at the unit.\n\n_Travel and transportation_ . During the study preparation an investigator will need to meet with local officials and school head\nteachers. Travel and accommodation costs for these trips have been factored in here.\n\nThe education component of the study involves modifying the way Standard 1 and 2 classroom teachers develop their\nstudents’ literacy skills. To do this, the intervention includes an initial residential teacher training over a four-day period\nfollowed by ongoing monitoring and support. To ensure that all of the school’s personnel are informed, the Head Teachers\nand the Senior Teachers will also be invited to the training. This way, they will be available to support the classroom teachers\nduring the implementation of the intervention. The literacy intervention will be implemented in 50 schools involving at least\nthree teachers from each.\n\nThe study has a longitudinal design to investigate the interaction of the malaria intervention and the literacy intervention. To\nunderstand the effects of the interventions we will measure students’ education achievement at the onset and end of the\ninterventions. Student achievement in 100 schools will be measured. While the surveys are going on, a supervisor, three\nlaboratory technicians, one laboratory technician, one interviewer, one nurse plus one driver will need to travel to the field\nsites to undertake school surveys. All costs for travel and accommodation have been estimated using standard KEMRI\nmileage and per diem charges.\n\n_Operating costs_ **.** This includes all costs required to carry out the field studies and include laboratory materials, supplies,\nreagents and disposables. Training workshops will be organized by ESACIPAC to train all the technicians at the DVBD in\nKwale hospitals on parasite microscopy. Also included are laboratory quality control costs.\n\n\n67", "source": "general_prwp", "subset": "annotate_aivin_part2", "spans": [{"key": "prwp:005912:68:1:0", "start": 1600, "end": 1614, "surface": "school surveys", "probe_tag": "drop", "probe_score": 0.0361, "luna_label": 0, "luna_reason": "Future school surveys are planned project data production."}]}, {"key": "aivin2-072", "text": "\nfell into the last two categories (GUS,\n2024). However, to become promoted\nto an appointed or chartered teacher, a\nforeigner must possess Polish, EU, Swiss,\nor other EEA citizenship (Babakova et al.,\n2024). In effect, only 0.4% of Ukrainian\nrefugees were teachers (ZUS-registered\nin mid-2024) compared to 2.2% of Polish\ncitizens. There were more teachers’\nassistants, who are not regulated, than\n\n\n\nactual teachers. Furthermore, the data\npresented in chapter 2 shows that the\nmedian net wages of Ukrainian refugees\nin the teaching profession are just\nPLN 3,500, constituting 66% of what the\nhost population earns, the lowest earnings\nof all sectors.\n\n\n**Occupational licensing rules regarding**\n**citizenship have been relaxed for**\n**medical professions in the wake of**\n**the COVID-19 pandemic in 2020 and in**\n**February 2022, but those were often**\n**makeshift arrangements.** According to\nthe Babakova et al. (2024) report, during\nthe COVID-19 pandemic, practicing medical\nprofessionals from Ukraine were allowed\n\n\n#### **4.3 Language wage premium**\n\n\n\nEnglish for Speakers of Other Languages\nprogramme in Massachusetts. The policy\ntargeted all immigrants, including those\nwho had lived in Massachusetts for\nseveral years, with data for 2008–2016 and\n4,700 individual lottery applicants. Authors\nfound a causal effect, with annual earnings\nincreasing by USD 2,400. These earnings\ngains generated additional tax revenue\nthat produced a 6% return for taxpayers.\nSchmid (2023) studied African refugees\nwho applied for asylum in Switzerland\nbetween 2008 and 2017. He exploited the\nrandom assignment of refugees to French,\nGerman, and Italian cantons, as well as\ntheir prior language knowledge (e.g. French\nspeakers placed in French or German\nspeaking cantons). The results showed that", "source": "jad_paddy_docs", "subset": "annotate_aivin_part2", "spans": [{"key": "sample:jad_paddy_docs:000001:15:1:0", "start": 434, "end": 461, "surface": "data\npresented in chapter 2", "probe_tag": "keep", "probe_score": 0.9968, "luna_label": 1, "luna_reason": null}, {"key": "sample:jad_paddy_docs:000001:15:1:1", "start": 1234, "end": 1252, "surface": "data for 2008–2016", "probe_tag": "keep", "probe_score": 0.9905, "luna_label": 0, "luna_reason": null}]}, {"key": "aivin2-073", "text": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n\nAn ageing population coupled with a growing\neconomy causes labour shortages. Despite\nfalling number of available workers, the Polish\neconomy is growing steadily, as it modernises\nand converges to the level of development of\nold EU Member States. Despite the Covid-19\npandemic, real GDP growth averaged 3.7%\nduring the last decade. As a result, due to\nsteady demand for labour since 2019, the\nharmonised unemployment rate in Poland\nhas not exceeded 4%, oscillating around\n3% in recent years. According to Eurostat\ndata, in September 2023, harmonized\nunemployment in Poland reached 2.8%, the\nsame level as Malta. In the entire EU, only the\nCzech Republic reached a lower level: 2.7%.\nVacancies stood at record heights before\n\n\n\nthe refugee inflow. Before the refugee\ninflux, the share of companies reporting\nvacancies in the quarterly NBP survey\nstood at 49% in Q4 2021 – the highest\nlevel on record. This helps to explain the\nrelative ease of the refugees' labour market\ninclusion in terms of employment rates.\nAfter refugee inflow, the share of firms\nreporting vacancies stopped growing and\ndeclined slightly to 45% in Q3 2023. This\npartly indicates the fact that many refugees\nentered the labour market, and partly a\ncyclical economic slowdown. Despite that,\nthe labour market remains relatively strong.\n\n\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n**Chart 9.** Change in the number of workers registered for social security with Ukrainian citizenship by NACE sector between end of Q3\n2023 and 2021\n\n\nThousands\n\n\n\n\n\nManufacturing\n\n\nAccommodation and food service activities\n\n\nWholesale and retail trade; repair of motor vehicles and motorcycles\n\n\nHuman heatlh and social work activities\n\n\nAdministrative and support service activities\n\n\nEducation\n\n\nInformation and communication\n\n\nProfessional, scientific and technical activities\n\n\nPublic administration and defense; compulsory social security\n\n\nConstruction\n\n\nFinancial and insurance activities\n\n\nAgriculture, forestry and fishing\n\n\nReal estate activities\n\n\nWater supply: sewerage, waste management and", "source": "jad_paddy_docs", "subset": "annotate_aivin_part2", "spans": [{"key": "sample:jad_paddy_docs:000007:9:0:0", "start": 580, "end": 593, "surface": "Eurostat\ndata", "probe_tag": "keep", "probe_score": 0.9993, "luna_label": 1, "luna_reason": null}, {"key": "sample:jad_paddy_docs:000007:9:0:1", "start": 899, "end": 919, "surface": "quarterly NBP survey", "probe_tag": "keep", "probe_score": 0.9884, "luna_label": 1, "luna_reason": null}]}, {"key": "aivin2-074", "text": "Analysis of the impact of refugees from Ukraine on the economy of Poland Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n\n\n**Table 1.** Ukrainian employment rate in EU.\n\n\n**Employment rate** **Main sectors of employment** **Date** **Source**\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n**Source:** Deloitte elaboration based on the aggregation in OECD International Migration Outlook 2023. The calculation methods of employment\nrates vary between the countries, the results for Poland, the United Kingdom, Czech Republic and Italy are based on surveys. Additionally, the\ndifferent statistical offices and organisations may use different employment and working age definitions.\n\n\n\nCurrently, DIW Berlin data shows that the\nemployment of refugees from Ukraine is\nmuch lower in Germany, although many\naspire to find employment. In a weekly\nreport from 12th July 2023 the German\nInstitute for Economic Research (DIW\nBerlin), a survey conducted in the first\nquarter of 2023 finds that only 18% of\nworking age refugees were employed\n(Kollman, 2023). Among the non-employed,\nhowever, as many as 93% declare\nwillingness to begin working, of which\n71% as soon as possible or within a year.\nImportantly, many refugees are currently\nattending language courses in Germany\n\n- 65% in early 2023 with a further 10%\nalready having completed a course. 87%\nalso took part in inclusion courses that\nwere offered. Per the report, since the\nbeginning of the full-scale war,, around one\nmillion people have fled to Germany, while\nEurostat data on beneficiaries of temporary\nprotection show that there were around 1.17\nmillion Ukrainians under such schemes in\nGermany <sup>30</sup> [^30: Eurostat data, <u>https://ec.europa.eu/eurostat/databrowser/view/migr_asytpsm/default/table?lang=en</u>] .\n\n\nAmong working refugees there is a\nsignificant number of entrepreneurs.\nThe high employment rate of refugees in\nPoland covers not", "source": "jad_paddy_docs", "subset": "annotate_aivin_part2", "spans": [{"key": "sample:jad_paddy_docs:000007:13:0:0", "start": 344, "end": 385, "surface": "OECD International Migration Outlook 2023", "probe_tag": "keep", "probe_score": 0.9999, "luna_label": 1, "luna_reason": "Named OECD report supplies aggregated employment-rate data presented in the table."}, {"key": "sample:jad_paddy_docs:000007:13:0:1", "start": 688, "end": 703, "surface": "DIW Berlin data", "probe_tag": "keep", "probe_score": 0.9881, "luna_label": 1, "luna_reason": "DIW Berlin data supports the reported employment finding for Ukrainian refugees."}, {"key": "sample:jad_paddy_docs:000007:13:0:2", "start": 920, "end": 965, "surface": "survey conducted in the first\nquarter of 2023", "probe_tag": "keep", "probe_score": 0.9396, "luna_label": 1, "luna_reason": null}, {"key": "sample:jad_paddy_docs:000007:13:0:3", "start": 1505, "end": 1559, "surface": "Eurostat data on beneficiaries of temporary\nprotection", "probe_tag": "confusion", "probe_score": 0.1036, "luna_label": 1, "luna_reason": null}, {"key": "sample:jad_paddy_docs:000007:13:0:4", "start": 1662, "end": 1675, "surface": "Eurostat data", "probe_tag": "keep", "probe_score": 0.9991, "luna_label": 1, "luna_reason": null}]}, {"key": "aivin2-075", "text": " frames and\ninformation regarding population distribution by\n\n\n18 With both adult males and females present\n\n19 Also defined here for the 15+ age group\n\n\n**10**\n\n\n\ngeographic area and accommodation type. The\nobjective was to ensure a diverse sample\nrepresentative of the population’s composition. A\ncombination of different sampling methods was\nused, typically incorporating multiple stages and\nblending convenience sampling, cluster random\nsampling, and simple random sampling (the latter\nbeing exclusive to Romania).\n\n\nFor the regional analysis, population weights were\napplied based on the most up-to-date figures\nregarding the number of individual refugees\nrecorded in each country. This ensured the analysis\nmore accurately represented the broader refugee\npopulation across the region.\n\n\nAppropriate measures were implemented to ensure\nthe protection of personal data and guarantee\nconfidentiality in all data collection and processing\nactivities. Consent was requested and recorded for\nall selected participants, providing clear information\non the purpose, and expected use of the data.\n\n\nThe poverty line for each country was defined as\n50% of the median <u>[equivalized disposable income](https://www.oecd.org/els/soc/OECD-Note-EquivalenceScales.pdf)</u>\nas reported by the <u>[OECD (new definition since](https://stats.oecd.org/)</u>\n2012) for 2021. This figure was indexed towards\n2023 using national consumer price indexes (CPI).\nOn the survey data side, only households that did\nnot have any missing information on income\n(respondents were asked to provide both sources\nand amounts) were included in the calculation\n(households that reported having no income also\ndid not pass the filter). In addition, for households\nthat reported total expenditure above total income,\nexpenditure data was used instead, as it was\ndeemed to be more reliable. Following the OECD\nmethodology for equivalization, the resulting\ndisposable income figure for each household was\ndivided by the", "source": "jad_paddy_docs", "subset": "annotate_aivin_part2", "spans": [{"key": "sample:jad_paddy_docs:000000:9:1:0", "start": 1402, "end": 1433, "surface": "national consumer price indexes", "probe_tag": "confusion", "probe_score": 0.5394, "luna_label": 1, "luna_reason": "Used to index the 2021 poverty line toward 2023."}, {"key": "sample:jad_paddy_docs:000000:9:1:1", "start": 1782, "end": 1798, "surface": "expenditure data", "probe_tag": "confusion", "probe_score": 0.1167, "luna_label": 1, "luna_reason": null}]}, {"key": "aivin2-076", "text": " for 15-74 (broadest available) age group, and earnings by educational attainment are taken from the GUS (2022) “Structure of\nwages and salaries by occupations in October 2020”.\n37  Note that the numbers of Ukrainian refugees and all workers numbers by poviats are taken from ZUS Statistical Portal on 30th September\n2023 from the universe of workers registered for social security (this does not cover the informal sector and some jobs that do not require social\nsecurity). Ukrainian refugees are identified by PESEL UKR. Salaries and wages are taken from Statistics Poland BDL GUS database for 2022, but\ncover only the enterprise sector (firms with 10 or more employees).\n38  Note that there is no publicly available administrative data on the sectoral distribution of Ukrainian refugees. We proxied their sectors by\ntaking the difference in workers with Ukrainian citizenship registered for social security between H1 2023 and end of 2021 in A-Q 1-letter NACE\nsections. For the general population we used employment in the 15+ age group in Q2 2023 from the Eurostat Labour Force Survey. Earnings by\nNACE section have been taken from Statistics Poland Statistical Bulletin wages and salaries for the enterprise sector and public sector in Q2 2023.\n39  Note that Ukrainian refugees have been allocated to firm sizes based on the July-August 2023 UNHCR (2023) survey, while general workers\nfrom the GUS (2023) “Employment in the national economy in 2022”. Productivity of firms by size is based on gross value added per person\nemployed in industry, construction, and market services sectors (broadest available) in 2021 from Eurostat Structural Business Statistics.\n40  Note that data on occupations of Ukrainian 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", "source": "jad_paddy_docs", "subset": "annotate_aivin_part2", "spans": [{"key": "sample:jad_paddy_docs:000007:16:3:0", "start": 276, "end": 298, "surface": "ZUS Statistical Portal", "probe_tag": "confusion", "probe_score": 0.5255, "luna_label": 1, "luna_reason": null}, {"key": "sample:jad_paddy_docs:000007:16:3:1", "start": 557, "end": 591, "surface": "Statistics Poland BDL GUS database", "probe_tag": "keep", "probe_score": 0.9996, "luna_label": 1, "luna_reason": "Named database provides salary and wage data used in the analysis."}, {"key": "sample:jad_paddy_docs:000007:16:3:2", "start": 1060, "end": 1088, "surface": "Eurostat Labour Force Survey", "probe_tag": "keep", "probe_score": 0.9358, "luna_label": 1, "luna_reason": "Survey data provide general-population employment figures for sectoral comparison."}, {"key": "sample:jad_paddy_docs:000007:16:3:3", "start": 1136, "end": 1174, "surface": "Statistics Poland Statistical Bulletin", "probe_tag": "confusion", "probe_score": 0.8278, "luna_label": 1, "luna_reason": null}, {"key": "sample:jad_paddy_docs:000007:16:3:4", "start": 1347, "end": 1366, "surface": "UNHCR (2023) survey", "probe_tag": "drop", "probe_score": 0.0077, "luna_label": 1, "luna_reason": null}, {"key": "sample:jad_paddy_docs:000007:16:3:5", "start": 1625, "end": 1664, "surface": "Eurostat Structural Business Statistics", "probe_tag": "drop", "probe_score": 0.0009, "luna_label": 1, "luna_reason": null}, {"key": "sample:jad_paddy_docs:000007:16:3:6", "start": 1680, "end": 1721, "surface": "data on occupations of Ukrainian refugees", "probe_tag": "confusion", "probe_score": 0.388, "luna_label": 1, "luna_reason": null}, {"key": "sample:jad_paddy_docs:000007:16:3:7", "start": 1891, "end": 1898, "surface": "GUS LFS", "probe_tag": "drop", "probe_score": 0.0019, "luna_label": 1, "luna_reason": "GUS Labour Force Survey data are used for occupational comparison."}]}, {"key": "aivin2-077", "text": " in the July-August 2023 MSNA\nsurvey to 76% in the May-June 2024 SEIS\nsurvey. <sup>7</sup> This is not surprising, as the\nsituation of Ukrainians in the Polish labour\nmarket has clearly improved. First,\nemployment rate of working-age refugees\n\n\n\nfrom Ukraine has increased from 61% to\n69%, while their unemployment rate has\nhalved from 15% to 8%. Second, median\nnet wage of Ukrainian refugees grew from\nPLN 3,100 to PLN 4,000, i.e. by 29%. While\nhalf of this wage growth came from the\noverall high earnings growth in the country\ndue to high inflation (gross wages in the\ngeneral economy grew by 15% <sup>8</sup> ), it was still\na major improvement. Gross wage gains\nappear lower, with ZUS social insurance\ncontributions data for the period from\n\n\n\nJune 30, 2023 and June 30, 2024 showing\nan increase of 18% (compared to 15% for\nPolish citizens). As of June 30, 2024, only\n44% of ZUS-insured Ukrainian refugees\nhad an employment contract (compared\nto 82% of Polish citizens). Many may opt for\ncivil law contracts and self-employment to\nlimit their social insurance contributions to\nthe level of minimum wage.\n\n\n\n7 Together with refugees working remotely in Ukraine, their income from work would add up to 80% in the SEIS survey.\n\n8 From Q2 2023 to Q2 2024, <u>https://stat.gov.pl/en/latest-statistical-news/communications-and-announcements/list-of-communiques-and-announcements/average-</u>\n<u>gross-wage-in-the-second-quarter-2024,281,43.html</u>\n\n\n14\n\n\n\n9 These employment rates are very close to the ones from the Polish central bank", "source": "jad_paddy_docs", "subset": "annotate_aivin_part2", "spans": [{"key": "sample:jad_paddy_docs:000001:7:2:0", "start": 65, "end": 76, "surface": "SEIS\nsurvey", "probe_tag": "drop", "probe_score": 0.0, "luna_label": 1, "luna_reason": null}, {"key": "sample:jad_paddy_docs:000001:7:2:1", "start": 685, "end": 724, "surface": "ZUS social insurance\ncontributions data", "probe_tag": "confusion", "probe_score": 0.6881, "luna_label": 1, "luna_reason": "ZUS contribution data support reported wage and employment comparisons."}, {"key": "sample:jad_paddy_docs:000001:7:2:2", "start": 1215, "end": 1226, "surface": "SEIS survey", "probe_tag": "confusion", "probe_score": 0.4802, "luna_label": 1, "luna_reason": null}]}, {"key": "aivin2-078", "text": "x|x|x|x|x|x|\n|Local (“host”) population|||x|x|x||x|\n\n\n**C. Project Components**\n\n**_Component A: Targeted Food Assistance (US$7 million IDA_** )\n\n7. Under this component, WFP provides a safety net to 31,200 refugees/returnees who\nreceive support for 12 months following their return. Safety nets are notoriously difficult to\ninitiate in crisis situations, and given its current operations in Chad, WFP is well placed to scale\nup an existing safety net that provides both vouchers (for people to purchase food) and direct\nfood transfers (consisting of basic food items as well as specialized foods for children). Targeted\nfood assistance will improve the food security of refugees and returnees and help them\nreestablish livelihoods by preventing them from having to sell their remaining productive assets.\nVouchers will be provided for eight months of the year; in the other four months (the lean\nseason), beneficiaries will receive direct transfers of food. The vouchers cover the cost of a local\nstandard food basket (currently about US$0.30 per day).\n\n8. Lists of individuals who will receive food assistance will be drawn up based on data on\nrefugees and returnees provided by agencies such as IOM, which facilitate the movement of\npeople from CAR to Chad. Informal returnees are identified locally and verified by WFP staff as\n\n\n25", "source": "jdc_operational", "subset": "annotate_aivin_part2", "spans": [{"key": "sample:jdc_operational:000007:34:2:0", "start": 1138, "end": 1168, "surface": "data on\nrefugees and returnees", "probe_tag": "keep", "probe_score": 0.9682, "luna_label": 1, "luna_reason": "Existing agency-provided data informs beneficiary targeting lists."}]}, {"key": "aivin2-079", "text": "**The World Bank**\nSouth Sudan Enhancing Community Resilience and Local Governance Project (P169949)\n\n\n**I.** **STRATEGIC CONTEXT**\n\n\n**A. Country Context**\n\n\n1. **South Sudan was beset by decades of armed conflicts even prior to its independence in 2011,**\n**and these have only become increasingly complex in the years since.** Southern Sudan, as the region was\ncalled before independence, has been marred by conflict since 1955, just a year before Sudan attained its\nindependence from British colonial rule. The region experienced systematic marginalization and\nunderdevelopment under both British and Sudanese rule, inhibiting it from developing its physical and\nhuman capital. Consequently, at its independence in July 2011, South Sudan ranked almost at the bottom\nof the global development indicators with little infrastructure, basic services provided almost entirely\nthrough humanitarian aid, and an economy completely dependent on oil. Renewed civil conflict broke out\nin December 2013 and has only recently subsided with the formation of a new government in February\n2020, pursuant to the terms of the September 2018 Revitalized Peace Agreement. <mark>As a result of decades</mark>\n<mark>of violence, nearly 7.5 million people of the estimated 14 million total population rely on some type of</mark>\n<mark>humanitarian assistance or protection.</mark> <sup>1</sup> [^1: UNOCHA (United Nations Office for Coordination of Humanitarian Affairs). 2020. _Humanitarian Needs Overview 2020_, p. 3]\n\n\n2. **The country is highly vulnerable to climate change and natural disasters, and increased stress**\n**on natural resources is fueling local conflicts** . The Global Climate Risk Index ranked the country 125 out\nof 171 between 1998 and 2018. <sup>2</sup> [^2: Germanwatch. 2019. _Global Climate Risk Index 2020_, p. 42.] With a strong reliance on subsistence farming and", "source": "jdc_operational", "subset": "annotate_aivin_part2", "spans": [{"key": "sample:jdc_operational:000049:14:0:0", "start": 777, "end": 806, "surface": "global development indicators", "probe_tag": "keep", "probe_score": 0.9799, "luna_label": 1, "luna_reason": null}, {"key": "sample:jdc_operational:000049:14:0:1", "start": 1663, "end": 1688, "surface": "Global Climate Risk Index", "probe_tag": "keep", "probe_score": 0.9976, "luna_label": 1, "luna_reason": null}]}, {"key": "aivin2-080", "text": "**I.** **STRATEGIC CONTEXT**\n\n\n**A.** **Country Context**\n\n\n1. **Jordan is a small middle-income country facing severe challenges.** These challenges are brought\nby insecurity in neighboring Syria and Iraq. The total closure of land trade routes with Syria and Iraq and\nother security-related challenges within and around Jordan adversely affected trade, tourism, investment,\nand construction. <sup>1</sup> [^1: As an indication, and comparing 2015 results with 2014, the number of tourist arrivals regressed by 9.7 percent;\nsimilarly, the number of construction permits were 9.6 percent lower and exports to Iraq and Syria were cut by 40.5\npercent and 40.3 percent, respectively.] According to a census conducted in 2015, Jordan has a population of 9.5 million (of\nwhich about a third are non-Jordanian) and suffers from a high unemployment rate of 13 percent for\nJordanians (about 200,000 individuals). Real gross domestic product (GDP) growth is estimated to have\ncontracted to 2.4 percent in 2015 from 3.1 percent in 2014. <sup>2</sup> [^2: Economic growth averaged 6.5 percent from 2000 to 2009. The economy’s performance was more muted from 2010\nto 2014, averaging growth of 2.7 percent.] GDP growth is forecasted to rebound slightly\nover 3.0 percent on average from 2016 to 2018. This low growth rate is insufficient to provide enough jobs\nto the growing population in Jordan.\n\n\n2. **The crisis in Syria has led to a massive influx of Syrian refugees into Jordan over the past five**\n**years.** As of June 2016, Jordan hosts 655,217 Syrian refugees registered with United Nations High\nCommissioner for Refugees (UNHCR), <sup>3</sup> [^3: _Source:_ UNHCR June 2016.] 80", "source": "jdc_operational", "subset": "annotate_aivin_part2", "spans": [{"key": "sample:jdc_operational:000045:9:0:0", "start": 697, "end": 721, "surface": "census conducted in 2015", "probe_tag": "keep", "probe_score": 0.9769, "luna_label": 1, "luna_reason": null}]}, {"key": "aivin2-081", "text": "**The World Bank**\nUganda Digital Acceleration Program (P171305)\n\n\na smart-phone. <sup>41</sup> [^41: https://www.gsma.com/mobilefordevelopment/wp-content/uploads/2019/07/The-Digital-Lives-of-Refugees.pdf] Furthermore, only 24 percent of refugees in the camp have used the Internet and 17\npercent are active Internet users. <sup>42</sup> [^42: https://www.gsma.com/mobilefordevelopment/wp-content/uploads/2019/07/The-Digital-Lives-of-Refugees.pdf] For 73 percent, the cost of an Internet-enabled device is a key\nbarrier. <sup>43</sup> [^43: https://www.gsma.com/mobilefordevelopment/wp-content/uploads/2019/07/The-Digital-Lives-of-Refugees.pdf] Consequently, refugees struggle to contact relatives, get timely market or business development\ninformation, access digital financial services, use digital learning options and use Internet for other\nproductive purposes. Many also face challenges meeting identity documentation requirements,\nespecially in the context of registering for a SIM card. COVID-19 has affected refugee livelihoods and\nincreased income insecurity, sexual and gender-based violence and anxiety. Women are more direly\naffected. Based on household surveys with over 1,500 refugees in Kampala and the settlements as well as\ninterviews with 185 key informants, UNHCR and UN Women found that household income loss has\ncontributed to an increased incidence of Gender-Based Violence (GBV) and negative coping mechanisms\nsuch as survival sex and sale of alcohol. 53% of girls and 46% of women aged 18-24 years reported an\nadditional unpaid work burden, with school closures also affecting their ability to access learning\nopportunities <sup>44</sup> [^44: Inter-agency report: refugee women and girls in Uganda disproportionately affected by COVID-19.\nhttps://www.unhcr.org/afr/news/press/2020/12/5fc7a6694/inter-agency-report-refugee-women-and-girls-in-ugandadisproportionately.html] . Limited connectivity also hampers humanitarian", "source": "jdc_operational", "subset": "annotate_aivin_part2", "spans": [{"key": "jdc_operational:000033:7:0:0", "start": 1156, "end": 1173, "surface": "household surveys", "probe_tag": "keep", "probe_score": 0.9013, "luna_label": 1, "luna_reason": "Surveys underpin reported refugee livelihood, violence, and unpaid-work findings."}]}, {"key": "aivin2-082", "text": "2.7 percent, respectively). Gross domestic\nproduct (GDP) per capita fell from US$969 in 2014 to US$843 in 2017.\n\n\n3. **Despite high levels of hunger, agriculture remains the main source of both food and**\n**employment for Chadians.** The 2018 Global Hunger Index ranks Chad second last of 119 countries. In\n2015, 43 percent of children under five years showed signs of stunting due to chronic malnutrition.\nNonetheless, three out of every four Chadians are employed in agriculture. In the project area, agriculture\nis diversified with many crops including sorghum, millet, peanuts, and cotton supplemented by cowpea\nand sesame. There is also expanding cultivation of rice, vegetables, and tubers (potato, yams, and\nmanioc).\n\n\n4. **Poverty is mainly a rural phenomenon.** Although poverty declined during the economic boom of\n2003–2014, from 55 percent to 47 percent, extreme poverty still affects half of all Chadians. A total of 47\npercent of the population lives below the national poverty line. About 52 percent of rural households are\npoor compared to 21 percent of urban households. A majority of the population lives in rural areas, which\nimplies that most of the poor (92 percent) live in rural areas, of which 40 percent live in the five southern\nprovinces of Chad. <mark>With more than 700,000 refugees from Sudan,</mark> Central African Republic, and Nigeria\nwithin its borders, the country is also facing a humanitarian challenge and an additional pressure on the\nscarce resources, notably in the rural areas. This makes the country even more fragile and at risk of food\nshortages and volatility.\n\n\n1 General Population and Housing Census (RGPH 2) of 2009.\n\n\nPage 7 of 76", "source": "jdc_operational", "subset": "annotate_aivin_part2", "spans": [{"key": "jdc_operational:000048:10:1:0", "start": 238, "end": 262, "surface": "2018 Global Hunger Index", "probe_tag": "keep", "probe_score": 0.9771, "luna_label": 1, "luna_reason": "Named index provides a ranking used as evidence of Chad’s hunger level."}, {"key": "jdc_operational:000048:10:1:1", "start": 1651, "end": 1657, "surface": "RGPH 2", "probe_tag": "keep", "probe_score": 0.9101, "luna_label": 1, "luna_reason": "Named 2009 population and housing census cited as an existing data source."}]}, {"key": "aivin2-083", "text": " of\nemployment in urban areas is in the informal sector <sup>2</sup>, characterized by low productivity and wages. In\naddition, congestion and lack of public transport options in many cities restricts the movement of goods and\npeople. The quality of housing remains inadequate for a large proportion of the urban population, with more\nthan 60 percent of the residents of urban areas living in slums. Finally, the delivery of social services of an\nadequate quality to a rapidly expanding urban population is also a source of concern <sup>3</sup> .\n\n4. **_Rapid Urbanization has resulted in a huge infrastructure backlog_** **.** For example, the backlog of\nbituminized roads in the 14 Municipalities targeted in the current phase of USMID was estimated at around\n\n\n1 Currently the Program targets 14 municipalities, namely: Arua, Gulu, Lira, Mbale, Soroti, Tororo, Jinja, Entebbe, Masaka, Mbarara,\nKabale, Fort Portal, Hoima, and Moroto.\n2 Uganda Urban Labor Force Survey 2009.\n3 World Bank. 2015. _The growth challenge: Can Ugandan cities get to work?_ . Washington, DC: World Bank Group.\n\n\n1", "source": "jdc_operational", "subset": "annotate_aivin_part2", "spans": [{"key": "sample:jdc_operational:000062:8:2:0", "start": 939, "end": 970, "surface": "Uganda Urban Labor Force Survey", "probe_tag": "keep", "probe_score": 0.9985, "luna_label": 1, "luna_reason": null}]}, {"key": "aivin2-084", "text": "**The World Bank**\nUganda: Roads and Bridges in the Refugee Hosting Districts Project (P171339)\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Percentage of women employed in<br>construction and maintenance of Project<br>road|Percentage of women<br>employed in construction<br>and maintenance of the<br>project road|Semi-<br>annually|Supervision<br>Consultant's<br>Reports|Contractor's and<br>consultant's data|Supervision Consultants,<br>Monitoring and<br>evaluation consultants,<br>UNRA|\n|---|---|---|---|---|---|\n|Health and Safety Management Plans|Health and Safety<br>Management Plans for the<br>Project road works|semi-<br>annually<br>|Monthly<br>progress<br>reports<br>|Police records, data<br>collected by supervision<br>consultants and<br>contractor<br>|UNRA<br>|\n|Percentage of Project Affected People<br>that received full compensation and all<br>R&R assistance dis-aggregated by gender,<br>refugees, hosts|Project Affected People that<br>received full compensation<br>and all R&R assistance|Semi-<br>annually<br>|Reports of<br>RAP<br>implementin<br>g agency<br>|Surveys, study<br>|Monitoring and<br>evaluation consultants,<br>UNRA<br>|\n|Grievances responded and/or resolved<br>within the stipulated service standards for<br>response times (dis-aggregated by<br>gender, refugees, hosts)|<br>Percentage of", "source": "jdc_operational", "subset": "annotate_aivin_part2", "spans": [{"key": "jdc_operational:000050:61:0:0", "start": 644, "end": 658, "surface": "Police records", "probe_tag": "confusion", "probe_score": 0.0602, "luna_label": 0, "luna_reason": "Listed as planned monitoring evidence, not analyzed or used existing data."}]}, {"key": "aivin2-085", "text": "**The World Bank**\nChad COVID-19 Strategic Preparedness and Response Project (P173894)\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|Monitoring & Evaluation Plan: PDO Indicators|Col2|Col3|Col4|Col5|Col6|\n|---|---|---|---|---|---|\n|**Indicator Name **<br>|**Definition/Description **<br>|**Frequency **|**Datasource **|**Methodology for Data**<br>**Collection **|**Responsibility for Data**<br>**Collection **|\n|Number of designated laboratories with<br>COVID-19 functioning diagnostic<br>equipment, test kits, and reagents per<br>MOH guidelines|Number of existing<br>laboratories with effective<br>capacity for testing COVID-<br>19 <br>|quarterly<br>|MOPH report<br>|<br>routine data<br>|<br>MOH<br>|\n|<br>Percentage of targeted acute healthcare<br>facilities with isolation capacity <br>|<br>Number of available<br>targeted acute healthcare<br>facilities with isolation<br>capacity for COVID-19<br>patients as a percentage of<br>all the target acute<br>healthcare facilities.|weekly<br>|COVID-19<br>report<br> <br>|routine data<br>|MOPH<br>|\n|Number of suspected cases of COVID-19<br>cases reported and investigated based on<br>national guidelines|<br>Number of suspected<br>effectively cases tested <br>|weekly<br>", "source": "jdc_operational", "subset": "annotate_aivin_part2", "spans": [{"key": "sample:jdc_operational:000039:36:0:0", "start": 634, "end": 645, "surface": "MOPH report", "probe_tag": "confusion", "probe_score": 0.8265, "luna_label": 0, "luna_reason": "Datasource cell in a monitoring-plan table, not independently used evidence."}, {"key": "sample:jdc_operational:000039:36:0:1", "start": 654, "end": 666, "surface": "routine data", "probe_tag": "confusion", "probe_score": 0.8431, "luna_label": 0, "luna_reason": null}]}, {"key": "aivin2-086", "text": " Decision Note)**|<br>**Safeguards Deferral (from Decision Review Decision Note)**|<br>**Safeguards Deferral (from Decision Review Decision Note)**|<br>**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|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|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|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 US$ Million)**|**Project Financing Data(in US$ Million)**|**Project Financing Data(in US$ Million)**", "source": "jdc_operational", "subset": "annotate_aivin_part2", "spans": [{"key": "jdc_operational:000047:6:3:0", "start": 1323, "end": 1345, "surface": "Project Financing Data", "probe_tag": "confusion", "probe_score": 0.4274, "luna_label": 0, "luna_reason": "Standalone table header, not a substantive data-use mention."}]}, {"key": "aivin2-087", "text": "6.9|17,160.3|22.0|\n|Appraisal period<br>reduced to 3 years|4,296|19.9|2,781|28.6|(9,239)|−11.9|6,874|30.2|59,200|45.1|\n|Appraisal period<br>reduced to 5 years|13,780|34.3|7,990|45.8|2,454|9.0|19,152|47.2|136,276|60.9|\n\n\n\n_Source:_ Based on World Bank staff estimates.\n\n\n\nPage 81 of 94", "source": "jdc_operational", "subset": "annotate_aivin_part2", "spans": [{"key": "jdc_operational:000049:86:1:0", "start": 240, "end": 266, "surface": "World Bank staff estimates", "probe_tag": "confusion", "probe_score": 0.2599, "luna_label": 1, "luna_reason": "Source line attributes the table's estimates to World Bank staff analysis."}]}, {"key": "aivin2-088", "text": "000\npeople with food supplies and some 30,000 households had been assisted with Emergency Flood Rapid\nResponse Kits. Humanitarian efforts continue in priority locations and additional response teams have been\ndeployed to flood-affected areas to further expand relief efforts. Increased flood response is enabled by\ndonor contributions, including US$15 million from United Nations Central Emergency Response Fund and\nUS$9.8 million from the South Sudan Humanitarian Fund. <sup>123</sup> [^123: UNOCHA. 2019. “South Sudan Flooding Update Nr. 4.” November 29, 2019.] To respond to the short-and longer-term needs\nexacerbated by the floods, UNDP in coordination with other disaster relief organizations is gathering hazard\nand exposure data to produce a comprehensive hazard risk profile for South Sudan. <sup>124</sup> [^124: According to personal communication with UNDP.]\n\n\n5. **The proposed project DRM activities complement humanitarian response efforts by aiming to**\n**reduce disaster vulnerability and enhancing existing coping capacities of affected communities.** Where\npossible, the ECRP will seek to build peoples’ and communities’ resilience on the basis of existing capacities\nand coping mechanisms in a way that promotes self-reliance and helps better manage shocks. The project\nwill ensure that all interventions further develop preparedness and coping strategies and disaster adaptation\nprocesses that exist at the community level and also determine and respond to the risk perceptions and\nknowledge of safety systems among communities in the event of a disaster.\n\n\n6. **DRM activities are developed in alignment with the subproject cycle.**\n\n\n(a) As part of the county and community diagnostics, a hazard screening will be performed based\n\non available flood and drought hazard data.\n\n\n(b) If hazard-prone communities choose to implement disaster risk reduction measures (as per the\n\nproject’s open menu approach), BDC and other community representatives are first engaged in\n\n\n119 UNEP. 2018. _South Sudan First State of the Environment and Outlook Report_ .\n120 UNOCHA. 2020. “South", "source": "jdc_operational", "subset": "annotate_aivin_part2", "spans": [{"key": "jdc_operational:000049:91:1:0", "start": 712, "end": 736, "surface": "hazard\nand exposure data", "probe_tag": "confusion", "probe_score": 0.1124, "luna_label": 0, "luna_reason": "Data are being gathered to produce a future hazard risk profile."}, {"key": "jdc_operational:000049:91:1:1", "start": 1767, "end": 1796, "surface": "flood and drought hazard data", "probe_tag": "confusion", "probe_score": 0.4548, "luna_label": 1, "luna_reason": "Existing hazard data used as the basis for community hazard screening."}]}, {"key": "aivin2-089", "text": ", high-volume, and/or\nmisuse- and abuse-prone conditions. <sup>21</sup> At the request of the World Bank, an additional technical audit\nmay be conducted to review expenses covered by Bank financing (refer to Financial Management\nsection). The MoPH admission criteria will be further elaborated as part of the Project Operations\nManual (POM) that will be adopted by the borrower no later than four months after loan effectiveness.\n\n\n31. **Component 3: Strengthening project management and monitoring (US$6.8 million).** This\ncomponent will finance:\n\n\n   - Strengthening the capacities of the MoPH and Project Management Unit for implementation,\ncoordination and management of activities under the project (including, inter alia, procurement,\nfinancial management, technical and financial audits, environmental and social safeguards,\ngrievance redress mechanisms, monitoring and evaluation, health information management,\nsupervision and reporting aspects), all through the provision of consulting services, nonconsulting services, training and workshops, operating costs, and acquisition of goods for the\npurpose.\n\n   - Carrying out of a comprehensive assessment of hospitals focusing on accuracy of hospital case\nmix, use of hospitalization data in medical auditing, development of performance indicators\nincorporating actual patient outcomes, resource allocation decisions, and\ninstitutional/organization structures, so as to identify gaps and make recommendations for\nimprovement. Results of the assessments will inform the MoPH in refining their hospital\n\n\n19 On average, hospitalization costs US$1,000. This component could finance additional admissions to approximately 33,000\npatients.\n20 Salaries are not covered by the contract.\n21 National Institute for Healthcare Excellence (NICE), U.K.\n\n\nPage 20 of 54", "source": "jdc_operational", "subset": "annotate_aivin_part2", "spans": [{"key": "jdc_operational:000032:22:1:0", "start": 1225, "end": 1245, "surface": "hospitalization data", "probe_tag": "confusion", "probe_score": 0.2914, "luna_label": 0, "luna_reason": "Planned assessment activity, not documented use of existing data."}]}, {"key": "aivin2-090", "text": "**The World Bank**\nEnhancing Community Resilience and Local Governance Project Phase II (P177093)\n\n\nclimate-resilient approaches, including risk assessments, to identify safe locations and elevated building\nstructure options to reduce flood and other disaster risks. The participatory planning process will\nbe supported under Component 2. All _payams_ and _bomas_ within the target counties will be eligible for\nfunding.\n\n\n33. To ensure flexibility, the project can also mobilize resources rapidly to respond to COVID-19 needs\nby funding handwashing facilities at public markets, places of worship, public transportation hubs,\ncommunal water points, women- and girl-friendly spaces, and other densely populated locations. Such\ninvestments will be coupled with hygiene promotion and COVID-19 awareness raising/communication to\nbe financed under Component 2. Communities’ priorities will be validated through local service mapping\nto avoid overlaps and to maximize the use of limited resources by consolidating common priorities among\nneighboring communities, where possible. Community labor will be used, to the extent possible, to\ngenerate income opportunities. The project will establish harmonized salary levels, to the extent possible,\nwith the planned Productive Safety Net for Socioeconomic Opportunities Project (PSNSOP, P177663) _._\n\n\n34. **Geographic targeting.** The selection of counties is guided by four principles: (a) vulnerability, (b)\nfeasibility, (c) equity, and (d) continuity (see Figure 2). The project will continue to target the 10 counties\nwhere ECRP-I has started implementation to consolidate the envisioned development gains in these\nlocations. <sup>48</sup> As indicated in Table 1, ECRP-II will scale up to include refugees in the two refugee-hosting\ncounties that were already targeted under ECRP-I <sup>49</sup> and two new flood-prone vulnerable counties to\nsupport Subcomponent 1", "source": "jdc_operational", "subset": "annotate_aivin_part2", "spans": [{"key": "sample:jdc_operational:000028:25:0:0", "start": 907, "end": 928, "surface": "local service mapping", "probe_tag": "confusion", "probe_score": 0.4356, "luna_label": 0, "luna_reason": null}]}, {"key": "aivin2-091", "text": ", prices of December 2016 are used. In\n2016, 56 percent of subsistence farmers cultivated an average of 0.84 hectare, and 25 percent farmers\ncultivated about 1.47 hectare, <sup>25</sup> thus an average of 1 ha/ beneficiary is assumed. The analysis assumes\nthat the investment leads to cropping on 22,500 ha (55 percent sorghum; 45 percent maize). Table A3.1\npresents the annual gross margins for sorghum and maize.\n\n\n20 Sulaiman, S. (2011): Incentive and crowding out effects of food assistance: Evidence from randomized evaluation of a food‐for‐\ntraining project in South Sudan. http://www.africaneconomicconference.org/2012/Documents/Papers/AEC2012‐017.pdf\n21 Torero, M (2014): Food security brings economic growth – not the other way around. IFPRI BLOG.\n22 European Parliament. Background Document. The social and economic consequences of malnutrition in ACP\ncountries.http://www.europarl.europa.eu/meetdocs/2009_2014/documents/acp/dv/background_/background_en.pdf\n23 The models have been established in the course of the project P147900 Southern Sudan EFCRP.\n24 Crop and Livestock Market Information System South Sudan (December 2016): Juba Bi‐Weekly Price Watch – December 2016,\nWeek 4. http://www.climis‐southsudan.org/uploads/publications/2016_Dec_Week4_Juba_Bi‐Weekly_Bulletin.pdf.\n25 WFP/FAO/UNICEF/Government of South Sudan (2016): South Sudan Food Security and Nutrition Monitoring Bulletin. March\n2017.\n\n\nPage 62 of 80", "source": "jdc_operational", "subset": "annotate_aivin_part2", "spans": [{"key": "jdc_operational:000038:65:2:0", "start": 1066, "end": 1122, "surface": "Crop and Livestock Market Information System South Sudan", "probe_tag": "confusion", "probe_score": 0.8902, "luna_label": 1, "luna_reason": "Named market information source used for December 2016 price assumptions"}, {"key": "jdc_operational:000038:65:2:1", "start": 1140, "end": 1166, "surface": "Juba Bi‐Weekly Price Watch", "probe_tag": "confusion", "probe_score": 0.3074, "luna_label": 1, "luna_reason": "Named price bulletin cited as the source for prices used in analysis."}, {"key": "jdc_operational:000038:65:2:2", "start": 1342, "end": 1401, "surface": "South Sudan Food Security and Nutrition Monitoring Bulletin", "probe_tag": "confusion", "probe_score": 0.564, "luna_label": 1, "luna_reason": "Named monitoring bulletin cited as source for cultivated-area findings."}]}, {"key": "aivin2-092", "text": " of 92.5 percent.\n\n16. **Competition for scarce resources between Jordanian students and Syrian refugee students is**\n**resulting in heightened social tensions and increased cases of school–based violence.** Tensions\nbetween Syrian refugee and Jordanian students are visible and have been a matter of concern for\nteachers and school leaders who have limited capacity and support to manage violent and disruptive\nbehaviors in a positive and constructive manner. It is estimated that 70 percent of Syrian refugee\nstudents are bullied or verbally abused in schools (UNICEF 2016), while 78 percent of parents state\nthat their children are subject to physical violence from teachers (UNICEF 2016). Syrian refugee\nstudents are reported to leave school (1,600 students left due to bullying in 2016), or not enter at all,\nto preserve their safety and self‐respect.\n\n17. **Teachers and school leaders are poorly trained to handle violence and disruptive behaviors.**\nTeachers themselves are still prone to use aggressive means for managing classrooms and disciplining\nstudents. In the 2015–2016 school year, 18 percent of children reported experiencing verbal violence\nin schools and 11 percent reported experiencing corporal punishment. Serious concerns also exist\nabout the increase in student‐to‐student violence and disruptive behaviors (particularly in schools\nwith Syrian refugees), including vandalism, harassment, bullying, and gender‐based violence. The\nMOE has made concerted efforts, including the introduction of the school‐based program Ma’an, to\npromote nonviolent and positive student discipline. The MOE has also initiated monthly violence\nsurveys that act as deterrents for teachers from using violence and help to keep all actors accountable\nfor their actions. However, further efforts are needed to support safe school environments and to\nunderstand and tackle the different challenges faced in gender‐segregated schools.\n\n18. **Jordan faces an additional major challenge in relation to its student assessment system.**\nJordan administers several census and sample‐based student assessments that appear", "source": "jdc_operational", "subset": "annotate_aivin_part2", "spans": [{"key": "jdc_operational:000041:12:1:0", "start": 1630, "end": 1654, "surface": "monthly violence\nsurveys", "probe_tag": "confusion", "probe_score": 0.7346, "luna_label": 0, "luna_reason": "MOE-initiated surveys are being conducted as an accountability activity."}]}, {"key": "aivin2-093", "text": "**The World Bank**\nUganda: Roads and Bridges in the Refugee Hosting Districts Project (P171339)\n\n\n|Indicator Name|PBC|Baseline|End Target|\n|---|---|---|---|\n|in place (Text)||||\n|Crash data entered into system, publicly reported, and used in<br>decision making (Yes/No)||No|Yes|\n|Annual number of fatalities or serious injuries involving<br>construction vehicles or at construction sites (Number)<br>||0.00|0.00|\n\n\n\n\n\n\n\n\n\n\n\n\n\n|RESULT_FRAME_TBL_IO|Col2|Col3|Col4|\n|---|---|---|---|\n|<br> <br>**Indicator Name**<br>|<br>**PBC**<br>|<br>**Baseline**|<br>**End Target**|\n|**Road Upgrading Works**|**Road Upgrading Works**|**Road Upgrading Works**|**Road Upgrading Works**|\n|Roads rehablitated (CRI, Kilometers)||0.00|105.00|\n|Roads rehabilitated - rural (CRI, Kilometers)||0.00|105.00|\n|Roads rehabilitated - non-rural (CRI, Kilometers)||0.00|0.00|\n|Increase in road user satisfaction on the Project road corridor<br>(dis-aggregated by gender, refugees, hosts) (Text)||Baseline surveys to be done|Rating of 4 out of 5|\n|Local labor among unskilled employment created under the<br>works contracts (dis-aggregated by gender, refugees", "source": "jdc_operational", "subset": "annotate_aivin_part2", "spans": [{"key": "sample:jdc_operational:000050:56:0:0", "start": 179, "end": 189, "surface": "Crash data", "probe_tag": "confusion", "probe_score": 0.065, "luna_label": 0, "luna_reason": null}]}, {"key": "aivin2-094", "text": "**The World Bank**\nSouth Sudan Enhancing Community Resilience and Local Governance Project (P169949)\n\n\nto higher transportation costs; and (c) needs are greater in more vulnerable, conflict-affected areas. The\nproposed allocation allows the project to support approximately 11 counties that have vulnerability scores\nhigher than 50 (out of 100). However, the number and the list of target counties will change as the\nvulnerability index and its underlying data sets will be updated. There will be two rounds of allocation per\ncounty to maximize communities’ learning-by-doing. Counties will need to meet a set of basic\nperformance indicators to be eligible for the second allocation. These include (a) participation rate of\nwomen, youths, IDPs, and returnees; (b) timely implementation of the subprojects; (c) formation of O&M\ncommittees and development of sustainable O&M measures, among others. All _payams_ and _bomas_ within\nthe target counties will be eligible for subproject budget allocation. Allocations to the _payam_ level will\nfollow the Government’s fiscal transfer formula of 60 percent equal allocation and 40 percent based on\npopulation (utilizing IOM’s DTM projections) <sup>80</sup> [^80: Population figures for urban areas would be calculated based on a headcount or by complementing 2008 census with other data sources (for\nexample, DTM).] whereas all _bomas_ within target _payams_ will receive equal\namount of funding as there are no population data available. Each _payam_ within the same county as well\nas all _bomas_ within the same _payam_ will receive equal amounts as there are no reliable data on their\npopulation sizes. About 65 percent of county allocations will be made available in round one, and more\ncomplex projects will be implemented first to ensure timely project implementation. Should any counties\nbe deemed unfeasible, they will be replaced by ‘replacement counties’ on the long list. In some cases,\ncertain _payams_ within selected counties will be inaccessible or difficult to", "source": "jdc_operational", "subset": "annotate_aivin_part2", "spans": [{"key": "sample:jdc_operational:000049:76:0:0", "start": 1169, "end": 1184, "surface": "DTM projections", "probe_tag": "keep", "probe_score": 0.9504, "luna_label": 1, "luna_reason": null}, {"key": "sample:jdc_operational:000049:76:0:1", "start": 1455, "end": 1470, "surface": "population data", "probe_tag": "confusion", "probe_score": 0.6185, "luna_label": 1, "luna_reason": null}]}, {"key": "aivin2-095", "text": "* . The CPF (report 101173-UG) recognizes that gender inequality and discrimination in access to economic\n\n\n_<mark>Issues Shaping Africa’s Economic Future.</mark>_ <mark>Washington, DC: World Bank</mark> _<mark>.</mark>_\n23 Uganda Communications Commission 2015 survey on Access and Usage of ICTs.\n24 Suri, T and W. Jack. 2016. \"The long-run poverty and gender impacts of mobile money.” _<mark>Science,</mark>_ <mark>Vol. 354, Issue 6317, pp. 1288-</mark>\n<mark>1292.</mark>\n25 Uganda Bureau of Statistics (UBOS) and ICF. 2018. Uganda Demographic and Health Survey 2016. Kampala, Uganda and Rockville,\nMaryland, USA: UBOS and ICF.\n26 Center for Domestic Violence Prevention. 2013. _Economic Costs of Domestic Violence in Uganda_ .\n27 Musime, David. 2019. “Financial Markets for Refugees and Host Communities in Arua and Isingiro Districts.” November.\nWashington DC: World Bank.\n\n\nJun 15, 2021 Page 8 of 13", "source": "jdc_operational", "subset": "annotate_aivin_part2", "spans": [{"key": "jdc_operational:000005:7:2:0", "start": 528, "end": 569, "surface": "Uganda Demographic and Health Survey 2016", "probe_tag": "confusion", "probe_score": 0.6554, "luna_label": 1, "luna_reason": "Named survey cited as an existing demographic and health data source."}]}, {"key": "aivin2-096", "text": "**The World Bank**\nRoads and Employment Project (P160223)\n\n\n\n\n\n\n\n\n\n\n\n\n|Sidewalks|25|High as most material locally produced|\n|---|---|---|\n|Masonry Wall<br>|40|**High** as most material locally produced|\n|Routine<br>Maintenance|60|**High** as most equipment/material locally<br>available|\n|Planting<br>trees/vegetation|75|**High** as most material locally produced|\n\n\n\n7. Targeted roads will be selected from a long priority list that will be finalized following the ongoing\nroad condition visual survey. Candidate road subprojects will be screened, and subjected to\nenvironmental, social and economic analysis on the basis of procedures established under the project.\nThe project will be part of a nationwide program, parallel financed by other donors with the Bank\nbeing the major donor, and the targeted roads may be located in any part of the Lebanese national\nroad network.\n\n\n8. This component will also finance the piloting of an innovative type of multi‐year routine maintenance\ncontracts (two to three years per contract) to be undertaken by small local contractors on a select\nnumber of the newly rehabilitated road sections, estimated at a total of about **US$15 million,** and is\ndesigned to help the Lebanese government remedy the current weaknesses in the management of\nroad maintenance and to increase the durability and efficiency of road investments. Component 1 of\nthe project will also include **US$12 million** as price contingencies.\n\n\n9. Component 1 will also finance consultancy services for the design and construction supervision of\nroad subprojects. The estimated cost of these services, which will be provided primarily by local\nconsultants is estimated at **US$8 million** . Under the project, an important", "source": "jdc_operational", "subset": "annotate_aivin_part2", "spans": [{"key": "jdc_operational:000008:56:0:0", "start": 474, "end": 502, "surface": "road condition visual survey", "probe_tag": "confusion", "probe_score": 0.231, "luna_label": 0, "luna_reason": "Ongoing survey is being conducted to finalize road selection."}]}, {"key": "aivin2-097", "text": "br>|<br>33.3<br>|\n|<br>Proportion of permanent full-time production workers that are female (%)a <br>|<br>1.9<br>|<br>19.0<br>|<br>26.8<br>|\n|<br>Proportion of permanent full-time non-production workers that are female (%)a <br>|<br>9.6<br>|<br>29.4<br>|<br>37.0<br>|\n\n\n_Note:_ a. Using data from manufacturing firms only.\n\n49 Ibid.\n50 World Bank. 2017. Findex database.\n\n\n\nPage 73 of 87", "source": "jdc_operational", "subset": "annotate_aivin_part2", "spans": [{"key": "jdc_operational:000051:78:4:0", "start": 287, "end": 316, "surface": "data from manufacturing firms", "probe_tag": "confusion", "probe_score": 0.7834, "luna_label": 1, "luna_reason": "Existing manufacturing-firm data underlies the reported table figures."}, {"key": "jdc_operational:000051:78:4:1", "start": 354, "end": 369, "surface": "Findex database", "probe_tag": "keep", "probe_score": 0.9184, "luna_label": 1, "luna_reason": "Named Findex database cited as the source for reported table statistics."}]}, {"key": "aivin2-098", "text": "**The World Bank**\nProductive Safety Net for Socioeconomic Opportunities Project (P177663)\n\n\ncollaboration with other organizations and service providers to link HHs with appropriate services. Programmatic and\ngeographic convergence will be proactively ensured with other World Bank funded projects including PEHSP.\n\n43. **The sub-component will also include refugees and host communities in LIPW and complementary social**\n**measures**, based on feasibility assessment to be conducted by an implementing partner. Selected beneficiaries in both\ncommunities will be engaged in selected and screened community priority sub-projects related to contribute towards\nclimate change adaptation and food security. Transfer amounts, frequency and duration will also be aligned to avoid\nfragmentation of support within project beneficiary HHs (i.e., 18 months of cash transfer at the rate of US$2.7 per day\nfor 15 days per month), including for those targeted under the refugee and host communities through the IDA19 WHR\nresources. As the majority of refugees in the two counties reside in refugee camps managed by the UNHCR, the project\nwill ensure strong coordination and collaboration with UNHCR for access and facilitation of project implementation with\nthe aim of the effective and accountable delivery of cash assistance and achievement of project results. Similar\ncommunity-based HH targeting mechanism will be adopted in line with the broader project design, with context-specific\nadjustments to accommodate nuanced considerations and dynamics, as appropriate.\n\n**Sub-Component 1.2: Direct Income Support** **_(US$23 million equivalent)_**\n\n44. **This sub-component will provide unconditional cash transfers to the poorest and most vulnerable HHs that are**\n**labor constrained to engage in LIPW.** A diagnostic of the South Sudan SP sector undertaken by the World Bank found\nthat majority of the safety net interventions in the country tend to include work requirements (i.e., public works, cash\nfor work).", "source": "jdc_operational", "subset": "annotate_aivin_part2", "spans": [{"key": "jdc_operational:000057:25:0:0", "start": 1798, "end": 1837, "surface": "diagnostic of the South Sudan SP sector", "probe_tag": "confusion", "probe_score": 0.679, "luna_label": 1, "luna_reason": "World Bank diagnostic provided evidence for the stated safety-net finding."}]}, {"key": "aivin2-099", "text": "**The World Bank**\nSouth Sudan Enhancing Community Resilience and Local Governance Project (P169949)\n\n\nbuilding power and voice through women’s identification of water and sanitation infrastructure needs.\nThis activity will be measured at the component level with the indicator: proportion of women in WASH\ninfrastructure/O&M groups. Progress on supporting the closing of the gender gaps through these efforts\nwill be measured through gender-disaggregated data in the M&E framework.\n\n\n81. **Citizen Engagement** . Citizen engagement is an essential element of the project, which is based on\na community-driven development approach, to improve community resilience and social cohesion. The\nproject mainstreams citizen engagement throughout the project cycle. Measures built in include:\nestablishment and strengthening of inclusive community institutions; a strong participatory planning\nprocess; inclusion of local communities in project implementation; community-based monitoring; training\non community-led O&M; a robust communication and outreach to communities; and a strong grievance\nredress mechanism to close the feedback loop. This will ensure community ownership of the project,\nadaptation of subprojects on local needs, efficient use of resources, and enhanced sustainability by\nincluding the communities in subproject O&M. Citizen engagement is also an essential tool for social risk\nmanagement, including a functioning grievance redress mechanism, meaningful consultations in line with\nESF/ESS10, prevention of elite capture, and inclusion of the most vulnerable. Implementing partners of\nthis project have considerable experience on citizen engagement in South Sudan, essential for effective\ncitizen engagement in the complex and diverse situations in different parts of the country.\n\n\n**B. Fiduciary**\n\n\n**(i) Financial Management**\n\n82. The overall fiduciary responsibility will be with UNOPS through the PMU with key staff responsible\nfor providing effective FM oversight. Since IOM will participate in the implementation of Components 1\nand 2 (and possibly some of Component 3 activities), IOM will establish similar FM arrangements. This will\nbe", "source": "jdc_operational", "subset": "annotate_aivin_part2", "spans": [{"key": "jdc_operational:000049:43:0:0", "start": 435, "end": 460, "surface": "gender-disaggregated data", "probe_tag": "confusion", "probe_score": 0.0901, "luna_label": 0, "luna_reason": "Future project monitoring through the M&E framework is planned, not existing data use."}]}, {"key": "aivin2-100", "text": " inequalities persist. School enrollment and retention rates\namong girls in the refugees hosting districts are exceptionally low, a result of their domestic\nresponsibilities, child marriage, teenage pregnancy, long distances to schools, and lack of sanitation\n\n\n9 This index reflects gender-based inequalities in three dimensions – reproductive health, empowerment, and economic\n[activity. http://hdr.undp.org/sites/all/themes/hdr_theme/country-notes/UGA.pdf.](http://hdr.undp.org/sites/all/themes/hdr_theme/country-notes/UGA.pdf)\n10 Uganda Demographic and Health Survey (2016).\n11 Uganda Violence Against Children Survey (2015).\n12 UNICEF: Situation Analysis of Children in Uganda, 2015\n13 Government of Uganda: Violence Against Children Survey (VACS) Report, 2018\n14 UDHS, 2016\n15 UNHCR, 2016, 5-Year Interagency SGBV Strategy, Uganda\n_16_ <u>http://ug.one.un.org/sites/default/files/documents/UNAC-</u>\n<u>[Northern%20Uganda%20and%20West%20Nile%20Humanitarian%20and%20Development%20Report%20-January-](http://ug.one.un.org/sites/default/files/documents/UNAC-Northern%20Uganda%20and%20West%20Nile%20Humanitarian%20and%20Development%20Report%20-January-February%202018.pdf)</u>\n<u>[February%202018.pdf](http://ug.one.un.org/sites/default/files/documents/UNAC-Northern%20Uganda%20and%20West%20N", "source": "jdc_operational", "subset": "annotate_aivin_part2", "spans": [{"key": "jdc_operational:000001:5:2:0", "start": 534, "end": 570, "surface": "Uganda Demographic and Health Survey", "probe_tag": "confusion", "probe_score": 0.8688, "luna_label": 1, "luna_reason": "Named survey cited as evidence for preceding education and gender findings."}, {"key": "jdc_operational:000001:5:2:1", "start": 582, "end": 621, "surface": "Uganda Violence Against Children Survey", "probe_tag": "confusion", "probe_score": 0.8202, "luna_label": 1, "luna_reason": "Named survey cited as an existing source in the reference list."}]}, {"key": "aivin2-101", "text": "**Annex 1: Results Framework and Monitoring**\n\n**Republic of Chad: Emergency Food and Livestock Crisis Response Project (P151215)**\n\n\n**Project Development Objective**\n\n\nThe project development objective is to improve the availability of and access to food and livestock productive capacity for targeted beneficiaries affected by the conflict in the\nCentral African Republic on the Recipient’s territory.\n\n\n**<mark>These results are at</mark>** Project Level\n\n\n**Project Development Objective Indicators**\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|Col1|Col2|Col3|Col4|Cumulative Target Values|Col6|Col7|Col8|Col9|Data source/|Responsibility for|\n|---|---|---|---|---|---|---|---|---|---|---|\n|**Indicator name**|**Core**|**Unit of**<br>**measure**|**Baseline**|**YR1**|**YR2**|**YR3**|<br>**End target**|**Frequency**|**methodology**|**data collection**|\n|Number of<br>agricultural input<br>packages distributed<br>to beneficiaries in the<br>target areas||Tons|0.00|5,000|<br>10,000<br>|15,000|<br>15,000|Quarterly|M&E and surveys|FAO, NGOs, MAE,<br>EAPSP|\n|Number of direct<br>beneficiaries of<br>vouchers or direct<br>food transfers||Number|0.", "source": "jdc_operational", "subset": "annotate_aivin_part2", "spans": [{"key": "sample:jdc_operational:000007:31:0:0", "start": 1006, "end": 1021, "surface": "M&E and surveys", "probe_tag": "confusion", "probe_score": 0.2647, "luna_label": 0, "luna_reason": null}]}, {"key": "aivin2-102", "text": "ics<br>reports<br>|<br>Administrative data<br>|<br>PMU/MOPH<br>|\n|Percentage of residents of Lebanon who<br>are fully vaccinated, total and<br>disaggregated by sex, age risk, group and<br>nationality (including refugees and host<br>communities).|<br>The indicator will track the<br>number of eligible people<br>as defined among a specific<br>set of priority groups in the<br>National Deployment and<br>Vaccination Plan<br>(NVDP)/government<br>prioritization list who are<br>fully vaccinated from<br>COVID-19 using vaccines<br>that meet the Bank's<br>vaccine approval criteria.<br>This indicator will be|<br>6 months<br>|MOPH<br>reports,<br>National<br>Vaccine digital<br>platform<br>(IMPACT)<br>|Administrative data<br>|PMU/MOPH<br>|\n\n\nPage 42 of 54", "source": "jdc_operational", "subset": "annotate_aivin_part2", "spans": [{"key": "jdc_operational:000000:46:1:0", "start": 696, "end": 715, "surface": "Administrative data", "probe_tag": "drop", "probe_score": 0.0335, "luna_label": 0, "luna_reason": "Planned indicator verification source, not demonstrated existing data use"}]}, {"key": "aivin2-103", "text": " support the implementation of the project with regard to these technical\nitems, the following measures will be undertaken:\n\n\na. The project will finance specialized consulting firms to undertake the required technical designs, which\nwill be reviewed the by Bank. In addition, specialized road engineering consultants will be financed from\nthe loan to ensure that road works are implemented according to design standards.\n\n\nb. As data availability and data collection practices is weak in Lebanon, and given the shortcomings of\nprevious projects to establish a sustainable asset management system despite heavy investments in\nsoftware and laboratory equipment, the project will design a simple and rather basic asset management\nsystem which requires little data collection and low cost data collection techniques (visual survey of the\nroad condition, IRAP safety rating, and traffic data). The asset management system will be implemented\nin collaboration with international consultants and universities, who will also provide capacity building\nto Lebanese consultants on data collection and update methodology. The asset management system will\nbe installed within both CDR and MPWT, with IT linkages, therefore ensuring redundancy and\nsustainability. Finally, an engineer will be financed from the loan to be part of the PIU and in charge of\nthe maintenance and update of the asset management system to support CDR and MPWT staff. The\nWorld Bank will bring international experience in best practices regarding road asset management\nsystems and will mobilize resources and expertise to assess the network vulnerability and improve its\n\n\nPage 65 of 90", "source": "jdc_operational", "subset": "annotate_aivin_part2", "spans": [{"key": "sample:jdc_operational:000008:68:1:0", "start": 814, "end": 849, "surface": "visual survey of the\nroad condition", "probe_tag": "confusion", "probe_score": 0.2576, "luna_label": 0, "luna_reason": null}, {"key": "sample:jdc_operational:000008:68:1:1", "start": 851, "end": 869, "surface": "IRAP safety rating", "probe_tag": "drop", "probe_score": 0.0066, "luna_label": 0, "luna_reason": null}, {"key": "sample:jdc_operational:000008:68:1:2", "start": 875, "end": 887, "surface": "traffic data", "probe_tag": "confusion", "probe_score": 0.2222, "luna_label": 0, "luna_reason": null}]}, {"key": "aivin2-104", "text": "**The World Bank**\nStrengthening Lebanon’s Covid-19 Response (P178478)\n\n\nand additional staffing will be hired to carry out the additional work required as needed. The current Financial\nOfficer and Financial Assistant will be responsible for handling the FM aspects of the project under the supervision\nof the Project Director. Both have experience in implementing World Bank-financed projects. The World Bank will\ncontinue to provide the necessary training to the Financial Officer, Financial Assistant and any new staff recruited\non World Bank FM procedures. MoPH is in the process of recruiting a stock management officer who will be\nresponsible for the vaccine stock inventory and will support the ministry in aligning the stock count with the\ntechnical audit records.\n\ng. _Internal controls:_ The MoPH has limited internal controls functions. The internal controls are set according to the\n\nMoPH’s internal bylaws. For this operation, the project PMU will prepare an FM chapter for the POM, containing\ndetailed information about the FM procedures and rules governing the flow of funds and internal control\nprocedures, as well as the specific responsibilities of each member of the unit. The POM will need to be finalized\nwithin one month of project effectiveness. To strengthen the internal controls for the project, the MoPH will hire\ntechnical auditor(s) to verify the COVID-19 vaccination activities and COVID-19 hospitalization claims. The\ntechnical auditor(s) will be responsible to independently: (i) verify the GOL’s compliance of the deployment of the\nWorld Bank-financed vaccines with the NDVP, WHO standards and World Bank requirements reflected in the legal\nagreements, Environmental and Social safeguards and the POM; and (ii) validate the payments made 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", "source": "jdc_operational", "subset": "annotate_aivin_part2", "spans": [{"key": "jdc_operational:000000:54:0:0", "start": 748, "end": 771, "surface": "technical audit records", "probe_tag": "drop", "probe_score": 0.045, "luna_label": 0, "luna_reason": "Project control records used for stock reconciliation, not substantive evidence."}]}, {"key": "aivin2-105", "text": " CGAP.\n10 Uganda remittances were US$1.3 billion in 2019, US$1.425 billion in 2018 and US$1.2 billion in 2017, World Bank 20172019 data.\n11 The Economic Policy Research Centre conducted a rapid survey of businesses which indicated that three-quarters of businesses\nhave laid off employees due to the risks and subsequent containment measures presented by COVID-19, and estimated that 3.8\nmillion workers would lose their jobs permanently while 625,957 workers risk losing their jobs permanently, if the threat of\nCOVID and associated containment measures persist for the next six months.\n\n\nJun 09, 2020 Page 5 of 9", "source": "jdc_operational", "subset": "annotate_aivin_part2", "spans": [{"key": "sample:jdc_operational:000043:4:2:0", "start": 111, "end": 135, "surface": "World Bank 20172019 data", "probe_tag": "drop", "probe_score": 0.0269, "luna_label": 1, "luna_reason": "World Bank data supports the reported 2017–2019 remittance figures."}]}, {"key": "aivin2-106", "text": " model will introduce and maintain a minimum standard of quality for a lower secondary education school\nand develop schools as safe learning spaces.\n\n\n33. **Approach to targeting sub-counties** :\n\n     - There are 135 districts in Uganda (as of 2016), including 13 refugee hosting districts (RHDs). The Project\nwill target sub-counties in 96 districts with low enrollment rates, high unsatisfied demand for lower\nsecondary education, and no public secondary school. All RHDs will be supported under the Project.\n\n     - The Project will also include 84 non-refugee hosting local governments (LG). The 84 LG were selected\nusing the following approach. First, only LGs which have sub-counties without a public secondary school\n(“underserved subcounty”) were considered as Uganda implements one-public-school-per-subcounty\npolicy. There are 90 such LGs. Second, the LGs which do not have enough primary feeder schools in\nunderserved sub-counties were removed. Based on the current primary to secondary transition patterns\nand experience from private sector constructing new secondary schools, a minimum of seven primary\nschools are required to provide sufficient number of graduates to feed in a new large (eight classrooms,\ntwo stream) lower secondary school. Thus, six LG were removed from the list brining the final number to\n84 LG.\n\n     - Unfortunately, enrollment data is not available on sub-county level. Thus, the demand assessment used\ndistrict/LG level information as a proxy. In 70 out of 84 selected LGs, the GER is below average for Uganda,\nand in 14 districts it exceeds the average. However, while the GER for the district as a whole is higher than\nexpected, there are sub-counties/areas in these districts which provide limited opportunities for\ncontinuing education in secondary schools and unsatisfied demand for lower secondary education is high.\nThe demand for each subcounty will be established and verified during the", "source": "jdc_operational", "subset": "annotate_aivin_part2", "spans": [{"key": "sample:jdc_operational:000018:22:1:0", "start": 1356, "end": 1371, "surface": "enrollment data", "probe_tag": "confusion", "probe_score": 0.6073, "luna_label": 1, "luna_reason": null}, {"key": "sample:jdc_operational:000018:22:1:1", "start": 1443, "end": 1472, "surface": "district/LG level information", "probe_tag": "drop", "probe_score": 0.0, "luna_label": 1, "luna_reason": null}]}, {"key": "aivin2-107", "text": "**The World Bank**\nChad - Refugees and Host Communities Support Project (P164748)\n\n\n\n\n\n\n\n\n\n\n|Health centers rehabilitated or newly built|Col2|Twice a<br>year|Baseline data<br>collected<br>from UNHCR<br>and WFP on<br>number of<br>health<br>centers built<br>or<br>rehabilitated<br>in target<br>areas. The<br>CFS is<br>launching a<br>baseline<br>study which<br>will help to<br>confirm<br>baseline<br>numbers, to<br>be reviewed<br>at MTR.<br>CFS<br>Management<br>information<br>system -<br>CNARR -<br>Ministry of<br>Health|CFS local offices<br>produce simple reports<br>by region on number of<br>health centers<br>rehabilitated or newly<br>built. Reports are then<br>consolidated by CFS<br>centrally and shared<br>with the Project<br>Steering Committee<br>and with the World<br>Bank. There will be two<br>reports per year in June<br>and December. Figures<br>are reported for the<br>period in question (6<br>months) and also<br>cumulatively.|CFS|\n|---|---|---|---|---|---|\n|Students attending new or rehabilitated<br>schools||Quarterly<br>report<br>|Baseline data<br>collected<br>from UNHCR|CFS local offices<br>produce simple reports<br>by region on|CFS<", "source": "jdc_operational", "subset": "annotate_aivin_part2", "spans": [{"key": "jdc_operational:000035:54:0:0", "start": 158, "end": 171, "surface": "Baseline data", "probe_tag": "drop", "probe_score": 0.0236, "luna_label": 0, "luna_reason": "The sentence describes baseline data being collected and a future baseline study."}]}, {"key": "aivin2-108", "text": "**The World Bank**\nCHAD Improving Learning Outcomes Project (P175803)\n\n\n24. The objective of this sub-component is to improve the accountability and coverage of the salary payment system\nfor teachers. There will be four activities, linked to five PBCTs as shown by Table 2. First, the government will develop\nand approve a teacher recruitment and salary payment policy, as well as a budgeted plan for its implementation. The\npolicy will include _inter alia:_ (i) lifting of the moratorium on state hiring of ENIB graduates, (ii) posting strategy that\nprioritizes rural communities in need, and (iii) revising state-salaried teacher categories to accommodate the official\nrecognition and integration of community teachers. The budgeted plan will progressively integrate all eligible community\nteachers first into the subsidy payments and subsequently onto the state payroll. Second, Ministry personnel will be\ntrained to regularly conduct a census (using Kobo toolbox or a similar tool) of all teachers working at community schools\nmapped under sub-component 3.2 that are eligible to be officially recognized as state schools. The census will gather and\ndigitize all relevant data pertaining to the teacher to constitute a personnel dossier as per state norms. The census will\nalso enable the MENPC and government to screen the teaching personnel for eligibility to be recognized as a teacher in\na state school. A professional development plan will also be elaborated for teachers who require further in-service\ntraining to meet the necessary criteria. Third, eligible community teachers will be formally incorporated onto the\npersonnel list of subsidized public-school teachers and will be progressively incorporated into the subsidy payments and\npayroll as per the approved plan. Finally, the government will strengthen the mobile money subsidy payment system\nmanaged by APICED, building on the innovations and lessons learned under the Bank-financed ESRP-II. This will ensure\nthe functioning and maintenance of the system, as well as systematic checks on personnel lists and the receipt of salaries.\nThis", "source": "jdc_operational", "subset": "annotate_aivin_part2", "spans": [{"key": "jdc_operational:000009:22:0:0", "start": 940, "end": 946, "surface": "census", "probe_tag": "drop", "probe_score": 0.0401, "luna_label": 0, "luna_reason": "The project will conduct this census as a future teacher-data collection activity."}]}, {"key": "aivin2-109", "text": "**Annex III: Implementation Arrangements**\n\n\n**LEBANON**\n**Emergency National Poverty Targeting Program Project (P149242)**\n\n**Institutional and Implementation Arrangements**\n\n\n1. With respect to the institutional setup of the NPTP, the program has been managed by the\nMOSA and the Presidency of the Council of Ministers (PCM). This was deemed the best option\nat the time of appraisal of the ESPISP II project, which supported the creation of the NPTP. The\npresent institutional setup will be retained during the implementation of the Emergency NPTP.\nHowever, an external unit (FOT) under the PCM will handle the fiduciary aspects of the project.\n\n2. The SDCs will continue supporting the implementation of the NPTP by hosting the social\nworkers who register beneficiaries, administer household questionnaires, do data entry, and\noverall follow up for the NPTP.\n\n\n3. With respect to the NPTP implementation and institutional structure, the following\nexplains the overall implementation arrangements of the program:\n\n\n     - The Council of Ministers makes policy decisions related to the NPTP, allocates\n\nannual budget, and defines cut-off scores which determine benefits.\n\n     - The Social-IMC reviews progress of NPTP and makes recommendations to the\n\nCouncil of Ministers.\n\n\n     - The NPTP Project Unit in the MOSA is responsible for the following: (i)\n\nmanaging the NPTP database in MOSA; (ii) receiving household applications;\n(iii) interfacing with applicants; (iv) entering data; (v) conducting household\nvisits; (vi) checking for data errors; (vii) transmitting data to the central database\nof the NPTP CMU; (viii) verifying claims from hospitals, schools, and PHCs and\nauthorizing payments; (ix) managing the outreach campaign; (x) managing the ecard food voucher beneficiaries list, delivery of the e-cards to beneficiaries, and\nfollow up; and (xi) monitoring", "source": "jdc_operational", "subset": "annotate_aivin_part2", "spans": [{"key": "sample:jdc_operational:000047:41:0:0", "start": 1371, "end": 1384, "surface": "NPTP database", "probe_tag": "drop", "probe_score": 0.0017, "luna_label": 0, "luna_reason": "Names a database managed administratively without showing its data informing analysis or decisions."}, {"key": "sample:jdc_operational:000047:41:0:1", "start": 1607, "end": 1615, "surface": "NPTP CMU", "probe_tag": "drop", "probe_score": 0.0, "luna_label": 0, "luna_reason": null}, {"key": "sample:jdc_operational:000047:41:0:2", "start": 1755, "end": 1792, "surface": "ecard food voucher beneficiaries list", "probe_tag": "drop", "probe_score": 0.0001, "luna_label": 0, "luna_reason": null}]}, {"key": "aivin2-110", "text": " between construction firms it does not permit any\nforced partnerships. Therefore, the PPDA instruction that 30 percent of the Civil works should be outsourced\nto local staff and companies shall not apply. However, the contract will require that the Contractor only hires\nUgandans for non-skilled, and semi-skilled trades including operation of various equipment. UNRA has put in\nplace a robust contract management arrangement including strengthened its in house monitoring and\nsupervision capacity for the contract execution stage.\n\nFor high-value, high-risk, or complex contracts such as the road works, contract management plans will be\nprepared. To mitigate procurement capacity risks, there will be a need for staff capacity building and training,\n<u>continuous oversight, reviews and audits, and the use of real-time monitoring and tracking tools.</u>\n\n20. **Systematic Tracking of Exchanges in Procurement (STEP).** The project will use STEP, a planning and\ntracking system, which would provide data on procurement activities, establish benchmarks, monitor delays and\nmeasure procurement performance.\n\n21. **Use of National Procurement System.** National procurement procedures shall only apply if the\nrequirements as required by paragraph 5.3 of the Procurement Regulations <sup>64</sup> are met. In March 2017 (updated\n\n\n64 (a) open advertising of the procurement opportunity at the national level; (b) the procurement is open to eligible firms from any country;\n(c) the request for bids/request for proposals document shall require that Bidders/Proposers submitting Bids/Proposals present a signed\nacceptance at the time of bidding, to be incorporated in any resulting contracts, confirming application of, and compliance with, the Bank’s\nAnti-Corruption Guidelines, including without limitation the Bank’s right to sanction and the Bank’s inspection and audit rights; (d)\nProcurement Documents include provisions, as agreed with the Bank,", "source": "jdc_operational", "subset": "annotate_aivin_part2", "spans": [{"key": "jdc_operational:000050:69:1:0", "start": 1002, "end": 1032, "surface": "data on procurement activities", "probe_tag": "drop", "probe_score": 0.0489, "luna_label": 0, "luna_reason": "Future STEP output is planned, not existing data used for analysis."}]}, {"key": "aivin2-111", "text": "**The World Bank**\nStrengthening Lebanon’s Covid-19 Response (P178478)\n\n\n|Indicator Name|PBC|Baseline|Intermediate Targets|Col5|Col6|Col7|End Target|\n|---|---|---|---|---|---|---|---|\n|<br>|||**1 **|**2 **|**3 **|**4 **||\n|vaccination service that they<br>received (Percentage)<br> <br>||||||||\n\n\n\n\n\n|Monitoring & Evaluation Plan: PDO Indicators|Col2|Col3|Col4|Col5|Col6|\n|---|---|---|---|---|---|\n|**Indicator Name **|**Definition/Description **<br>|**Frequency **|**Datasource **|**Methodology for Data**<br>**Collection **|**Responsibility for Data**<br>**Collection **|\n|Number of COVID-19 vaccine doses<br>acquired through project financing|This indicator will measure<br>the number of COVID-19<br>vaccines that have been<br>procured by the GOL<br>through World Bank<br>financing support. <br>|6 months<br>|Vaccine<br>logistics<br>reports<br>|<br>Administrative data<br>|<br>PMU/MOPH<br>|\n|Percentage of residents of Lebanon who<br>are fully vaccinated, total and<", "source": "jdc_operational", "subset": "annotate_aivin_part2", "spans": [{"key": "jdc_operational:000000:46:0:1", "start": 880, "end": 888, "surface": "PMU/MOPH", "probe_tag": "drop", "probe_score": 0.0371, "luna_label": 0, "luna_reason": "Standalone table cell naming responsible data collectors, not a data resource."}]}, {"key": "aivin2-112", "text": "39. The NPTP Project Unit in the MOSA is responsible for the following: (i) managing the\nNPTP database in MOSA; (ii) receiving household applications; (iii) interfacing with applicants;\n(iv) entering data; (v) conducting household visits; (vi) checking for data errors; (vii)\ntransmitting data to the central database of the NPTP CMU; (viii) verifying claims from\nhospitals, schools, and primary healthcare centers (PHCs) and authorizing payments; (ix)\nmanaging the outreach campaign; (x) managing the e-card food voucher beneficiaries list,\ndelivery of the e-cards to beneficiaries, and follow up; and (xi) monitoring of the program\n(specifically inputs and outputs).\n\n40. The NPTP CMU in the PCM is responsible for the following: (i) managing the central\ndatabase; (ii) validating data and cross-checking with national databases; (iii) processing\nhousehold data and generating scores and ranks according to the PMT formula; (iv) maintaining\nthe PMT formula, and providing the list of beneficiaries (v) analyzing national data and reporting\nfindings to the Social Inter-Ministerial Committee (Social-IMC); (vi) monitoring of program\nresults including targeting performance; and (vii) auditing data processing.\n\n41. MOSA SDCs are responsible for: (i) receiving household applications and interface with\napplicant; (ii) data entry into program application; (iii) conducting household visits; (iv)\nchecking possible data errors in application forms against provided official documents; (v)\ntransmitting households’ application data to MOSA central unit; and (vi) handling appeals and\nclaims received by households.\n\n42. With respect to the implementation arrangements of the e-card food voucher, the\nfollowing arrangements have been agreed upon: (i) WFP will conduct training for NPTP field\nwork coordinators and social workers, including on", "source": "jdc_operational", "subset": "annotate_aivin_part2", "spans": [{"key": "sample:jdc_operational:000047:24:0:0", "start": 89, "end": 110, "surface": "NPTP database in MOSA", "probe_tag": "confusion", "probe_score": 0.1266, "luna_label": 0, "luna_reason": null}, {"key": "sample:jdc_operational:000047:24:0:1", "start": 849, "end": 863, "surface": "household data", "probe_tag": "drop", "probe_score": 0.0043, "luna_label": 0, "luna_reason": null}, {"key": "sample:jdc_operational:000047:24:0:2", "start": 1014, "end": 1027, "surface": "national data", "probe_tag": "confusion", "probe_score": 0.114, "luna_label": 1, "luna_reason": null}]}, {"key": "aivin2-113", "text": " 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, direct payments and payments under\nSpecial Commitments including full documentation or against statements of expenditure, as appropriate.\nFor components 1 and 2, a lump sum amount will be disbursed in the form of UN blanket commitments\nto WFP and UNICEF (Component 1), and FAO (Component 2) following submission of a duly executed\ncontract between the respective UN agency and MAFS and a Payment Request from that agency (see Fig\nA2.2). WFP, UNICEF and FAO will then provide quarterly funds utilization reports to the PIU within 45 days\nafter the end of the quarter, which will be used to account for expenditures in the Bank records.\n\n\n26. For Component 3, the proceeds of the Grant will be disbursed into the DA following the transaction–\nbased SoE method. The PIU will submit Withdrawal Applications accompanied by SoE incurred to the\nWorld Bank for replenishment of the DA. The project will also maintain a local currency sub‐project\naccount for making payments denominated in local currency. Funds will only be transferred from the main\nDA to the local currency sub‐account in order to meet immediate payment obligations. No significant cash\nbalances will be maintained in local currency to reduce the foreign exchange exposure risk. MAFS will be\nresponsible for initiating, incurring and authorizing expenditures under the Project in accordance with the\nspecified procedures and initiating the payment process with all the required supporting documentation.\nDetailed disbursements arrangements are documented in the Disbursement Letter.\n\n\nPage 48 of 80", "source": "jdc_operational", "subset": "annotate_aivin_part2", "spans": [{"key": "sample:jdc_operational:000038:51:1:0", "start": 833, "end": 845, "surface": "Bank records", "probe_tag": "drop", "probe_score": 0.0018, "luna_label": 0, "luna_reason": null}]}, {"key": "aivin2-114", "text": "**The World Bank**\nEthiopia Digital ID for Inclusion and Services Project (P179040)\n\n\n18. **According to the latest data available from UNICEF, only 3 percent of children** **under 5 years of age have their**\n**birth registered.** <sup>**18**</sup> Through the World Bank-funded Health SDG Program (P123531), the percentage of births occurring in\na given year that were registered attained 20.9 percent in 2022. <sup>19</sup> In 2016, kebeles introduced paper-based and manual\nrecording of births, deaths, marriages, and divorces. In May 2021, the Immigration, Nationality and Vital Events Agency—\nnow known as Immigration and Citizenship Services (ICS)—unveiled a Civil Registration and Vital Statistics Improvement\nPlan for 2022–2026. <sup>20</sup> Digitalization is a major component, supported by the World Bank’s Program for Results (Hybrid)\nfor Strengthening Primary Health Care Services (P175167) project.\n\n\n19. **In line with the Digital Ethiopia 2025 Strategy,** <sup>**21**</sup> **the GoE began an initiative in 2019 to establish a foundational**\n**ID system as a complement—not a replacement—to the existing Kebele IDs.** The intention of the new ID system is to\nprovide a trusted source of identity, including for online transactions, while Kebele IDs will continue to provide proof of\naddress and residence. In the same year, the GoE developed the Principles and Governance Structure of the National\nIdentity Program, which emphasized inclusion for all residents (including refugees) of Ethiopia and alignment with the\nPrinciples on Identification for Sustainable Development. <sup>22</sup> Responsibility was transferred from the", "source": "refugee_pads", "subset": "annotate_aivin_part2", "spans": [{"key": "refugee_pads:000005:15:0:0", "start": 116, "end": 142, "surface": "data available from UNICEF", "probe_tag": "keep", "probe_score": 0.912, "luna_label": 1, "luna_reason": "UNICEF data supports the reported 3 percent birth-registration finding."}]}, {"key": "aivin2-115", "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": "refugee_pads", "subset": "annotate_aivin_part2", "spans": [{"key": "refugee_pads:000175:38:1:1", "start": 870, "end": 881, "surface": "survey data", "probe_tag": "keep", "probe_score": 0.9348, "luna_label": 1, "luna_reason": "Existing survey data supports enrollment findings and identifies a classification limitation."}, {"key": "refugee_pads:000175:38:1:2", "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 the finding that parents withdraw girls from school."}]}, {"key": "aivin2-116", "text": " has ratified the 1951 Refugee Convention\nand the 1967 Protocol Relating to the Status of Refugees and nine international and regional human rights\ninstruments relevant to refugee protection. These are domesticated into Uganda’s legal system through\n\n\n14 Based on the Uganda Refugee Protection Assessment Update August 4-22, 2022.\n\n\nPage 11 of 81", "source": "refugee_pads", "subset": "annotate_aivin_part2", "spans": [{"key": "sample:refugee_pads:000001:16:2:0", "start": 268, "end": 311, "surface": "Uganda Refugee Protection Assessment Update", "probe_tag": "keep", "probe_score": 0.9477, "luna_label": 1, "luna_reason": null}]}, {"key": "aivin2-117", "text": "**The World Bank**\nGenerating Growth Opportunities and Productivity for Women Enterprises Uganda Project (P176747)\n\n\nowned enterprises without children. <sup>19</sup> [^19: Delecourt, S. and Fitzpatrick, A. 2021. “Childcare Matters: Female Business Owners and the Baby-Profit Gap.” Management Science, Vol, 67, No.\n7. May 13.] With total fertility rates in Uganda still very high at 4.7 children per woman, care\nburdens are compounded for women.\n\n13. **Social norms and risks of violence against women also influence the choices of Ugandan women for businesses**\n**sectors and sizes.** Women can feel discouraged from entering or expanding in more profitable (male-dominated) sectors,\nas doing so may signal their transgression of gender norms about men being the main income providers in households.\nRisk of violence also constitutes a significant barrier to women’s entrepreneurship in Uganda. A 2020 national survey of\nviolence against women reports that almost all (95 percent) of Ugandan women between 15–49 years old have\nexperienced physical or sexual violence from either an intimate partner or a non-partner during their lifetime. <sup>20</sup> [^20: Uganda Bureau of Statistics (2021). Uganda Violence Against Women and Girls Survey 2020. Uganda Bureau of Statics. Kampala, Uganda. This\nsurvey was designed as part of the UNHS and drew from UNHS samples which are nationally representative.] This is\nmore than three times the global average (27 percent lifetime,) and the averages for Sub-Saharan Africa (33 percent\nlifetime). <sup>_21_</sup> [^21: World Health Organization (2021). Violence against women prevalence estimates, 2018: global, regional and national prevalence estimates for\nintimate partner violence against women and global and regional prevalence estimates for non-partner sexual violence against women. Geneva:\nWorld Health Organization.] More than half reported that their partners insisted on knowing where they were", "source": "refugee_pads", "subset": "annotate_aivin_part2", "spans": [{"key": "refugee_pads:000088:14:0:0", "start": 898, "end": 944, "surface": "2020 national survey of\nviolence against women", "probe_tag": "keep", "probe_score": 0.9435, "luna_label": 1, "luna_reason": "Existing survey supports the reported 95 percent violence finding."}]}, {"key": "aivin2-118", "text": "), which falls under the authority of the Deputy Prime\nMinister and Minister of State for Public Sector Modernization.\n\n**8.** **Jordan consistently ranks above average among middle-income countries on government effectiveness, rule of law,**\n**regulatory quality, and control of corruption, but below average on voice and accountability.** <mark>International benchmarks</mark>\n<mark>and opinion surveys suggest that improvement is needed in transparency and access to information, social accountability,</mark>\n<mark>and grievance redress mechanisms to support citizens’ trust in government. This is an objective of the government reform</mark>\n<mark>agenda which aims at promoting e-participation, enforcing public access to information, institutionalizing stakeholder</mark>\n<mark>consultation to inform policy making and implementation, and at improving government responsiveness to citizen</mark>\n<mark>feedback.</mark> According to the United Nations (UN) e-government index and the World Bank (WB) GovTech Maturity index, <sup>6</sup> [^6: See Jordan’s detailed rating in Technical Assessment.]\ndespite significant progress in digital government, there is an opportunity for improvement to voice and accountability,\nas well as to access to and quality of services. Internet and mobile connectivity and the use of internet social media is\nwidespread, with close to 10 million internet users in 2023 (an 88 percent penetration rate). There are over 8.5 million\nactive cellular mobile connections, and over 6.5 million social media users (that is, 58 percent of the population), with 45\npercent of users being women. <sup>7</sup> [^7: Kemp, Simon. 2023. “Digital 2023: Jordan.” Datareportal. https://datareportal.com/reports/digital-2023-jordan.]\n\n**9.** **Jordan has been actively working on the digitalization of public services", "source": "refugee_pads", "subset": "annotate_aivin_part2", "spans": [{"key": "sample:refugee_pads:000181:12:1:0", "start": 389, "end": 404, "surface": "opinion surveys", "probe_tag": "keep", "probe_score": 0.9865, "luna_label": 1, "luna_reason": null}, {"key": "sample:refugee_pads:000181:12:1:1", "start": 963, "end": 981, "surface": "e-government index", "probe_tag": "keep", "probe_score": 0.9043, "luna_label": 1, "luna_reason": null}, {"key": "sample:refugee_pads:000181:12:1:2", "start": 1006, "end": 1028, "surface": "GovTech Maturity index", "probe_tag": "keep", "probe_score": 0.9266, "luna_label": 1, "luna_reason": null}]}, {"key": "aivin2-119", "text": "\nGovernment focuses on reforming state-owned enterprise governance, taking steps to implement the\nCode of Good Governance, appointing new executive boards, and signing performance contracts with five\npublic enterprises.\n\n\n7. **Djibouti is reforming its public sector, but it continues to lag behind comparators on governance**\n**indicators.** According to the 2017 Ibrahim Index of African Governance (IIAG), the country scored 46.4\npercent and was ranked 38 out of 54 countries in Africa, a deterioration of 0.15 percent compared to the\naverage annual trend of the previous five years. Djibouti also fares poorly on the World Bank’s WGI. For\nexample, regarding voice and accountability, it ranks in the bottom 10 percent of the 214 countries\nranked, reflecting limited interaction with citizens and businesses. Djibouti ranks in the bottom third of\n214 countries regarding control of corruption, a significant drop from being above the 50th percentile in\n2008. Further, Djibouti ranks in the bottom 20 percent on government effectiveness, indicating gaps in\nservice delivery and the efficiency of the administration.\n\n\n8. **To address these gaps, Djibouti is taking steps to adopt e-government.** With investment in egovernment infrastructure (www.egouv.df), the Government has created a National Agency for State\nInformation System ( _Agence Nationale de Systèmes d’Informations de l’État,_ ANSIE). Its goal is to\nmodernize public administration and make it more efficient. It also plans an open data platform to\nincrease access to information. According to the 2017 IIAG, Djibouti was ranked among the top 10\n\n\n4 Vision Djibouti 2035 targets a medium-term growth rate of 7.5–10 percent per year, tripling per capita income, and reducing\nunemployment. It includes five pillars: peace and national unity, good governance, economic diversification, human capital\ndevelopment, and regional integration.\n5 International Monetary Fund Country Report", "source": "refugee_pads", "subset": "annotate_aivin_part2", "spans": [{"key": "refugee_pads:000142:12:1:2", "start": 1564, "end": 1573, "surface": "2017 IIAG", "probe_tag": "keep", "probe_score": 0.9558, "luna_label": 1, "luna_reason": "Named governance index cited for Djibouti’s ranking."}]}, {"key": "aivin2-120", "text": " survey within\nthe duration of the ASPIRE MPA to seek feedback on benefits and services provided by the program. A\ncitizen engagement strategy will be developed to maintain continuous engagement and communication\nwith beneficiaries and citizens overall and contribute to building trust and a social contract. In addition,\nongoing citizens’ feedback will be considered when implementing the activities of the MPA phases, and\nPENRA will publish the results of the beneficiary surveys on its website, as a key results indicator for citizen\nengagement.\n\n\nPage 38 of 74", "source": "refugee_pads", "subset": "annotate_aivin_part2", "spans": [{"key": "refugee_pads:000133:41:2:0", "start": 462, "end": 481, "surface": "beneficiary surveys", "probe_tag": "confusion", "probe_score": 0.5372, "luna_label": 0, "luna_reason": "Planned beneficiary surveys are future project feedback activities."}]}, {"key": "aivin2-121", "text": "**Annex 1:** **Project** **Design** **Summary**\n\n**SIERRA LEONE:** **NATIONAL** **SOCIAL ACTION** **PROJECT**\n\n\n. **Hierarchy o.Qbijctives -'**  - . **diator** **r**, t **,P** **jCitidaI** **r!** **As's-umptIons,Y-**\n**Sector-related** **CAS** **Goal:** **Sector** **Indicators:** **Sector/ country reports:** **(from** **Goal** **to Bank** **Mission)**\nMitigate the risk of renewed 1. National conflict/security- - UNHCR/OCHA reports - Continued peace and\n**conflict** **and lay foundation** related indicators - Household Income and regional security\n**for** **poverty reduction and** 2. Inter-regional disparities in Expenditure Surveys - Economic and political\n**improvements** **in nutrition,** I-PRSP & PRSP core - PETS surveys stability\n**health, education** **and** indicators - Strategic Planning and\n**targeting** **the rural** 3. Inter-regional disparities in Action Process (SPP) reports\n**population,** women **and** Popular Benchmarks\n**children.**\n\n\n**Project** **Development** **Outcome** **/** **Impact** **Project reports:** **(from** *", "source": "refugee_pads", "subset": "annotate_aivin_part2", "spans": [{"key": "refugee_pads:000017:29:0:0", "start": 590, "end": 639, "surface": "Inter-regional disparities in Expenditure Surveys", "probe_tag": "confusion", "probe_score": 0.6578, "luna_label": 0, "luna_reason": "Table cell fragment, not an independently cited or analyzed data resource."}, {"key": "refugee_pads:000017:29:0:1", "start": 721, "end": 733, "surface": "PETS surveys", "probe_tag": "confusion", "probe_score": 0.8347, "luna_label": 1, "luna_reason": "Named survey source listed for sector indicators and country reporting."}]}, {"key": "aivin2-122", "text": "43 \nthe Customs \nGolden List  \nfollow expedited clearance including lowered \nguarantees, green channel streaming, cursory \ndocument review, and minimal to no physical \ninspections \n  \nDepartment of \ncustom services  \nAutomated \nsystem for \ncustoms data \ndatabase \n \na print from the \ncustoms IT system \n(automated system \nfor customs data) to \nverify the number \nof entries by those \ncompanies and \nwhat, if any, \nexaminations \noccurred.  \nAB will confirm the \ncounting and \nperform random \nchecks as needed \nand issue its report \nwithin 2 months \nfollowing PMU \nnotification.  \nMOPIC will submit \nrelated \ndocumentation \nconfirming \nachievement of \nresults along with \nthe AB report. \nDLI 5 \nNumber of \ninvestments \nbenefitting \nfrom \ninvestment \nfacilitation by \nthe JIC  \nDLR 5.1: Removing the minimum capital \nrequirements for foreign investments (Prior \nResult) \nDLR 5.2: Number of investments benefiting \nfrom investment facilitation by JIC = 530 \n(cumulative).  \n \nThis includes the following:  \n(a) Basic communication/investor inquiries \n(b) Site visits facilitated \n(c) Secured investment commitment \nYes \nThe JIC’s CRM \ndatabase \nAB \nAt the end of each \nCY, the JIC will \nprovide to the PMU \nits CRM database. \nAB will review and \nconfirm the \ncounting and \nperform random \nchecks of the \nfacilitated \ninvestments as \nneeded. The AB", "source": "refugee_pads", "subset": "annotate_aivin_part2", "spans": [{"key": "refugee_pads:000137:51:0:0", "start": 1120, "end": 1139, "surface": "JIC’s CRM \ndatabase", "probe_tag": "confusion", "probe_score": 0.5222, "luna_label": 0, "luna_reason": "Future submission and verification of the CRM database are planned monitoring procedures."}]}, {"key": "aivin2-123", "text": "reaching out to the poor_**\n\n\n**235.** Reaching the ultra-poor is a challenge: they are often widely dispersed in small settlements, have\nno means of communication with authorities and lack basic skills (i-e., literacy, numeracy, etc.) and\nresources. Multi-pronged methods such as surveys, community consultations, CSO contacts, SWF staff\nknowledge, knowledge of other program staff, etc., must be utilized to identify them. The SWF process of\nbeneficiary selection and enrollment is carried out in the following steps:\n\n\n_Identification_     - Obtain a list of potential beneficiaries developed from community sources as well\nas from new applicant lists. Community committees/leaders can help to identify and inform\nhouseholds that they can apply to the CT program. Community leaders or social workers at the\ntime of application inform households concerning the program rights, obligations and rules via an\norientation meeting.\n_Registration_     - Register and collect survey datdinformation on potential beneficiaries.\nRegistration can also be open to people from the community not previously identified, but still\ndeemed to be poor.\n_Selection_     - The selection of potential beneficiaries is made using a proxy means testing approach\nbased on the information collected from each household registered for the program. The PMT\nformula is designed to capture one dimension of the economic status of the household, Le., the\neconomic welfare of the household. The PMT represents the “predicted (potential) household per\ncapita expenditure” according to household characteristics. The final list of selected applicants\ncan be verified by the community or by community leaders during consultations.\n_Enrollment_    - beneficiaries are enrolled in the program (after selection of potential beneficiaries\n\nbased on the previous steps) to receive a certain amount of cash. As part of the enrolment process,\nfamilies receive information about the entitlements of the Program and payment method, and are\nprovided with identity cards.\n\n\n**73**", "source": "refugee_pads", "subset": "annotate_aivin_part2", "spans": [{"key": "refugee_pads:000080:78:1:1", "start": 971, "end": 993, "surface": "survey datdinformation", "probe_tag": "confusion", "probe_score": 0.6181, "luna_label": 0, "luna_reason": "Survey data are being collected during beneficiary registration."}]}, {"key": "aivin2-124", "text": "**Annex II: Detailed Project Description**\n\n\n**LEBANON**\n**Emergency National Poverty Targeting Program Project (P149242)**\n\n\n**Project Components**\n\n\n1. The Emergency NPTP project consists of two technical components and a fiduciary\noperations component. Specifically, the components are: (i) administration of the NPTP, (ii)\nprovision of Social Assistance, and (iii) fiduciary Operations.\n\n\n**_Component 1: Administration of the National Poverty Targeting Program (US$11.19 million_**\n**_total cost, of which US$3.89 million financed from TFL, and US$6.9 million from the GOL)_** <sup>**_29_**</sup> [^29: There is a financing gap of US$390,107 million for this component.]\n\n\n2. This component’s objective is to ensure an effective and efficient administration and\nimplementation of the NPTP through its structures in the MOSA and the PCM, so that it can\nexpand the coverage and enhance the social assistance to extremely poor Lebanese households\nand those affected by the Syrian crisis. This component will also improve the efficiency of the\nNPTP. To achieve its objective, this component will finance technical assistance for the\nfollowing activities:\n\n\n(a) Supporting the program management team in the MOSA and the PCM;\n(b) Recertification of applicants in 2015 including refining the program application\nforms and PMT questionnaire;\n(c) Upgrading the NPTP Management Information System (MIS);\n(d) Refining the grievance and redress mechanism for improved efficiency and\ntransparency;\n(e) Monitoring and evaluation of the program, including evaluating the business\nprocesses of the NPTP, and implementation of short quantitative and qualitative\nsurveys (beneficiary assessments, opinion polls on awareness, etc.);\n(f) Carrying out an outreach campaign to enroll new beneficiaries particularly in the\npoorer and remote areas;\n(g) Providing training to Beneficiaries in the use of Food", "source": "refugee_pads", "subset": "annotate_aivin_part2", "spans": [{"key": "refugee_pads:000139:35:0:0", "start": 1660, "end": 1683, "surface": "beneficiary assessments", "probe_tag": "confusion", "probe_score": 0.6411, "luna_label": 0, "luna_reason": "Planned assessments are listed among future project monitoring activities."}, {"key": "refugee_pads:000139:35:0:1", "start": 1685, "end": 1711, "surface": "opinion polls on awareness", "probe_tag": "confusion", "probe_score": 0.0912, "luna_label": 0, "luna_reason": "Opinion polls are planned for implementation as project monitoring activities."}]}, {"key": "aivin2-125", "text": "**The World Bank**\nEducation Infrastructure for Resilience (EU Facility for SuTP) (P162004)\n\n\n**VII. RESULTS FRAMEWORK AND MONITORING**\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Indicator Name|Core|Unit of<br>Measure|Baseline|End Target|Frequency|Data Source/Methodology|Responsibility for<br>Data Collection|\n|---|---|---|---|---|---|---|---|\n|**Name:**Number of direct<br>beneficiaries provided with<br>access to disaster resilent,<br>informal education facilities<br>(to be disaggregated by<br>gender)||Number|0.00|360.00|Annual<br>|PPRs, PIU data from<br>Ministry, MONE Strategic<br>Plan<br>|PIU<br>|\n|Description:This indicator measures the number of students/trainees registered in the newly built informal education facility up to the expected capacity. Indicator will<br>be disaggregated by gender and country of origin.|Description:This indicator measures the number of students/trainees registered in the newly built informal education facility up to the expected capacity. Indicator will<br>be disaggregated by gender and country of origin.|Description:This indicator measures the number of students/trainees registered in the newly built informal education facility up to the expected capacity. Indicator will<br>be disaggregated by gender and country of origin.|Description:This indicator measures the number of students/trainees registered in the newly built informal education facility up to the expected capacity. Indicator will<br>be disaggregated by gender and country of origin.|Description:This indicator measures the number of students/trainees registered in the newly built informal education", "source": "refugee_pads", "subset": "annotate_aivin_part2", "spans": [{"key": "refugee_pads:000160:36:0:0", "start": 521, "end": 529, "surface": "PIU data", "probe_tag": "confusion", "probe_score": 0.3329, "luna_label": 0, "luna_reason": "Fragmentary table data-source entry, not an independently used data resource."}]}, {"key": "aivin2-126", "text": "**The World Bank**\nAgricultural Employment Support for Refugees and Turkish Citizens through Enhanced Market Linkages (P171543)\n\n\nto the person who lodged the complaint. Complaints received through the GRM will be registered and\ntracked in the management information system.\n\n\n54. This subcomponent will finance national- and local-level communications and visibility activities,\nincluding making the contributions of the EU and the World Bank visible in the branded products (contract\nfarming supported under this action). This activity will be informed by a communication and visibility plan.\n\n\n55. **Subcomponent 3.3: Monitoring and evaluation** (US$4.45 million equivalent). Given the\ninnovative nature of this project, M&E will be given special emphasis as follows to inform implementation\nand modifications to design parameters during project implementation:\n\n\n(a) **Management information systems** : Enhancement and implementation of an information\n\nand monitoring system to allow the ACC to track contract farming and related outputs, by\nfurther developing the IT system based on the relevant processes and set of indicators, as\nwell as collection of basic administrative data. As part of this system, the project will support\nthe development and implementation of the registry of certified skilled workers and the\nvacancies database, as well as the data collection related to them to ensure that the\ninformation they provide is updated. As part of this set of activities, the proposed project\nwill also support the ACC in the following areas: (i) IT development (software and hardware)\nto create, administer, and maintain a regularly updated registry of workers who have been\ntrained and certified and (ii) IT development (software and hardware) to improve the system\nto maintain an updated list of vacancies.\n\n\n(b) **Reports and evaluations:** This subcomponent will support the preparation of a series of\n\nactivity-level reporting, process assessments, and independent evaluations. Specifically, the\nproposed project will support the following:\n\n\ni. Process evaluations to", "source": "refugee_pads", "subset": "annotate_aivin_part2", "spans": [{"key": "refugee_pads:000114:26:0:1", "start": 1324, "end": 1342, "surface": "vacancies database", "probe_tag": "confusion", "probe_score": 0.2174, "luna_label": 0, "luna_reason": "Project will develop the vacancies database, so the data resource is not yet existing."}]}, {"key": "aivin2-127", "text": "**S R I LANKA: PUTTALAM HOUSING PROJECT**\n\n**Annex** **12:** **Documents in the Project File**\n\n\nUNHCR supervised Survey o f Refugee Camps in Puttalam - 2004\nUNHCR supervised Survey o f Refugee Camps in Puttalam - 2006\nNational Survey o f IDPs - 2003\n\nSocial Profiles for 11 1 Refugee Camps43\nEnvironment Profiles for 11 1 Refugee Camps\nEnvironmental and Social Management Framework.\nHousing Assessment Survey\nProject Concept Note\nMinutes o f the Quality Enhancement Review Meeting\nIntegrated Safeguards Data Sheet\nAction Plan for Future Investment in Puttalam District\n\n\n43 The Social and Environmental profile for the remaining 30 refbgee camps will be prepared in early 2007 to\ncomplete these assessments for 141 camps.\n\n\n_69_", "source": "refugee_pads", "subset": "annotate_aivin_part2", "spans": [{"key": "refugee_pads:000023:74:0:0", "start": 97, "end": 150, "surface": "UNHCR supervised Survey o f Refugee Camps in Puttalam", "probe_tag": "confusion", "probe_score": 0.8247, "luna_label": 1, "luna_reason": "Named UNHCR-supervised survey cited among project documents."}, {"key": "refugee_pads:000023:74:0:1", "start": 219, "end": 243, "surface": "National Survey o f IDPs", "probe_tag": "confusion", "probe_score": 0.7415, "luna_label": 1, "luna_reason": "Named existing national survey listed among project documents."}, {"key": "refugee_pads:000023:74:0:2", "start": 384, "end": 409, "surface": "Housing Assessment Survey", "probe_tag": "confusion", "probe_score": 0.6428, "luna_label": 0, "luna_reason": "Listed as a project-file document without evidence of data use or findings."}]}, {"key": "aivin2-128", "text": " The sustainability of the sanitation measures will be carefully assessed from the point of view\nof good practices, cost effectiveness, affordability and the Djibouti water shortage environment.\n\n\n6. **Social**\n\n\n_6.1 Summarize key social issues relevant to the project objectives, and specify the project's social_\n_development outcomes._\n\n\nDjibouti is a small country and many key social issues were identified in the 1997 Poverty\n\nAssessment. The issues raised included the percentage of the population classified as poor in 1996\n(50-80% reaching the upper-bound when refugees, nomads and homeless are taken into account); large\nnumbers of refugees, nomads, and homeless populations; the majority of the poor live in urban areas\n(85%) even if the incidence of extreme poverty is overwhelmingly rural. Urban households can take\nadvantage of safety nets derived from the commodity market and services, and job opportunities are\nnot available in rural areas. The key problems faced by children include: (a) the high number of street\nchildren who have fled war ravaged Somalia and Ethiopia; (b) late entrance into school by poorer\nchildren (one out of four starts school at age 9 and leaves school at age 14); (c) health issues (diarrhea\n\nand malnutrition) are a leading cause of death for children under age 5. Other problems affecting the\nwhole population include respiratory infections on the increase (due to malnutrition); endemic health\nproblems (AIDS, tuberculosis, malaria, cholera); the widespread practice of Female Genital Mutilation\n(FGM); sanitation costs are high for poorer households not connected on the main water network as", "source": "refugee_pads", "subset": "annotate_aivin_part2", "spans": [{"key": "refugee_pads:000100:23:1:0", "start": 420, "end": 444, "surface": "1997 Poverty\n\nAssessment", "probe_tag": "confusion", "probe_score": 0.8166, "luna_label": 1, "luna_reason": "Named poverty assessment cited as evidence for multiple social findings."}]}, {"key": "aivin2-129", "text": "Annex 10\nPage 2 of 2\nDJIBOUTI: School Access and Improvement Program\n\n\nCountry at a Glance\n\n\n_Djibouti_\n\n\n**PRICES and GOVERNMENT FINANCE**\n\n**1979** **1989** **1998** **1999** **Inflation (%)**\n**_Domestic prices_**\n_(% change)_\nConsumer prices .\nImplicit GDP deflator 3.0 **_4_**\n\n**_Government_** _finance_ **2**\n_(% of GDP, includes current grants)_ -,\nCurrent revenue **.4** **95** **Os** **97** 98 99\nCurrent budget balance - GDP deflator e CPI\nOverall surplus/deficit\n\n\n\n**TRADE**\n\n\n\n**1979** **1989** **1998** **1999**\n_(US$ millions)_\nTotal exports (fob)\n\n\n\nn.a.\nn.a.\nManufactures\nTotal imports (cif ..\nFood\nFuel and energy\nCapital goods\n\n\n\nExport price index _(1995=100)_ _._\nImport price index _(1995=100)_\nTerms of trade (1995=100) .\n\n\n**BALANCE of PAYMENTS**\n\n_(US$ rrillions)_ **1979** **1989** **1998** **1999** **Current account balance to GDP ratio (%)**\n\n\n\nExports of goods and services .\nImports of goods and services\nResource balance .. .. **4**\n\n\n\nNet income\nNet current transfers\n##### 1.8 11\n\n\n\nCurrent account balance . **.2**\n\n\n\nFinancing items (net)\nChanges in net reserves .. .\n_Memo:_\nReserves including gold _(US$ millions)_\nConversion rate _(DEC, loca", "source": "refugee_pads", "subset": "annotate_aivin_part2", "spans": [{"key": "refugee_pads:000022:63:0:0", "start": 686, "end": 704, "surface": "Import price index", "probe_tag": "confusion", "probe_score": 0.2994, "luna_label": 0, "luna_reason": "Standalone table indicator label without cited data use"}]}, {"key": "aivin2-130", "text": "**The World Bank**\nSocio-economic Inclusion of Refugees & Host Communities\nin Rwanda Project Phase II (P509677)\n\n|Proportion of beneficiaries indicating satisfaction with infrastructure subprojects constructed or upgraded by the project<br>(Percentage)|Col2|\n|---|---|\n|Description|Quantitative indicator counting proportion of beneficiaries indicating satisfaction with infrastructure<br>subprojects constructed or upgraded by the project. Indictor is a composite of beneficiaries responding<br>“satisfied” or “very satisfied” on a Likert scale.|\n|Frequency|Annual.|\n|Data source|Annual survey.|\n|Methodology for Data<br>Collection|Survey.|\n|Responsibility for Data<br>Collection|MINEMA.|\n|**Kilometers of road upgraded (Kilometers)**|**Kilometers of road upgraded (Kilometers)**|\n|Description|Quantitative indicator counting kilometers of roads upgraded (completed).|\n|Frequency|Quarterly|\n|Data source|Project MIS and Project Progress Reports.|\n|Methodology for Data<br>Collection|Monitoring project implementation. RTDA data fed to MINEMA.|\n|Responsibility for Data<br>Collection|RTDA and MINEMA.|\n|**Market facilities and Integrated Craft Production Centers constructed or upgraded (Number)**|**Market facilities and Integrated Craft Production Centers constructed or upgraded (Number)**|\n|Description|Quantitative indicator counting number of market facilities and ICPCs constructed or upgraded<br>(completed).|\n|Frequency|Quarterly|\n|Data source|Project MIS and Project Progress Reports.|\n|Methodology for Data<br>Collection|Monitoring project implementation.|\n|Responsibility for Data<br>Collection|MINEMA.|\n|**Economic", "source": "refugee_pads", "subset": "annotate_aivin_part2", "spans": [{"key": "refugee_pads:000188:46:0:1", "start": 905, "end": 945, "surface": "Project MIS and Project Progress Reports", "probe_tag": "confusion", "probe_score": 0.2868, "luna_label": 0, "luna_reason": "Project monitoring reports are routine implementation bookkeeping, not substantive evidence."}, {"key": "refugee_pads:000188:46:0:2", "start": 1019, "end": 1028, "surface": "RTDA data", "probe_tag": "confusion", "probe_score": 0.59, "luna_label": 0, "luna_reason": "Project monitoring data supporting routine implementation tracking, not substantive evidence."}]}, {"key": "aivin2-131", "text": "**The World Bank**\nDjibouti Health System Strengthening (P178033)\n\n\n**Figure 4: Main health problem, last 30 days**\nChildren under 5 Children under 1\n\n\n_Source: World Bank visualization based on the 2017-2018 EDAM survey_\n\n18. **Poor nutrition outcomes for children are pervasive across the country and are often linked to incidence**\n**of diarrheal diseases in childhood and increased risk of non-communicable diseases (NCDs) in adulthood.**\nUndernutrition accounts for 57 percent of deaths among children under five; it is widespread, with 17 percent\nunderweight and 25 percent stunted with no gender differentials. The stunting rate is higher among rural (34\npercent) than urban children (19 percent). Some lagging regions experience higher burden of stunting: 40.2, 33.3,\nand 32.6 percent in Obock, Dikhil and Tadjourah, respectively. At the same time, deaths due to NCDs such as\nischemic heart disease, stroke, cirrhosis, and diabetes have increased significantly between 2009 and 2019.\nObesity <sup>11</sup> [^11: A body mass index (BMI) over 25 is considered overweight, and over 30 is obese.] rates are also on the rise – 18.3 percent for women, 8.6 percent for men, and about 5 percent for\nchildren. The poor adult health outcomes, including a high burden of NCDs, are in part driven by nutrition and\nhealth deficiencies accumulated in early childhood <sup>12</sup> [^12: IHME, 2021, _[https://www.healthdata.org/djibouti](https://www.healthdata.org/djibouti)_] . Human immunodeficiency virus/acquired immunodeficiency\nsyndrome (HIV/AIDS) also remains a key cause of mortality, which makes the double burden of disease prevalent\nin Djibouti, a key challenge for improved health outcomes through the lifecycle.\n\n19. **Despite national efforts, harmful gender norms increase the", "source": "refugee_pads", "subset": "annotate_aivin_part2", "spans": [{"key": "refugee_pads:000131:19:0:0", "start": 209, "end": 221, "surface": "EDAM survey_", "probe_tag": "confusion", "probe_score": 0.8835, "luna_label": 1, "luna_reason": "Named EDAM survey cited as the basis for the World Bank visualization."}]}, {"key": "aivin2-132", "text": "Uganda-Refugee-and-Host-Communities-2018-Household-Survey)\n[47 https://data2.unhcr.org/en/documents/details/64290](https://data2.unhcr.org/en/documents/details/64290)\n\n\nPage 19 of 80", "source": "refugee_pads", "subset": "annotate_aivin_part2", "spans": [{"key": "refugee_pads:000146:23:3:0", "start": 0, "end": 57, "surface": "Uganda-Refugee-and-Host-Communities-2018-Household-Survey", "probe_tag": "confusion", "probe_score": 0.8527, "luna_label": 1, "luna_reason": "Named existing household survey cited as an external data resource."}]}, {"key": "aivin2-133", "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": "refugee_pads", "subset": "annotate_aivin_part2", "spans": [{"key": "sample:refugee_pads:000093:38:1:0", "start": 565, "end": 598, "surface": "household expenditure survey data", "probe_tag": "confusion", "probe_score": 0.7323, "luna_label": 1, "luna_reason": null}, {"key": "sample:refugee_pads:000093:38:1:1", "start": 870, "end": 881, "surface": "survey data", "probe_tag": "confusion", "probe_score": 0.1461, "luna_label": 1, "luna_reason": null}, {"key": "sample:refugee_pads:000093:38:1:2", "start": 1978, "end": 2008, "surface": "data from the Household Survey", "probe_tag": "confusion", "probe_score": 0.1121, "luna_label": 1, "luna_reason": null}]}, {"key": "aivin2-134", "text": " to the returnees and providing information on return processes, the project\nwill facilitate the returnees to access social services and economic opportunities that alleviate their vulnerability\nto shocks. The labor intensive public works, investments in market infrastructure, and regulatory reforms to\npromote economic opportunities are expected to create more jobs and provide for more stable income\ngeneration activities in the target cities, mitigating economic shocks of climate change. Improved connectivity to\nmarkets (access roads) and market infrastructure (e.g. electrification, storage, drainage, sanitation) are also\n\n\n46 Germanwatch (2018). Global Climate Risk Index.\n47 Maplecroft (2011). Climate Change Risk Atlas.\n48 World Bank Group (2016). Shock Waves, Managing the Impacts of Climate Change on Poverty.\n49 <u>https://www.gfdrr.org/sites/default/files/afghanistan_low_FINAL.pdf</u>\n50 _www.disasterrisk.af_\n\n\nPage 84 of 85", "source": "refugee_pads", "subset": "annotate_aivin_part2", "spans": [{"key": "refugee_pads:000123:90:2:0", "start": 655, "end": 680, "surface": "Global Climate Risk Index", "probe_tag": "confusion", "probe_score": 0.7882, "luna_label": 0, "luna_reason": "Standalone numbered bibliography entry, not data use in the passage."}]}, {"key": "aivin2-135", "text": " more efficient and transparent way by continuing training and campaigns\nto raise awareness. This would help raise subscriptions, avoid illegal connections, improve collection\nof fees/tariffs, and encourage good practices such as metering and rationalizing water consumption\nuse.Given the critical role that collection plays; BWE has prepared a new proposal to its Board to\nrevisit the issue of how to reinforce the collection effort. The **new proposal** focuses on: undertaking a\nnew customer survey, outreach to political and municipal authorities that interact directly with people\nexplaining the necessity to pay for water consumed, payment modalities and legal implications and\n\n\n32", "source": "refugee_pads", "subset": "annotate_aivin_part2", "spans": [{"key": "refugee_pads:000036:40:2:0", "start": 486, "end": 501, "surface": "customer survey", "probe_tag": "confusion", "probe_score": 0.6102, "luna_label": 0, "luna_reason": "Proposed new survey is future data collection, not existing data use."}]}, {"key": "aivin2-136", "text": "terms of nutrition as any deficiencies not resolved by the end of this period is very likely to be\nirreversible. To also encourage older children to receive adequate nutrition and benefit from\nroutine health check-ups, the targeting range includes all households with children under the age\nof 12 years old including pregnant women. In rural Chad, almost all poor households have\nchildren under the age of 12 years old.\n\n\n17. **The program will reach an estimated 6,200 poor households, in both the southern**\n**Sudanian and Sahel regions.** The analytical work preceding the preparation of the project\nindicates that chronic poverty and vulnerability is present in the southern Sudanian region. For\nexample, comparisons between 2003 and 2011 household surveys (ECOSIT 2 and 3) the food\npoverty rate increased substantially in the three southern regions (Guera and Salamat from 35\npercent to 42 percent and Logone Occidental from 38.6 percent to 46.4 percent). However, the\nsouthern Sudanian region has few existing SP programs and interventions by donor partners are\nvery limited, while the Government has virtually no assistance programs. In the Sahel area, there\nis a noticeable presence of development partners, responding to cyclical food insecurity.\nHowever, many of these programs are in need of further harmonization and of a shared platform\non which to build common databases to register potential and current beneficiaries, coordinate on\ntargeting or enrollment into social assistance programs, and then monitor the implementation and\neffectiveness of these programs. In the Sahel, this subcomponent would pilot project approaches\nthat can support such harmonization and the building of a common platform. For the purpose of\nthe pilot under this component, the following two regions have been retained: BEG in the Sahel\narea, and Logone Occidental in the Sudanian region. Besides being affected by deep poverty\n(households in food poverty represents 23 percent in BEG and 38 percent Logone Occidental),\nboth present the abovementioned challenges of limited donor", "source": "refugee_pads", "subset": "annotate_aivin_part2", "spans": [{"key": "refugee_pads:000028:41:0:0", "start": 743, "end": 760, "surface": "household surveys", "probe_tag": "confusion", "probe_score": 0.8287, "luna_label": 1, "luna_reason": "Existing 2003 and 2011 surveys support reported food-poverty comparisons."}, {"key": "refugee_pads:000028:41:0:1", "start": 762, "end": 770, "surface": "ECOSIT 2", "probe_tag": "confusion", "probe_score": 0.7937, "luna_label": 1, "luna_reason": "Named household survey used in comparisons supporting regional food-poverty findings."}]}, {"key": "aivin2-137", "text": " biometric data\ncollected by RRS through the UNHCR ProGres system for Fayda registration. NIDP will also develop registration strategies\nfor individuals who require to be ‘introduced’ by a witness in the absence of supporting documentation (for example, due\nto delay in issuance of refugee cards). <mark>Fayda will not substitute existing documents issued to refugees (refugee ID card,</mark>\n<mark>proof of registration, a</mark> nd so o <mark>n) but will be used as a complementary form of identification.</mark>\n\n\n35 Floodlist 2023. Ethiopia-Flooding Continues in Several Regions, Displacing Thousands and Threatening Food Security.\nhtps://floodlist.com/africa/ethiopia-floods-may-2023\n36 Governments must respond quickly to climate or other shocks and provide emergency assistance. When Pakistan was hit by floods in 2010, it used\nthe foundational ID to facilitate emergency cash grants: beneficiaries used their cards to make a quick application at centers across the country, and\ntheir address was validated (to check whether they lived in the affected areas). Over 2.7 million people applied, but 1.1 million were deemed\nineligible, saving up to US$248 million. Having such reliable systems enables a country to respond at speed and with transparency.\n37 The process will require thousands of registration kits.\n38 Numbers of refugees in Tigray require confirmation as RRS is currently in the process of re-engaging in the region following the recent conflict.\n39 The target for refugees tackles almost the whole population of registered refugees in Ethiopia as of October 2023. However, this number might change\ndue to continuing inflows and outflows of refugees. The same is valid for the target seizure of the host community, which is until now an estimate\nprovided by UNHCR, for _woredas_ with a great number of host communities. It should be", "source": "refugee_pads", "subset": "annotate_aivin_part2", "spans": [{"key": "refugee_pads:000005:23:2:0", "start": 1, "end": 15, "surface": "biometric data", "probe_tag": "confusion", "probe_score": 0.5521, "luna_label": 0, "luna_reason": "Data are collected for Fayda registration rather than reused as existing evidence."}]}, {"key": "aivin2-138", "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_aivin_part2", "spans": [{"key": "refugee_pads:000090:16:0:0", "start": 379, "end": 395, "surface": "statistical data", "probe_tag": "drop", "probe_score": 0.0402, "luna_label": 0, "luna_reason": "Planning unit generates the data; it is project-produced rather than existing data used."}]}, {"key": "aivin2-139", "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": "refugee_pads", "subset": "annotate_aivin_part2", "spans": [{"key": "refugee_pads:000165:31:0:0", "start": 226, "end": 240, "surface": "NaCSA M&E data", "probe_tag": "drop", "probe_score": 0.0279, "luna_label": 0, "luna_reason": "Names monitoring data without showing its figures informing analysis or decisions."}, {"key": "refugee_pads:000165:31:0:1", "start": 412, "end": 437, "surface": "NaCSA administrative data", "probe_tag": "confusion", "probe_score": 0.1197, "luna_label": 1, "luna_reason": "Named administrative data source listed for verifying program indicators."}]}, {"key": "aivin2-140", "text": ">implementation.|<br> <br> <br>Semi-<br>annually<br>|P-MIS,<br>progress<br>reports<br>|Data on indicator will<br>be collected from<br>subproject proposals.<br>|MINEMA SPIU, Districts<br>|\n|Beneficiaries participating in project<br>planning activities|This indicator will track the<br>number of people<br>participating in project<br>planning activities.|Semi-<br>annually<br>|P-MIS,<br>progress<br>reports<br>|Data on indicator will<br>be collected from<br>attendance sheets and<br>consultation reports.<br>|MINEMA SPIU, Districts<br>|\n\n\n\nPage 41 of 82", "source": "refugee_pads", "subset": "annotate_aivin_part2", "spans": [{"key": "refugee_pads:000030:45:1:0", "start": 456, "end": 473, "surface": "attendance sheets", "probe_tag": "drop", "probe_score": 0.042, "luna_label": 0, "luna_reason": "Attendance sheets are routine project bookkeeping records, not substantive data evidence."}]}, {"key": "aivin2-141", "text": " <br>Bank). It is expected that these reforms could be directly and immediately extended to the universal goods subsidy programs so as to <br>ensure their long-term fiscal sustainability.<br>|**Risk Management:** To avoid burdening the existing institutional and financial structure of the existing systems, the project is designed <br>to support only a temporary increase in health and subsidy related expenditures due to Syrian refugees and prevent any disruption of <br>availability of basic goods and services for Jordanian citizens. For component 1, the MOH is running a deficit equivalent of 40% of its <br>annual budget even prior to the refugee crisis. The aim of this program is not to increase the debt of the MOH but rather for the program <br>to open channels for more policy dialogue with the GOJ on health sector reforms and structural changes needed to deal with the larger<br>MOH debt. For component 2, the temporary financing enables the Government to have sufficient time to develop and implement more <br>efficient social safety net programs through, for example, the targeting of the current subsidy programs. Reforms of such critical but <br>imperfect social safety net programs need to be carefully designed. A reform of an existing cash compensation program is underway <br>through the development of a unified registry and the development of proxy means testing (with technical assistance from the World <br>Bank). It is expected that these reforms could be directly and immediately extended to the universal goods subsidy programs so as to <br>ensure their long-term fiscal sustainability.<br>|**Risk Management:** To avoid burdening the existing institutional and financial structure of the existing systems, the project is designed <br>to support only a temporary increase in health and subsidy related expenditures due to Syrian refugees and prevent any disruption of <br>availability of basic goods and services for Jordanian", "source": "refugee_pads", "subset": "annotate_aivin_part2", "spans": [{"key": "refugee_pads:000064:59:8:0", "start": 1326, "end": 1342, "surface": "unified registry", "probe_tag": "drop", "probe_score": 0.0322, "luna_label": 0, "luna_reason": "Registry is being developed as part of the reform, not used as existing data."}]}, {"key": "aivin2-142", "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_aivin_part2", "spans": [{"key": "sample:refugee_pads:000097:16:0:0", "start": 379, "end": 395, "surface": "statistical data", "probe_tag": "confusion", "probe_score": 0.582, "luna_label": 0, "luna_reason": null}, {"key": "sample:refugee_pads:000097:16:0:1", "start": 1487, "end": 1500, "surface": "random survey", "probe_tag": "drop", "probe_score": 0.012, "luna_label": 0, "luna_reason": null}]}, {"key": "aivin2-143", "text": "**Annex 15: Map IBRD 33512**\n\n**WEST BANK AND GAZA:**\n**Teacher Education Improvement Project**\n\n\n79", "source": "refugee_pads", "subset": "annotate_aivin_part2", "spans": [{"key": "refugee_pads:000171:86:0:0", "start": 12, "end": 26, "surface": "Map IBRD 33512", "probe_tag": "drop", "probe_score": 0.0065, "luna_label": 0, "luna_reason": "Standalone map reference, with no shown data use or analysis."}]}, {"key": "aivin2-144", "text": " health personnel and total number of children immunized. <br>|\n|Frequency <br>|Every six months <br>|\n|Data source <br>|KHIS|\n|Methodology for Data<br>Collection|Routine HMIS data collection|\n|Responsibility for Data<br>Collection <br>|MoH <br>|\n|**Number of children immunized (Number)CRI** <br> <br>|**Number of children immunized (Number)CRI** <br> <br>|\n|Description <br>|Total number of children immunized. <br>|\n|Frequency <br>|Every six months <br>|\n|Data source|KHIS|\n|Methodology for Data<br>Collection|Routine HMIS data collection|\n|Responsibility for Data<br>Collection <br>|MoH <br>|\n|<br>**Number of deliveries attended by skilled health personnel (Number)CRI**|<br>**Number of deliveries attended by skilled health personnel (Number)CRI**|\n\n\n\nFeb 21, 2024 Page 33 of 43", "source": "refugee_pads", "subset": "annotate_aivin_part2", "spans": [{"key": "refugee_pads:000000:38:2:0", "start": 471, "end": 475, "surface": "KHIS", "probe_tag": "drop", "probe_score": 0.0109, "luna_label": 0, "luna_reason": "KHIS is named as a data source without showing its data being used."}]}, {"key": "aivin2-145", "text": "**The World Bank**\nGenerating Growth Opportunities and Productivity for Women Enterprises Uganda Project (P176747)\n\n\n**B. Results Monitoring and Evaluation Arrangements**\n\n\n**Monitoring and Regular Reporting**\n\n79. **Objectives and design** . The objective of the M&E system is to track the project’s implementation progress and\nachievement of expected outcomes to enable the government (national and sub-national) and World Bank to address\nissues as they arise. An integrated web-based data collection platform will be established at the MGLSD into which data\non implementation progress and outcomes will be entered will be entered to track implementation of project\ninterventions and their outcomes. The MGLSD will contract a consulting firm to design and develop the integrated data\nplatform, which will include an interface that allows the persons responsible for M&E at all implementing agencies to\nenter monitoring data that they collect.\n\n80. **The MGLSD will lead the overall M&E efforts.** The MGLSD already has an experienced Planning Unit which has\nbeen responsible for leading the efforts to track government programs. Staff with specialized skills in (a) survey design,\nimplementation, and analysis; (b) operations and maintenance of management information systems; and (c) data\nmanager; and (d) others as needed will comprise the M&E team at the MGLSD.\n\n81. **M&E teams will be established as members of the PITs at both the national.** They will be responsible for collecting\nand sharing information presented in the results framework in accordance with the procedures laid out in the M&E\nmonitoring plan, and entering the data into the integrated data platform. Data from each implementing agency will be\naggregated with the data of others and used as the basis of quarterly progress reports.\n\n82. **Data generation and reporting** . The data to track the key performance indicators come from (", "source": "refugee_pads", "subset": "annotate_aivin_part2", "spans": [{"key": "sample:refugee_pads:000088:36:0:0", "start": 910, "end": 925, "surface": "monitoring data", "probe_tag": "drop", "probe_score": 0.0303, "luna_label": 0, "luna_reason": null}, {"key": "sample:refugee_pads:000088:36:0:1", "start": 1678, "end": 1712, "surface": "Data from each implementing agency", "probe_tag": "confusion", "probe_score": 0.1516, "luna_label": 0, "luna_reason": null}]}, {"key": "aivin2-146", "text": "**The World Bank**\nSouthern Niger Connectivity and Integration Project (P179770)\n\n\ninformed prioritization, as well as NMT, road safety, and climate-resilient design considerations under Subcomponent 1.1,\nwill also apply under this subcomponent.\n\n- **Subcomponent 1.3:** **Climate-resilient road asset management strengthening** **and reform operationalization** _(US$17.0_\n_million; US$10.0 million IDA credit and US$7.0 million counterpart funding)._ This subcomponent will primarily support\nimproving governance and institutional mandates for climate-resilient road asset management. The component takes a\ntwo-pronged approach by financing the following: (a) a technical assistance to maximize the effectiveness of the 2019\nroad sector reforms and institutional strengthening for road maintenance; and (b) designing and implementing a multiyear contract for periodic and routine road maintenance for a road section to be determined during implementation that\nmeets certain eligibility criteria. The technical assistance aims to facilitate the transition to medium-term planning and\nmulti-year contracting for routine and periodic road maintenance in Niger, in alignment with the GoN priorities identified\nthrough the 2025 GoN’s sectorial policy letter. Key activities to be carried out include: (i) providing technical guidance for\nthe modernization of the road database; (ii) incorporating climate risks in maintenance programming; (iii) conducting a\nstudy to diversify sources of maintenance financing and digitize toll facilities to optimize revenues from tolling,\nincluding investments in more modernized toll facilities; (iv) developing multi-year maintenance contract models; and (v)\nbuilding the capacity of DGSR, AMODER and CACER to improve road asset management through key performance\nindicators monitoring. This comprehensive approach aims to develop a sustainable and efficient climate-resilient road\nmaintenance system in Niger. Regarding the multi", "source": "refugee_pads", "subset": "annotate_aivin_part2", "spans": [{"key": "refugee_pads:000184:22:0:0", "start": 1360, "end": 1373, "surface": "road database", "probe_tag": "drop", "probe_score": 0.0231, "luna_label": 0, "luna_reason": "Planned modernization activity, not demonstrated use of existing database data"}]}, {"key": "aivin2-147", "text": "s (Amount [US$]) **|\n|Description <br>Value of investments disbursed by the project to MSMEs for implementing climate resilience standards and/or best<br>practices.|Description <br>Value of investments disbursed by the project to MSMEs for implementing climate resilience standards and/or best<br>practices.|\n|Frequency<br>Semi-annually|Frequency<br>Semi-annually|\n|Data Source<br>Implementation partners|Data Source<br>Implementation partners|\n|Methodology for Data<br>Collection <br>Project disbursment records|Methodology for Data<br>Collection <br>Project disbursment records|\n|Responsibility for Data<br>Collection|Implementation partners, PIU|\n\n\n\n**Monitoring & Evaluation Plan: Intermediate Results Indicators by Components**\n\n|MSME access to markets and value chain development|Col2|\n|---|---|\n|**Annual exports increase of supported MSMEs (Percentage) **|**Annual exports increase of supported MSMEs (Percentage) **|\n|Description<br>Percent change in the number of supported MSMEs that exported their products or services.|Description<br>Percent change in the number of supported MSMEs that exported their products or services.|\n|Frequency<br>Annually|Frequency<br>Annually|\n|Data Source<br>Project partners|Data Source<br>Project partners|\n|Methodology for Data<br>Collection <br>Baseline, annual, and endline data are collected from supported MSMEs|Methodology for Data<br>Collection <br>Baseline, annual, and endline data are collected from supported MSMEs|\n|Responsibility for Data<br>Collection <br>P", "source": "refugee_pads", "subset": "annotate_aivin_part2", "spans": [{"key": "refugee_pads:000004:39:3:0", "start": 485, "end": 512, "surface": "Project disbursment records", "probe_tag": "drop", "probe_score": 0.0404, "luna_label": 0, "luna_reason": "Routine project disbursement records used for monitoring paperwork"}]}, {"key": "aivin2-148", "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": "refugee_pads", "subset": "annotate_aivin_part2", "spans": [{"key": "refugee_pads:000104:31:0:0", "start": 226, "end": 240, "surface": "NaCSA M&E data", "probe_tag": "drop", "probe_score": 0.0279, "luna_label": 0, "luna_reason": "Listed as a table source without a concrete finding or demonstrated data use."}, {"key": "refugee_pads:000104:31:0:1", "start": 412, "end": 437, "surface": "NaCSA administrative data", "probe_tag": "confusion", "probe_score": 0.1197, "luna_label": 1, "luna_reason": "Named administrative data cited as a verification source for program results."}, {"key": "refugee_pads:000104:31:0:2", "start": 1188, "end": 1214, "surface": "NaCSA adrninistrative data", "probe_tag": "confusion", "probe_score": 0.4274, "luna_label": 0, "luna_reason": "Listed as logframe verification data, without demonstrated substantive use."}]}, {"key": "aivin2-149", "text": "**The World Bank**\nPublic Administration Modernization Project (P162904)\n\n\nsupported by the Social Safety Net Project (P130138). <sup>16</sup> [^16: The Djibouti Social Safety Net Project is a World Bank-funded project, with an Additional Financing that also supports the\nSocial Registry and National Social Protection Strategy. The registry currently contains information about 42,000 households,\nexceeding the target of 20,000. The collection of biometric data about these households has been launched and biometric\ninformation about 33,000 beneficiaries has been registered. The Djibouti Public Administration Modernization Project will be\ncollaborating closely with the safety net project team. The Project will build on lessons learned from the enrollment and\nregistration phase conducted by the Social Affairs Department.] The experiences, capabilities, information\ncollected, and possibly some of the technology resources will be leveraged to derisk the project and\noptimize the use of available resources. The same coordination effort between ANSIE and sector\nministries is being followed in the development of e-services.\n\n\n53. The theory of change, as presented through the Results Chain in annex 1, is that supporting\ninstitutional and capacity building on access to information, asset disclosure, transparency, and\naccountability—as well as putting in place a solid foundation of e-government (unique ID, cybersecurity,\nPKI, and so on) and modernizing revenue administration services—will increase access to services and\nreduce transaction costs. In addition, it will reduce opportunities for fraud by disintermediating the\ninteractions between citizens, businesses, and civil servants. This will give more credibility to the\ncommitment by the authorities to improve services, governance, accountability, and fight corruption.\nFurthermore, the provision of more information to the citizenry, public feedback about the quality of\nservices delivered, and citizen interaction with the digital platform including public data disclosure (open\ndata) will increase engagement and cooperation in the public service delivery system. This would\nultimately contribute to greater legitimacy and stability.\n\n\n54. **Tax and customs administration modernization.** The", "source": "refugee_pads", "subset": "annotate_aivin_part2", "spans": [{"key": "sample:refugee_pads:000142:26:0:0", "start": 2045, "end": 2054, "surface": "open\ndata", "probe_tag": "drop", "probe_score": 0.0, "luna_label": 0, "luna_reason": "Open data is mentioned as a disclosure mechanism, without showing data use."}]}, {"key": "aivin2-150", "text": "up>**(1)**</sup>, and\n**Eritrea** were the five top source\ncountries of asylum-seekers in the\n44 industrialized countries in 2014.\n\n\n<mark>149,600</mark>\n\n\nThe **Syrian Arab Republic**\nremained the main country\nof origin of asylum-seekers\nin industrialized countries.\nProvisional data indicate that\nsome 149,600 Syrians requested\nrefugee status in 2014, more\nthan double the number of 2013\n(56,300 claims) and 17 times\nmore than in 2011 (8,700 claims).\nThe 2014 level is the highest\nnumber recorded by a single\ngroup among the industrialized\ncountries since 1992.\n\n\nUNHCR Asylum Trends 2014 **3**\n\n\n\nthe largest single recipient of new\nasylum claims among the group\nof industrialized countries.\n\n\n(1) References to Kosovo shall be understood to\nbe in the context of Security Council resolution 1244\n(1999), henceforth referred to in this document as\nKosovo (S/RES/1244 (1999)).\n\n\n\nThe **United States of America**\nwas second with an estimated\n121,200 asylum applications,\nfollowed by **Turkey** (87,800),\n**Sweden** (75,100), and **Italy**\n(63,700). The top five receiving\ncountries together accounted\nfor six out of ten new asylum\nclaims submitted in the 44\nindustrialized countries.", "source": "reliefweb", "subset": "annotate_aivin_part2", "spans": [{"key": "reliefweb:000195:2:1:0", "start": 268, "end": 284, "surface": "Provisional data", "probe_tag": "keep", "probe_score": 0.9473, "luna_label": 1, "luna_reason": "Provisional data support concrete asylum-seeker counts and comparisons."}]}, {"key": "aivin2-151", "text": "The analysis draws on multiple data sources including: (1) individual consumer\n\nexpenditure and income by type from the Household Expenditure and Income\n\nSurveys; (2) individual-level panel data from the Jordan Labor Market Panel Survey;\n\n(3) children’s health development outcomes from the Demographic and Health Survey;\n\n(4) data on satellite night light density from the National Oceanic and Atmospheric\n\nAdministration; (5) data on the location of refugee camps from UNHCR; and (6) data\n\non Syrian settlements in Jordan before the civil war from the 2004 _Housing and_\n\n_Population Census_ .\n\n\nMain findings:\n\n\n- **Syrian refugee flows increased housing rental prices in Jordan** . Housing\n\nrental prices increased closer to refugee camps after the onset of the Syrian civil war\n\nin 2011.\n\n- **Overall, Jordanians living closer to the refugee camps increased their**\n\n**housing expenditures** . While overall, total consumption expenditure remained\n\nunchanged, Jordanians living closer to the refugee camps compensated for higher\n\nhousing (and transport) costs by decreasing their spending on food, communication\n\nservices, education, and health.\n\n- **Some segments of the population living near the refugee camps were**\n\n**adversely affected, including people with lower educational attainment, younger**\n\n**people, and people working in the informal sector** . Total consumption expenditure\n\nfell for individuals with less than a high school education, with sharp reductions in their\n\nspending on non-food items, food, communication, and health. Higher expenditures\n\non housing were accompanied by worse dwelling quality for individuals aged 26 to 40\n\nand those working in the informal sector. The analysis also suggests that refugee\n\nexposure can have negative effects of on self-employment (across all education\n\nlevels) consistent with the idea that refugees may be displacing workers in the informal\n\nsector.\n\n- **Jordanians located closer to refugee camps have higher property and**\n\n**rental income** . The positive effect of", "source": "reliefweb", "subset": "annotate_aivin_part2", "spans": [{"key": "reliefweb:001689:17:0:1", "start": 120, "end": 161, "surface": "Household Expenditure and Income\n\nSurveys", "probe_tag": "keep", "probe_score": 0.9618, "luna_label": 1, "luna_reason": "Analysis draws on these surveys to support findings on expenditure and income effects."}, {"key": "reliefweb:001689:17:0:4", "start": 291, "end": 320, "surface": "Demographic and Health Survey", "probe_tag": "keep", "probe_score": 0.9477, "luna_label": 1, "luna_reason": "Analysis draws on this survey for children’s health development outcomes."}, {"key": "reliefweb:001689:17:0:8", "start": 554, "end": 593, "surface": "2004 _Housing and_\n\n_Population Census_", "probe_tag": "keep", "probe_score": 0.9489, "luna_label": 1, "luna_reason": "Named census data are included among sources used in the analysis."}]}, {"key": "aivin2-152", "text": "serves du foyer ou de la communauté, ou aux manques de moyens du foyer à cause\nd’un revenu trop bas ou de prix trop hauts. En février 2022, 88,4% des foyers de l’Extrême-Nord dépensaient\nplus de 50% de leurs revenus en nourriture. Les prix atteignent leur pic en août, juste avant les récoltes, ce qui\naffecte la consommation des ménages. Les familles semblent faire face à des pénuries de nourriture entre avril\net juin, quand le labour et les semis sont en cours. Après juillet, la situation s’améliore rapidement, jusqu’à la fin\nde l’année. <sup>68</sup> [^68: WFP, Seasonal Analysis of Severe Acute Malnutrition, Far North Region, Cameroon, Mai 2022.]\n\n\nLes conflits intercommunautaires ont causé des dommages matériels, du pillage, des cessations d’activités, à\ncause desquels les déplacés souffrent d’une situation urgente en termes d’insécurité alimentaire. 76% des foyers\nont un score de consommation alimentaire pauvre ou limité, et 73% ont un score de diversité alimentaire bas.\nEn ce qui concerne les retournés, 85% des foyers sont dans une situation de vulnérabilité alimentaire. Cette\nsituation est aggravée dans les foyers comprenant des femmes enceintes ou allaitantes, et des enfants de moins\nde 5 mois. <sup>69</sup>\n\n\n61 Commune de Logone-Birni, Plan Communal de Développement de Logone-Birni, Novembre 2014", "source": "reliefweb", "subset": "annotate_aivin_part2", "spans": [{"key": "sample:reliefweb:000568:20:2:0", "start": 569, "end": 615, "surface": "Seasonal Analysis of Severe Acute Malnutrition", "probe_tag": "keep", "probe_score": 0.9915, "luna_label": 1, "luna_reason": null}]}, {"key": "aivin2-153", "text": "_ basis as well\nas those who have been newly registered and\ngranted temporary protection. An additional\n398,500 persons were granted refugee status or a\ncomplementary form of protection following refugee\nstatus determination during the reporting period.\n\n\nThe conflict in Syria continued to cause people to\nflee that country, with 280,700 new refugees in the\nfirst half of the year alone as well as some 209,600\ngranted refugee status or a complementary form of\n\n\n**3** Operational data show that daily arrivals to countries transited\nen-route to Germany such as Serbia and Austria decreased\nfrom highs of 10,000 per day seen in October 2015 to highs of\n300 by April 2016 and 200 by September 2016.\n[www.data.unhcr.org](http://www.data.unhcr.org)\n\n\n\n10 u n h c r > **m i d - y e a r t r e n d s** **2 0 1 6**", "source": "reliefweb", "subset": "annotate_aivin_part2", "spans": [{"key": "sample:reliefweb:001232:9:1:0", "start": 470, "end": 486, "surface": "Operational data", "probe_tag": "keep", "probe_score": 0.9883, "luna_label": 1, "luna_reason": null}]}, {"key": "aivin2-154", "text": "-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-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-Q3<br>Q1<br>Q2<br>Q3<br>Q4<br>Italy|Total<br>2007<br>including<br>Italy|\n|Origin|No. of applications (excluding Italy)|No. of applications (excluding Italy)|No. of applications (excluding Italy)|No. of applications (excluding Italy)|No. of applications (", "source": "reliefweb", "subset": "annotate_aivin_part2", "spans": [{"key": "sample:reliefweb:000427:22:11:0", "start": 167, "end": 179, "surface": "monthly data", "probe_tag": "keep", "probe_score": 0.9262, "luna_label": 1, "luna_reason": null}, {"key": "sample:reliefweb:000427:22:11:1", "start": 521, "end": 533, "surface": "monthly data", "probe_tag": "keep", "probe_score": 0.9072, "luna_label": 1, "luna_reason": null}]}, {"key": "aivin2-155", "text": "Chapter 3\n\n\n**Almost 1 in every 2 primary and secondary school-**\n**aged refugees were enrolled in national education**\n**systems in 51 countries with data.**\n\n\nAccording to data from 51 countries, 48 per cent of\nprimary and secondary school-aged refugees were\nenrolled in national education systems. Data on\nthe enrolment rate of refugee children in national\neducation systems was mostly available where\nUNHCR or its implementing partners operated\nparallel education systems, such as camp-based\nschools. Conversely, in countries with inclusive\npolicies and refugee children enrolled in national\nschools, few countries could report on refugees’\nenrolment rate. For example, despite the region\nhaving a very favourable policy environment,\nonly one European country provided data for this\nindicator. Similarly, in the Americas, where the\nmajority of countries had inclusive policies, data was\navailable for only three countries. <sup>44</sup> [^44: GLOBAL COMPACT ON REFUGEES INDICATOR REPORT]\n\n\n\n**A favourable policy environment did not guarantee**\n**effective access to schooling due to barriers.**\n\n\nThere was a general positive correlation between\nnational policies on inclusive education and refugee\nenrolment rates. More inclusive national policies in\neducation contributed to higher enrolment rates for\nrefugee children. However, the data showed that\nmost reporting countries had refugee enrolment\nrates below 50 per cent, despite having favourable\npolicy environments. Many countries among the 51\ncountries with data, had enrolment rates ranging\nfrom one to 30 per cent, despite providing legal\naccess to educational systems (Figure 22). This\nhighlighted that while children had a legal right to\naccess schools, it did not necessarily mean that\nrefugees could do so in practice. To advance in\nthis area, it is crucial to address the main barriers\nhampering effective access to education, including\nthose related to nationality, legal status, and\ndocumentation, enabling refugee children to be\nenrolled in authorized institutions.\n\n\n\nFigure 22: **Primary and secondary education inclusion, 2022**\n\n\n100\n\n\n80\n\n\n60\n\n\n40\n\n\n20\n\n\n0\n\n\n\n\n\n|Col1|", "source": "reliefweb", "subset": "annotate_aivin_part2", "spans": [{"key": "reliefweb:000435:43:0:0", "start": 174, "end": 196, "surface": "data from 51 countries", "probe_tag": "keep", "probe_score": 0.9528, "luna_label": 1, "luna_reason": "Data from 51 countries supports the reported 48 percent enrollment finding."}]}, {"key": "aivin2-156", "text": "\non need, not mandates or artificial legal categorizations‟.\n52 See further Alice Edwards, 'Overview of International Standards and Policy on Gender Violence and\nRefugees: Progress, Gaps and Continuing Challenges for NGO Advocacy and Campaigning'. Paper\ndelivered at the Canadian Refugee Council International Refugee Rights Conference, Toronto, Canada, 1719 June 2006. Amnesty International, AI Index: POL/33/004/2006.\n\n13", "source": "reliefweb", "subset": "annotate_aivin_part2", "spans": [{"key": "reliefweb:001303:14:1:0", "start": 393, "end": 401, "surface": "AI Index", "probe_tag": "confusion", "probe_score": 0.4235, "luna_label": 0, "luna_reason": "Bibliographic index citation with no demonstrated data use or finding."}]}, {"key": "aivin2-157", "text": "the approach to youth, who are often left out of the\ntraditional assistance scheme.\n\n\n**The response to COVID-19 also benefited from high**\n**levels of data disaggregation** . In **Malaysia** and **Yemen,**\nAGD-disaggregated data were useful in identifying\npriority groups to be enrolled in the national COVID-19\nimmunization programme, particularly those living with\ndisabilities, older people and those with serious medical\nconditions.\n\n\nAmong the examples of how **AGD-disaggregated**\n**data allowed access to programmes and activities,**\naccording to the findings of the Global Survey on\nRegistration, Biometrics, and Digital Identity, in\n**Iraq** AGD-friendly registration processes are fully\nmainstreamed across all registration locations and\nfacilities to accommodate groups at heightened\nrisk, child-friendly spaces exist, access is facilitated\nfor those using wheelchairs, and UNHCR staff are\ntrained to consider AGD dimensions. In **Borno State,**\n**Nigeria,** women, girls, older persons, female heads of\nhouseholds, caregivers, and persons with disabilities\n\n\n\nwere screened to assess their vulnerabilities and needs\nin order to decide on the provision of protection and\nlife-saving assistance. Targeting the most vulnerable\nIDPs using the vulnerability screening tool challenged\nthe pre-existing socially constructed inequalities based\non the roles of women, girls, men and boys. In addition,\nall the eligible beneficiaries were targeted equally\nconcerning cultural sensitivities. <sup>38</sup> [^38: UNHCR, “AGD Report 2021 case study examples: Shelter and settlement” (2022).]\n\n\nAmong the countries that reported **collecting and**\n**using disaggregated data for monitoring and**\n**evaluation purposes** are **Afghanistan, Bulgaria,**\n**Croatia, Ecuador, Hungary Multi-Country Office**\n**(MCO), India, Islamic Republic of Iran, Malaysia,**\n**Morocco, Spain** and the", "source": "reliefweb", "subset": "annotate_aivin_part2", "spans": [{"key": "reliefweb:000524:22:0:0", "start": 207, "end": 229, "surface": "AGD-disaggregated data", "probe_tag": "confusion", "probe_score": 0.3241, "luna_label": 1, "luna_reason": "Existing disaggregated data informed identification of priority immunization groups."}, {"key": "reliefweb:000524:22:0:1", "start": 1655, "end": 1673, "surface": "disaggregated data", "probe_tag": "confusion", "probe_score": 0.0626, "luna_label": 0, "luna_reason": "The sentence explicitly reports collecting the data as part of the activity."}]}, {"key": "aivin2-158", "text": "**I. APERCU DE L’ENVIRONNEMENT SECURITAIRE ET DE PROTECTION**\n\n\nLe mois de juillet 2022 a été caractérisée par une insécurité croissante dans les zones couvertes par le projet de monitoring\nde protection dans la région de Maradi. L’on a assisté à une dégradation du contexte sécuritaire, marqué par la multiplication\ndes incursions des groupes armés non étatiques (GANE) dans les villages situés le long de la frontière avec le Nigéria. Au\ntotal, le système de suivi a permis de rapporter 24 incursions armées dans les zones sous monitoring, contre 10 pour le mois\nde juin. Sur la même période, l’on a noté l’attaque à main armée d’un camion tombé en panne à Guidan Roumdji, sur la route\nnationale (RN1) et des menaces proférées par les GANE à l’endroit des exploitants des terres agricoles de certaines localités\nfrontalières des communes de Gabi, Safo et Sarkin Yamma. Cette recrudescence des incursions semble marquer un retour\nen « vrai » des groupes armés dans les villages frontaliers des départements de Guidan Roumdji et Madarounfa, avec au\ncentre de leurs actions de multiples violations des droits humains. Cette situation crée un sentiment de psychose qui, à termes\nrisque de compromettre les travaux champêtres, alors que la saison s’annonce prometteuse. Au-delà, elle risque de réduire\nl’accès humanitaire dans les zones affectées.\n\n\nDe toute évidence, la saison", "source": "reliefweb", "subset": "annotate_aivin_part2", "spans": [{"key": "reliefweb:000193:1:0:0", "start": 450, "end": 466, "surface": "système de suivi", "probe_tag": "confusion", "probe_score": 0.5562, "luna_label": 1, "luna_reason": "Monitoring system data reports 24 armed incursions and supports the security finding."}]}, {"key": "aivin2-159", "text": "**Economic Survey of Syrian Refugees in the Kurdistan Region of Iraq, April 2014**\n\n\nConcerning outside work, it was reported by actors present in Gawilan camp that **many of the refugees who work**\n**outside the Gawilan camp are single males**, which can explain that none of the interviewed household reported this\ntype of income.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nThe fact that Gawilan is a closed camp, i.e. a camp where nearly all refugees are without a residency card and are\ntherefore confined to the camp, limits significantly the freedom of movement of refugees wishing to work outside the\ncamp. That being said, this alone does not explain the situation, as there are similar restrictions of movement in other\nrefugee camps. In closed camps, (Gawilan, Qushtapa, Darashakran, Kawergosk), individuals working outside the camp\ncan receive a daily authorisation to leave the camp for a limited period of time.\n\n\nThe opposite situation that was found **in Akre**, where **outside work was more commonly relied on than CFW**, could\nbe explained by the fact that few NGOs are present in the camp to offer CFW combined to the availability of outside\nwork. It may also be due to the setting of the camp itself, where people live very closely to each other in a building\ninstead of tents, which might limit the possibilities for CFW activities generally associated with camp settings (from\ntrench digging for water infrastructures to hiring daily labourers to walk around camps for public announcements).\nAnother potential hypothesis to explain this finding could be that the availability of CFW opportunities might act as a\ndeterrent against finding outside work but anecdotal evidence from FGDs suggests otherwise. In fact, **FGD**\n**participants often mentioned that while CFW is indeed central to many refugee households’ income, it**\n**generally remains a coping strategy households resort to when outside", "source": "reliefweb", "subset": "annotate_aivin_part2", "spans": [{"key": "reliefweb:000688:14:0:1", "start": 1675, "end": 1679, "surface": "FGDs", "probe_tag": "confusion", "probe_score": 0.8723, "luna_label": 1, "luna_reason": "Focus group discussions provide anecdotal evidence for the stated finding."}]}, {"key": "aivin2-160", "text": "**A/AC.96/1178**\n\n\ncities in 2017. In April 2018, the OECD published research from 72 cities on local\napproaches to integration, accompanied by a checklist for cities and regions to use in\npromoting integration.\n\n\n56. Successful local integration programmes require efforts from all parties, including\nrefugees in their willingness to adapt, host communities in welcoming them and public\ninstitutions in meeting their needs. In some countries, significant additional support from\nthe international community, taking into account the needs of receiving communities, is\nessential.\n\n\n**D.** **Other pathways for admission**\n\n\n57. Other pathways for the admission of persons needing international protection can\nfacilitate access to protection and solutions, and alleviate pressure on host countries,\nparticularly in large-scale and protracted situations. Such pathways also create\nopportunities for refugees to learn new skills, acquire an education and reunite with family\nmembers in third countries.\n\n\n58. Although refugees sometimes find complementary pathways themselves, such\nprocesses may require the facilitation of administrative measures, complemented with\nprotection safeguards. To this end, UNHCR helped support the establishment and\nexpansion of complementary pathways, including in Argentina, Brazil, Chile, Colombia,\nFrance, Japan and Peru, along with other States in the MERCOSUR region. A new\npartnership was established with the United World Colleges to expand secondary education\nfor refugee students in third countries, and Talent Beyond Boundaries was commissioned to\ncreate a database of refugee talent in Jordan and Lebanon to facilitate labour mobility to\nthird countries. UNHCR and OECD initiated a mapping of non-humanitarian entry visas\nused by refugees in OECD countries to help develop guidance on complementary\npathways. UNHCR also supported the adoption of the African Union Protocol on Free\nMovement of Persons, Right of Residence and Right of Establishment, which will facilitate\naccess to other pathways for admission.\n\n\n59. Despite progress, refugees continue facing barriers and challenges in accessing\ncomplementary pathways, including being unable to obtain exit permits, entry visas and\ntravel documents. Other challenges include", "source": "reliefweb", "subset": "annotate_aivin_part2", "spans": [{"key": "reliefweb:001472:15:0:0", "start": 1594, "end": 1620, "surface": "database of refugee talent", "probe_tag": "confusion", "probe_score": 0.1252, "luna_label": 0, "luna_reason": "Database is being created by a commissioned activity, so it does not yet exist."}, {"key": "reliefweb:001472:15:0:1", "start": 1720, "end": 1759, "surface": "mapping of non-humanitarian entry visas", "probe_tag": "confusion", "probe_score": 0.8482, "luna_label": 0, "luna_reason": "Mapping was initiated as an ongoing data-production activity, not cited existing data."}]}, {"key": "aivin2-161", "text": "vulnerable people with humanitarian assistance\nand other services through a network of community\ncentres while pursuing a dialogue with the Syrian\nGovernment and other stakeholders to address\nobstacles to voluntary and sustainable return and\nreintegration.\n\n\nOther notable returns during the year included\nCameroonian refugees returning from Chad (30,800),\nBurundian refugees returning from Uganda (10,100),\nand Ivorian refugees returning from Liberia (12,900).\nIn Burundi, monitoring conducted by UNHCR and\npartners in return destinations indicated a low\ncapacity of returnees to access essential social\nservices, which made some refugees reluctant\nto return. In Côte d’Ivoire, an updated <u>[Regional](https://data2.unhcr.org/en/documents/details/89034)</u>\n<u>[Roadmap for Comprehensive Solutions for Ivorian](https://data2.unhcr.org/en/documents/details/89034)</u>\n<u>[Refugees was launched in 2021 to find a durable](https://data2.unhcr.org/en/documents/details/89034)</u>\nsolution for every Ivorian refugee and bring closure\nto the situation by the end of 2022.\n\n\nThe Venezuelan authorities reported that since\nSeptember 2018, over 30,000 other people in need\nof international protection returned to their country\nunder a government-organized return plan called\n“Plan Vuelta a la Patria”. Overall, including selforganized returns, some 300,000 Venezuelans were\nreported by the Venezuelan authorities as returning\nto their country by the end of 2022.\n\n**Outcome 2: Refugees are able to return**\n**and reintegrate socially and economically**\n\n**Data on legal identity remained largely unavailable.**\n\n\nA legal identity is essential to enjoying rights and\nenabling access to basic services and opportunities.\nThe lack thereof is often a cause and effect of\ndisplacement and state", "source": "reliefweb", "subset": "annotate_aivin_part2", "spans": [{"key": "reliefweb:000435:58:0:0", "start": 1549, "end": 1571, "surface": "Data on legal identity", "probe_tag": "confusion", "probe_score": 0.3921, "luna_label": 0, "luna_reason": "Pure availability statement without an analyzed finding or substitute estimate."}]}, {"key": "aivin2-162", "text": "The following table captures the number and nature of interviews conducted during our 2012\nfieldwork:\n\n\nColombia Haiti Kenya Thailand\n\n\nShelter programs studied 8 6 10* 15\n\n\nShelter staff interviews** 10 8 15* 27\n\n\nShelter resident interviews 7 5 7 6\n\n\nKey informant interviews 28 9 21 31\n\n\n- Not including Dadaab surveys conducted in 2011 or follow-up communications in 2012.\n** Some interviews included more than one respondent, as is explained in the country reports.\n\n\n_Data Analysis_\n\nA team of five to six analysts coded the transcripts using Dedoose qualitative coding software. In all\ncases, the lead field researcher led the coding. Each team carried out thematic coding of the transcripts,\nusing a series of deductive codes developed to reflect key questions in the interview instruments.\nIn addition, researchers employed an inductive approach to identify patterns in respondent experiences. Select transcripts were double-coded by each lead researcher to check for and ensure intercoder\nreliability.\n\n\n_Limitations_\n\nStudy limitations varied for each fieldwork mission. <sup>14</sup> Common limitations included time constraints\n(four to seven weeks per country), limited access to certain refugee camps due to security issues or\nlack of permission, and reliance on program staff to recruit shelter residents and act as interpreters in\nsome cases.\nIn light of our sample-specific data, we are also limited in our ability to provide generalizable statements. However, we offer broad recommendations based on patterns that emerged among the four\ncase studies in hopes that they will spur dialogue, broader thinking, and further research.\n\n\n_Ethical Approval_\n\nEthical approval was provided by the University of California, Berkeley’s Committee for the Protection\nof Human Subjects. When possible, we also obtained local ethical clearance from authorized local\nentities.\n\n\n**SAFE HAVEN | COMPARATIVE REPORT** **15**", "source": "reliefweb", "subset": "annotate_aivin_part2", "spans": [{"key": "reliefweb:001484:19:0:1", "start": 1376, "end": 1396, "surface": "sample-specific data", "probe_tag": "confusion", "probe_score": 0.7989, "luna_label": 1, "luna_reason": "Existing sample data supports a stated limitation on generalizability."}]}, {"key": "aivin2-163", "text": "Apéndice A. Fuentes de datos por país\n\n\n56\n\n\nhogares en el 2021, la GEIH es\nrepresentativa de las 24 ciudades\ncapitales y áreas metropolitanas\n(incluida Bogotá), zonas geográficas\nrurales y urbanas y 23 departamentos.\nEl presente informe restringe las\ncomunidades receptoras a los\nhogares urbanos, donde viven casi\ntodos los venezolanos. La muestra\nincluye 447,888 colombianos y la\nencuesta se realizó unos meses\nantes de la encuesta de migrantes.\n\n\nEcuador\n\n\n**El análisis para Ecuador se basa**\n**en la cuarta ronda de la HFPS**\n**realizada en el 2022 y la Encuesta**\n**a Personas en Movilidad Humana**\n**y** **en** **Comunidades** **Receptoras**\n**en Ecuador o EPEC del 2019** . La\ncuarta ronda de la encuesta HFPS\nconstituyó un esfuerzo conjunto\ndel Banco Mundial y PNUD para\nmedir el impacto de la pandemia\nCOVID-19 en los hogares de la\nregión ALC. También recopiló datos\nsobre los hogares venezolanos\ncon el fin de evaluar si la pandemia\ntuvo un efecto diferencial en los\nmigrantes. La encuesta telefónica es\nrepresentativa de los venezolanos\nen Ecuador y de los ecuatorianos\nambos mayores de 18 años que\ntenían una línea telefónica fija o móvil\nactiva. Dado que la mayoría de las\ncompañías telefónicas exigen una\nidentificación nacional, es probable", "source": "reliefweb", "subset": "annotate_aivin_part2", "spans": [{"key": "reliefweb:001322:55:0:1", "start": 425, "end": 446, "surface": "encuesta de migrantes", "probe_tag": "confusion", "probe_score": 0.7884, "luna_label": 0, "luna_reason": "Survey is only mentioned as a timing reference, without cited findings or analytical use."}, {"key": "reliefweb:001322:55:0:4", "start": 871, "end": 906, "surface": "datos\nsobre los hogares venezolanos", "probe_tag": "confusion", "probe_score": 0.6552, "luna_label": 1, "luna_reason": "Past-collected data used to assess pandemic effects on Venezuelan migrants."}, {"key": "reliefweb:001322:55:0:5", "start": 992, "end": 1011, "surface": "encuesta telefónica", "probe_tag": "confusion", "probe_score": 0.8079, "luna_label": 1, "luna_reason": "Existing telephone survey supports a concrete representativeness claim."}]}, {"key": "aivin2-164", "text": ">Guinea<br>5<br> <br>18<br> <br>*<br>6<br> <br>*<br>-<br> <br>*<br>130<br> <br>57<br> <br>266<br> <br>-<br> <br>29<br> <br>130<br> <br>469<br> <br>** Refers to January to November only (December data not available).<br>*** Figures may include citizens of Montenegro in the absence of separate statistics available for Serbia and for Montenegro.<br>**** UNHCR estimate.<br>***** Combination of number of persons (EOIR) and cases (DHS).|Origin<br>Poland<br>Portugal<br>Rep. of<br>Korea<br>Romania<br>Serbia<br>Slovakia<br>Slovenia<br>Spain<br>Sweden<br>Switzerland<br>TfYR<br>Macedonia<br>Turkey<br>United<br>Kingdom<br>United<br>States*****<br>Afghanistan<br>14<br> <br>-<br> <br>8<br> <br>87<br> <br>218<br> <br>51<br> <br>11<br> <br>43<br> <br>1,694<br> <br>719<br> <br>71<br> <br>1,009<br> <br>3,535<br> <br>129<br> <br>Iraq<br>21<br> <br>-<br", "source": "reliefweb", "subset": "annotate_aivin_part2", "spans": [{"key": "reliefweb:000810:17:29:0", "start": 353, "end": 367, "surface": "UNHCR estimate", "probe_tag": "confusion", "probe_score": 0.2242, "luna_label": 1, "luna_reason": "Identifies UNHCR as the source of estimates underlying the table figures."}]}, {"key": "aivin2-165", "text": "**<mark>LANDMINES AND EXPLOSIVE REMNANTS OF WAR</mark>**\n\n\n\nThe explosive legacy of conflict in South Sudan means that nearly\neight million people live in counties which are impacted by landmines\nand explosive remnants of war, with 94 million square metres of land\ncontaminated by explosive hazards recorded in the mine action\ndatabase. During the reporting period, mine action teams were\ndeployed across the country and conducted surveys, clearance,\nand/or risk education to support protection of civilian activities, create\nconditions for the delivery of humanitarian assistance, and support\nhuman rights monitoring and reporting.\n\nThe map below illustrates the spread of known explosive hazards\nacross all of South Sudan. The full extent of contamination remains\nunknown, as the Greater Upper Nile region (including Unity, Upper\nNile, and Jonglei) has not yet been comprehensively surveyed and\nthe impact of armed violence in the region remains to be quantified.\n\nDuring the last three quarters of 2015, a significant number of new\nhazardous areas were found than cleared and closed. Comparing\n2016 with 2015, UNMAS recorded 699 new explosive hazards,\ncompared to 533 new hazards in the first quarter of 2015, highlighting\nthat the incremental increase is caused by more than seasonal\nfactors.\n\nThe increase in the number of hazards known to UNMAS has multiple\ndeterminants:\n\n1: Ongoing conflict has increased the proliferation of explosive\n\n\n\nhazards. There is currently no evidence relating to the laying of new\nminefields; rather, the majority of contamination resulting from the\ncurrent conflict is unexploded ordnance (UXO) such as grenades and\nmortars. Still, the threat posed by UXO is significant: While an anti-personnel mine is designed to kill or maim one person, a single UXO has a\ngreater blast radius. During this quarter, 30 people were killed and\nmaimed, including 10 children, yet only two of those people were\ninjured by landmines and the remainder by UXO. An analysis of\naccident information shows a link to young boys engaged in", "source": "reliefweb", "subset": "annotate_aivin_part2", "spans": [{"key": "reliefweb:000827:6:0:0", "start": 315, "end": 335, "surface": "mine action\ndatabase", "probe_tag": "confusion", "probe_score": 0.1029, "luna_label": 1, "luna_reason": "Database records support the reported extent of contaminated land."}]}, {"key": "aivin2-166", "text": " unlike physical capital, social capital does not wear out\nwith use, but rather deteriorates from disuse. (Grootaert and van Bastelaer, 2001, pp.\n7-8).\n\n\nA number of tools have been developed to measure social capital. Some rely on\ncommunity-level indicators, such as the number of associations in a city. Others\ninvolve individual or household-surveys which ask questions such as: membership in\nclubs, societies or social groups to which individuals belong; networks and social\ncontact (how often individuals see family, friends and acquaintances); as well as\nnorms and values (whether individuals trust their neighbours and whether they\nconsider their neighbourhood a place where people help each other).\n\n\nThe World Bank has developed a social capital assessment tool. This involves three\nparts. The community profile outlines how to conduct open-ended community\ndiscussions and structured community interviews. The household survey explores\nboth the structural dimensions of social capital (organizational density, expectations\nregarding networks and mutual support, patterns of exclusion, nature of previous\ncollective action) and cognitive elements (solidarity, trust and cooperation, conflict\nand conflict resolution). The final part of the tool demonstrates how to conduct\norganizational profiles of key local organizations. (World Bank, 2002)\n\n\nThese measures are obviously proxy indicators, rather than a measure of social capital\nitself. However, and despite this limitation, which admittedly exists for the wellestablished concept of human capital as well, there is a growing consensus among\n\n\n8", "source": "reliefweb", "subset": "annotate_aivin_part2", "spans": [{"key": "reliefweb:001000:9:1:0", "start": 232, "end": 258, "surface": "community-level indicators", "probe_tag": "confusion", "probe_score": 0.4571, "luna_label": 0, "luna_reason": "Conceptual indicator example, not an attributed finding or data use."}, {"key": "reliefweb:001000:9:1:2", "start": 919, "end": 935, "surface": "household survey", "probe_tag": "confusion", "probe_score": 0.6912, "luna_label": 0, "luna_reason": "Describes a survey instrument, not existing survey data used for analysis."}]}, {"key": "aivin2-167", "text": "\nall, and specifically with SDG 4 targets 4.c on qualified teachers, 4.a on safe learning environments, and indicator 4.1.1 on\nlearning.\n\n\n - **To international and regional learning assessments:** Incorporating refugee learners in existing learning\nassessments is a low-cost way to improve knowledge on the quality of refugee learners’ education (a key indicator\nidentified for SDG monitoring as identified by EGRISS). LLECE in Latin America is already piloting the way forward in its\nnext round of ERCE in 2025 and their methodological notes will provide many opportunities for peer learning.\n\n - **To Ministries of Education and National Statistical Offices:** Where refugees are already included in learning\nassessments and administrative data, reporting these data in a disaggregated way so that the needs of refugee\nlearners may be clearly identified and better understood is critical. Where they are not included, collaborating with\ninternational partners to include refugees within existing assessments is crucial. Administrative data on teachers and\nschool facilities can also fill critical knowledge gaps and should be made available to partners.\n\n\n**Develop shared definitions and indicators for both refugee identification and education-related indicators across**\n**the humanitarian-development spectrum to improve data quality and ensure that the data collected is comparable**\n**across different DCEs.** This would align with previous recommendations to continue to improve data quality and accuracy,\nstrengthen the methodologies used to produce data, and improve the timeliness and usability of the data collected\non crisis-affected learners (Montjourides, 2013, p. 85). The creation of common indicators for refugee education, with\nstandardized definitions and methodologies for measuring these indicators (e.g. on attendance) used within national data\nsystems and across partners, would improve both intra and inter-agency coordination while enabling the comparability of\ndata and facilitating uptake into policy-making processes. This could also be facilitated by collaborative development of\nshared modular analysis tools, not only for refugees but", "source": "reliefweb", "subset": "annotate_aivin_part2", "spans": [{"key": "reliefweb:000382:55:1:0", "start": 728, "end": 747, "surface": "administrative data", "probe_tag": "confusion", "probe_score": 0.43, "luna_label": 1, "luna_reason": "Existing administrative data are reported disaggregated to identify refugee learners' needs."}]}, {"key": "aivin2-168", "text": "; it also imposes considerable demands on both the individual and the receiving society. Over time the process should lead to\npermanent residence rights and, in some cases, the\nacquisition of citizenship in the country of asylum. The\nobjective of local integration is for integrated refugees to be able to pursue sustainable livelihoods and\ncontribute to the economic life of the host country,\nand live among the host population without discrimination or exploitation.\n\nMeasuring and quantifying the degree and nature\nof local integration is challenging, and the available\n\n\n**25** During the US fiscal year 2015, 69,933 people were resettled\nto the United States of America. Figures for Canada included\nprivate sponsorship programme arrivals. Figures for Australia\nincluded departures under the Special Humanitarian\nProgramme.\n\n\n\n**28**\n**26**\n\n\n\n**25** **24**\n\n\n\n**28**\n**26**\n\n\n\n**21** **20**\n\n\n\n**17**\n\n\n\n**18** **17**\n\n\n\n**12** **12**\n\n\n\n**16**\n**14**\n\n\n\n**26** UNHCR Global Trends 2015", "source": "reliefweb", "subset": "annotate_aivin_part2", "spans": [{"key": "reliefweb:001367:24:2:0", "start": 967, "end": 991, "surface": "UNHCR Global Trends 2015", "probe_tag": "confusion", "probe_score": 0.5873, "luna_label": 1, "luna_reason": "Named UNHCR report cited alongside resettlement figures."}]}, {"key": "aivin2-169", "text": "**a.** Actions and policies need to be grounded in\nthorough knowledge and understanding of land and\nproperty dynamics prevalent in areas of planned\nrelocation. For example, multiple forms of land and\nproperty frameworks (traditional/customary, collective and individual, private and social, formal and\ninformal, local versus national, etc.) may co-exist;\nthere may be a disconnect between the formal State\nland tenure laws and the way land and property\nrelations are actually managed on the ground; and\ninformal land tenure arrangements and/or existing\ncadastres and land title registries may not be reliable,\netc.;\n\n\n**b.** Macro-level policy setting needs to be accompanied by micro-level political engagement, since land\nand property relations are highly contextual and\noften highly politicized;\n\n\n**c.** The feasibility of action should be ascertained\nfrom the outset, with policies grounded in a realistic\nassessment of institutional capacities. <sup>58</sup>\n\n\n73. Among the multiple sources of potentially valuable guidance on land, housing, and property are:\nthe FAO Voluntary Guidelines on the Responsible\nGovernance of Tenure of Land, Fisheries, and Forests in the Context of National Food Insecurity, the\nUnited Nations Principles on Housing and Property\nRestitution for Refugees and Displaced Persons, and\nguidance on evictions. <sup>59</sup>\n\n\nCOMPENSATION AND RESTITUTION\n\n\n74. Experience from DIDR, in particular, indicates\nthat cash-based compensation schemes alone have\nrarely prevented impoverishment risks and impacts.\nIn-kind compensation, however, entails less risk\nand such compensation remains one indispensable\nmeans of making reparations for what has been lost.\nCertain forms of compensation schemes can fail relocated communities, thereby compounding vulnerability. For example, when compensation is provided\n\n\n\nin the form of ‘cash for land’, safeguards need to be\nput in place to avoid the sudden and concomitant\ninfusion of money into the market from pricing out\nrelocated communities. Compensation", "source": "reliefweb", "subset": "annotate_aivin_part2", "spans": [{"key": "reliefweb:000184:23:0:0", "start": 553, "end": 562, "surface": "cadastres", "probe_tag": "confusion", "probe_score": 0.6241, "luna_label": 0, "luna_reason": "Names cadastral records without showing their data informing analysis or decisions."}, {"key": "reliefweb:000184:23:0:1", "start": 567, "end": 588, "surface": "land title registries", "probe_tag": "confusion", "probe_score": 0.1002, "luna_label": 0, "luna_reason": "Registry is mentioned only as potentially unreliable, without showing data use."}]}, {"key": "aivin2-170", "text": "**_2._** **_Southern and Central Somalia_**\n\n\nOn account of the general unavailability of protection from the State in southern and central Somalia\ndue to the fact that the State has lost effective control over large parts of territory, the situation in\nsouthern and central Somalia does not meet the “relevance” test for the application of the IFA/IRA\nconcept. Furthermore, the customary law systems cannot be considered as sources of effective and\ndurable protection <sup>262</sup> [^262: Ibid, paras. 16-17.] due to their fragmented nature, the recent breakdown of traditional clan\nprotection mechanisms, bias towards majority clans and the contradictions between customary law\nand international human rights law, particularly in relation to the rights of women.\n\n\nIn the absence of a risk of persecution or other serious harm upon relocation, it must also be\n“reasonable” for a claimant to relocate. Such an assessment must take into account the elements of\nsafety and security, respect for human rights and options for economic survival in order to evaluate if\nthe individual would be able to live a relatively normal life without undue hardship given his or her\nsituation. <sup>263</sup> [^263: Ibid, p. 3.]\n\n\nIn light of the risks to safety and security, ongoing armed conflict and the shifting armed fronts and\nongoing widespread human rights violations, it cannot be considered reasonable for any Somali,\nregardless of whether the individual originates from southern and central Somalia, Somaliland or\nPuntland, to relocate within or to southern and central Somalia.\n\n\nAccess to land, water, services and security in southern and central Somalia is generally defined by\nclan membership. In such situations, it would not be reasonable to expect someone to take up\nresidence in an area or community where persons with a different clan background are settled, or\nwhere they would otherwise be considered aliens. There is evidence from the IDP settlements in\nurban areas across Somalia, including Puntland and Somaliland, of daily", "source": "reliefweb", "subset": "annotate_aivin_part2", "spans": [{"key": "reliefweb:001069:37:0:0", "start": 1945, "end": 1960, "surface": "IDP settlements", "probe_tag": "confusion", "probe_score": 0.4274, "luna_label": 0, "luna_reason": "Names a settlement population, not an eligible data resource."}]}, {"key": "aivin2-171", "text": " assist persons in need, \nprimarily for health, food, funerals, education, electricity or other related needs2. In Kheshgi RV, the \n                                                             \n2 Examples of such practice provided from participants living in settlements in Chiltan Town Tehsil, Quetta district in Baluchistan \nand Rawalpindi and Attock districts in Punjab.", "source": "reliefweb", "subset": "annotate_aivin_part2", "spans": [{"key": "reliefweb:000337:6:2:0", "start": 115, "end": 125, "surface": "Kheshgi RV", "probe_tag": "confusion", "probe_score": 0.4705, "luna_label": 0, "luna_reason": "A geographic location, not a data source or data-use mention."}]}, {"key": "aivin2-172", "text": "in their community and very poor knowledge about GBV referral\nservices available (80%). Various forms of GBV, including sexual\nviolence, were reported to be a risk. There were reportedly limited\nconsultations with women and girls on their safety and wellbeing\nneeds, which contribute to rising GBV risks if the humanitarian\nresponse does not meet their specific needs or provide them with\nadequate/safe access to services.\n\nWhen asked if there are any specific concerns affecting women / girls,\nrespondents replied one of the most concerning issues is the lack of\nsafe place in community (62%), and therefore, the spread of\nharassment and sexual violence/abuse in their home (39%) and risk\nof attack when travelling outside home (51%).\n\n\n**Capacities to address the protection risk**\n\n\nThe pre-existing GBV issues in flood affected have several\ncontributing factors including socio-cultural barriers, economic\ndependency, lack of information, accessibility as well as lack of\nexistence of support systems such as health care and psycho-social\nsupport services. Although, the GBV prevalence statistics do not\nrepresent the full extent of cases, the risk of gender-based violence\nis exacerbated in times of emergencies as the public services become\noverstretched, gender norms that regulate social behavior are\nweakened, separation of family members, lack of opportunities for\nmeaningful participation and decision making for women, including\nin accessing relief services and goods are among few of several\ncontributing factors. The worsening of the situation is further\nhighlighted in the results of the MSRNAs. Women with disabilities\nhave been found to form one of the most socially excluded group in\nany displaced or conflict-affected community. They have difficulty\naccessing humanitarian assistance programs, due to a variety of\nsocietal, attitudinal, environmental and communication barriers, and\nare at greater risk of violence than their nondisabled peers. Women\nand girls with disabilities are ‘particularly vulnerable to\n\n\n\ndiscrimination, exploitation and violence, including GBV, but they\nhave difficulty accessing", "source": "reliefweb", "subset": "annotate_aivin_part2", "spans": [{"key": "reliefweb:001618:7:0:0", "start": 1075, "end": 1100, "surface": "GBV prevalence statistics", "probe_tag": "keep", "probe_score": 0.9184, "luna_label": 1, "luna_reason": "Existing prevalence statistics are cited as incomplete evidence of GBV extent."}, {"key": "reliefweb:001618:7:0:1", "start": 1603, "end": 1609, "surface": "MSRNAs", "probe_tag": "confusion", "probe_score": 0.78, "luna_label": 1, "luna_reason": "Results of named MSRNs assessments support the reported worsening GBV situation."}]}, {"key": "aivin2-173", "text": " Iraqi and\nAfghan participation in post-conflict elections. There is also evidence that Liberian\nreluctance to participate in the 1997 peace-building election was in part because a\ntemporary return would have been required not only in order to vote, but also in\norder to register.\n\n\n184. UNHCR could play a role in encouraging countries to adopt same-day\nregistration and voting processes by facilitating the compilation of preliminary voter\nlists through use of refugee documentation. For example, in the 2004 Afghan\nelections, the government-issued Amayesh refugee card could be used to prove\nidentity and eligibility to vote, so that a skeleton electoral register was created on\nelection day itself using the Amayesh card to validate refugees‟ identity (Thompson\n2007).\n\n\n185. Although the Amayesh registration cards later proved insufficient and other\nforms of identification were also accepted, the fact remains that registration\ndocuments held by UNHCR may prove a useful starting point from which to either\nvalidate a self-initiated registration initiative, or on which to base the compilation of\na state-initiated register, which may in turn help to reduce the need for advance\nregistration. However, same-day registration often requires that polling take place\nover several days and may increase security risks as a result.\n\n\n186. The lack of an electoral register prior to voting may also lead to polling stations\nbeing located in inaccessible areas or inadequately staffed (Lacy 2004: 20).\nResponding to this last challenge may be less difficult when addressing camp-based\nrefugee populations, however, as UNHCR is likely to already hold demographic data\n\n33", "source": "reliefweb", "subset": "annotate_aivin_part2", "spans": [{"key": "reliefweb:000168:35:1:0", "start": 1649, "end": 1665, "surface": "demographic data", "probe_tag": "confusion", "probe_score": 0.4274, "luna_label": 0, "luna_reason": "States likely data availability without showing analysis, targeting, or substantive use."}]}, {"key": "aivin2-174", "text": " access to education.|Child Protection AoR|\n|**Health**|Ensure health and volunteer staff working at the<br>different GBV entry points within health centres<br>(maternity,<br>_SAAJ-Serviços_<br>_Amigos_<br>_dos_<br>_Adolescentes e Jovens_, _UATs –Unidades de_<br>_Aconselhamento e Testagem_) are trained to be able<br>to provide survivor-centred care and safe referrals.<br> <br>Ensure that complete post-rape kits are available at<br>health centre level, including pregnancy tests,<br>emergency contraception, PEP, STD treatment,<br>Hepatitis B vaccine and that safe abortion services<br>are available and providers trained in clinical<br>management of rape. Make different family planning<br>methods are available at health centre level,<br>including condoms. Ensure that all services are<br>provided for free and complaints mechanisms are in<br>place.<br> <br>Ensure GBV screening is always conducted in safe<br>and confidential manners, and a safe and<br>confidential space to attend GBV survivors is<br>available at health centre level.<br> <br>Ensure data on GBV cases are collected in<br>confidential manner and safely stored and MISAU<br>case intake forms are available.|Health Cluster, GBV AoR|\n|**WASH**|Seek ways of increasing safe access to water at<br>household<br>and<br>neighbourhood<br>level,<br>monitor<br>protection risks for women and girls in the sale of<", "source": "reliefweb", "subset": "annotate_aivin_part2", "spans": [{"key": "reliefweb:000736:10:1:0", "start": 1057, "end": 1074, "surface": "data on GBV cases", "probe_tag": "drop", "probe_score": 0.0308, "luna_label": 0, "luna_reason": "The sentence directs future collection and storage of GBV case data."}]}, {"key": "aivin2-175", "text": " poverty, labor markets,\nand other welfare indicators at the country level. Including\nthem can contribute to filling socioeconomic data gaps on\ninternational displacement, while providing crucial inputs\n\n\n\nto inform targeted responses, policies, and programs for refugees and host communities. Particularly, increasing panel\ndata across refugee and host communities would provide\na rich learning to assess how welfare and social cohesion\ntrends change over time. Investigating this hypothesis and\nothers underlines our earlier point, the need for panel data\nto monitor changes of the same household over times of war\nand forced displacement.\n\n\n**74. Socioeconomic data with a focus on the displacement**\n**trajectory can further enhance the design of solutions**\n**for displacement.** Socioeconomic surveys are essential to\nunderstand the current living conditions of households to\ninform policies, for example, on labor markets and safety\nnets as well as health and education. However, they usually\ndo not consider the specific displacement trajectory of refugees who are affected by traumatic episodes causing them to\ncross international borders. It is critical to understand refugees’ vulnerabilities and needs in order to find solutions. It is\nrecommended that a forcibly displaced module be developed\nby development organizations in collaboration with national\nstatistics offices, to serve as an input for existing surveys,\nsuch as national surveys that measure poverty, Living Standards Measurement Surveys, and beyond. A standardized\nforced displacement module that measures the vulnerabilities faced by refugees and other forcibly displaced persons\nis essential to complete the picture needed for informing\noptimal national policies and programming. A newly developed framework by the World Bank has been administered\nto displaced populations in Ethiopia, Nigeria, Somalia, South\nSudan, and Sudan—and should be considered for future data\ncollection of refugees in Kenya and other countries in the\nregion. <sup>93</sup>\n\n\n93 \u0007Pape and Sharma. 2019. Informing Durable Solutions for Internal\nDisplacement in Nigeria, Somalia, South Sudan, and Sudan.\n\n\n33", "source": "reliefweb", "subset": "annotate_aivin_part2", "spans": [{"key": "sample:reliefweb:000641:45:1:0", "start": 319, "end": 329, "surface": "panel\ndata", "probe_tag": "drop", "probe_score": 0.0, "luna_label": 0, "luna_reason": null}, {"key": "sample:reliefweb:000641:45:1:1", "start": 650, "end": 668, "surface": "Socioeconomic data", "probe_tag": "confusion", "probe_score": 0.0908, "luna_label": 0, "luna_reason": null}, {"key": "sample:reliefweb:000641:45:1:2", "start": 785, "end": 806, "surface": "Socioeconomic surveys", "probe_tag": "confusion", "probe_score": 0.3435, "luna_label": 0, "luna_reason": null}, {"key": "sample:reliefweb:000641:45:1:3", "start": 1437, "end": 1474, "surface": "national surveys that measure poverty", "probe_tag": "confusion", "probe_score": 0.2719, "luna_label": 0, "luna_reason": "Names surveys as future module inputs without citing their existing data or findings."}, {"key": "sample:reliefweb:000641:45:1:4", "start": 1476, "end": 1512, "surface": "Living Standards Measurement Surveys", "probe_tag": "confusion", "probe_score": 0.0687, "luna_label": 0, "luna_reason": null}]}, {"key": "aivin2-176", "text": " in the same ways; beer and juice were luxury items with sunk costs,\nwhile the other items satisfied basic needs: _“Beer and juice is not something to be_\n_taken every day, you can just drink it when you want. Maybe every one or two_\n_weeks”_ (Interview 22, No053, July 29, 2014).\n\n|Table 1. Rank of Expenditure between Samples|Col2|\n|---|---|\n|**Rank of Item by Amount Spent (UGX), Refugee**<br>**Sample**|**Rank of Item by Amount Spent (UGX),**<br>**National Sample**|\n|1. Clothes, 5,600|1. Cloth, 4,333|\n|2. Rice, 4,200|2. Clothes, 3,833|\n|3. Cloth, 4,936|3. Rice, 3,800|\n|4. Shoes, 3,573|4. Shoes, 1,967|\n|5. Cooking Oil, 3,200|5. Cooking Oil, 1,433|\n\n\n\nThe rank of items shown in Table 1 is similar in both groups. Rice, clothes\nand cloth are the top three, while shoes and oil are at the bottom. Refugees spent\nmore on clothes and rice than education. Refugees also spent more on clothes, rice,\ncooking oil and shoes than nationals. Qualitative data will be used to uncover the\nsignificance of these differences in the next sub-section.\n\n\n12 It should be noted that schoolbooks were selected as a proxy for more general educational\ninvestments based on the free school fees and uniforms supplied by the UNHCR.\n\n\n16", "source": "reliefweb", "subset": "annotate_aivin_part2", "spans": [{"key": "sample:reliefweb:001583:17:1:0", "start": 939, "end": 955, "surface": "Qualitative data", "probe_tag": "drop", "probe_score": 0.0083, "luna_label": 0, "luna_reason": null}]}, {"key": "aivin2-177", "text": "# **Shelter Mapping**\n\n**REACH led master shelter listing**\n\n\n**Which actors are visiting communal shelters?**\n**Can we consolidate shelter information and track shelter rehabilitations?**\n\n\n**Winterization Workshop, October 2022**", "source": "reliefweb", "subset": "annotate_aivin_part2", "spans": [{"key": "reliefweb:001548:38:0:0", "start": 25, "end": 57, "surface": "REACH led master shelter listing", "probe_tag": "drop", "probe_score": 0.0153, "luna_label": 0, "luna_reason": "Names a shelter listing without showing its data being used."}]}, {"key": "aivin2-178", "text": " affected people\ntotals.\n\n\nAt a global level, the most thorough and most cited database of disaster losses that tracks these variables is EMDAT. At a national level, the expanding series of disaster\nloss databases following the DesInventar methodology\nprovide disaggregated loss figures per jurisdiction. Due\nto the fact that each DesInventar database is administered by each participating country, there are slight\nvariations in structure and more significant variations\nin coverage and low-end thresholds for inclusion. In the\npast this has made inter-country comparison difficult.\nIn 2015 IDMC is going to use the ISDR’s GAR data universe, which has been pre-screened to insure the highest\nlevel of inter-country comparison, thus largely removing this substantial limitation to previous DesInventar\ndatasets.\n\n\nIn all of these datasets, mortality data is of the highest\nquality, while homeless and affected population information can be somewhat less accurate, especially for\nsome particular types of hazard. Homeless data appears\nto be most accurately represented in earthquake events,\nand least well tracked in flood events. Storms and floods\nhave both the highest number of entries and total in\nterms of mortality and homelessness, which makes their\nindividual hazard analyses rather more robust due to\nthe larger sample sizes.\n\n\nLandslides, and smaller events in general, receive\nsubstantially less attention due to a combination of\ndifficulty in collecting data on so many events and\nproblems that can arise from a change in methodology.\nThese can include a lowering of thresholds for inclusion,\nthat would drastically increase the number of entries\nfor these types of events. For example, EM-DAT utilises\n\n\n\nDisaster-related displacement risk: Measuring the risk and addressing its drivers 39", "source": "reliefweb", "subset": "annotate_aivin_part2", "spans": [{"key": "sample:reliefweb:000972:36:2:0", "start": 331, "end": 351, "surface": "DesInventar database", "probe_tag": "drop", "probe_score": 0.0004, "luna_label": 1, "luna_reason": null}, {"key": "sample:reliefweb:000972:36:2:1", "start": 624, "end": 641, "surface": "GAR data universe", "probe_tag": "confusion", "probe_score": 0.1778, "luna_label": 0, "luna_reason": null}, {"key": "sample:reliefweb:000972:36:2:2", "start": 840, "end": 854, "surface": "mortality data", "probe_tag": "confusion", "probe_score": 0.1965, "luna_label": 1, "luna_reason": null}, {"key": "sample:reliefweb:000972:36:2:3", "start": 1012, "end": 1025, "surface": "Homeless data", "probe_tag": "confusion", "probe_score": 0.0574, "luna_label": 1, "luna_reason": null}, {"key": "sample:reliefweb:000972:36:2:4", "start": 1698, "end": 1704, "surface": "EM-DAT", "probe_tag": "drop", "probe_score": 0.0, "luna_label": 0, "luna_reason": null}]}, {"key": "aivin2-179", "text": "# **COUNTRY REPORTS**\n\n### DISPLACED & DISCONNECTED", "source": "reliefweb", "subset": "annotate_aivin_part2", "spans": [{"key": "reliefweb:001415:0:0:0", "start": 4, "end": 19, "surface": "COUNTRY REPORTS", "probe_tag": "drop", "probe_score": 0.0165, "luna_label": 0, "luna_reason": "Standalone report heading, not an existing data resource or data use."}]}, {"key": "aivin2-180", "text": "[Etim, A. (2023). Tunisian National Guard arrests major human smuggler linked to migrant deaths. Africa](https://africanewswatch.com/2023/05/tunisian-national-guard-arrests-major-human-smuggler-linked-to-migrant-deaths/)\nNews Watch, 27 May.\n\n\nEuropean Union Agency for Asylum (n.d.). [Key first instance indicators by country of origin, 2023.](https://public.flourish.studio/visualisation/14637792/)\n(accessed 14 February 2024).\n\n\n[European Union/International Centre for Migration Policy Development (ICMPD) (n.d.). The Khartoum](https://www.khartoumprocess.net/)\n[Process.](https://www.khartoumprocess.net/)\n\n\nEurostat (n.d.). [First instance decisions on applications by type of decision, citizenship, age and sex –](https://ec.europa.eu/eurostat/databrowser/view/migr_asydcfstq__custom_9874408/default/table?lang=en)\n[quarterly data (accessed 17 January 2024).](https://ec.europa.eu/eurostat/databrowser/view/migr_asydcfstq__custom_9874408/default/table?lang=en)\n\n\nFereday, A. (2022a). _[Niger: Routes Shift amid Post-COVID Increase in Human Smuggling](https://globalinitiative.net/wp-content/uploads/2022/06/Human-smuggling-and-trafficking-ecosystems-NIGER.pdf)_ . Human Smuggling\nand", "source": "reliefweb", "subset": "annotate_aivin_part2", "spans": [{"key": "reliefweb:001558:60:0:0", "start": 822, "end": 836, "surface": "quarterly data", "probe_tag": "drop", "probe_score": 0.0087, "luna_label": 0, "luna_reason": "Reference-list qualifier, not an independently used data resource."}]}, {"key": "aivin2-181", "text": "**Methodology A:** Uses the Specific Needs Codes (SNC) in _proGres_ to estimate the number of people in need of\n\nresettlement. This methodology requires Offices to create a report from _proGres_ showing the number\nof persons who have specific needs that correspond to a likelihood of resettlement eligibility. The\nguidelines further provide breakdown of SNC into high/medium or variable/low resettlement likelihood.\n\n\n**Methodology B:** \u0007Uses community-based approaches, participatory assessments, and the HRIT to inform resettlement\n\nneeds of people of concern to UNHCR as well as to key partners. The HRIT links participatory\nassessments and individual assessment methodologies to identify refugees at risk.\n\n\n**Methodology C:** \u0007Uses “best estimates” based upon limited available data. This methodology requires Country Offices to\n\nprovide a “best estimate” of the projected resettlement needs by using relevant internal and external\ndata.\n\n\nThe most thorough and reliable approach combines all of the above methodologies with an emphasis on methodologies\nA and B. Methodology C alone is normally only used when Offices do not have access to _proGres_ data and are unable to\nconduct participatory assessments or a representative sample survey of the refugee population. For the 2020 planning\ncycle, the vast majority of Country Offices combined various methodologies to ensure a comprehensive and multi-year\napproach to this exercise.\n\n\n\n60", "source": "reliefweb", "subset": "annotate_aivin_part2", "spans": [{"key": "sample:reliefweb:000739:60:0:0", "start": 915, "end": 941, "surface": "internal and external\ndata", "probe_tag": "confusion", "probe_score": 0.5908, "luna_label": 1, "luna_reason": null}, {"key": "sample:reliefweb:000739:60:0:1", "start": 1145, "end": 1159, "surface": "_proGres_ data", "probe_tag": "confusion", "probe_score": 0.4676, "luna_label": 1, "luna_reason": null}, {"key": "sample:reliefweb:000739:60:0:2", "start": 1217, "end": 1271, "surface": "representative sample survey of the refugee population", "probe_tag": "drop", "probe_score": 0.0247, "luna_label": 0, "luna_reason": null}]}, {"key": "aivin2-182", "text": "#### **Services offered and taken up**\n\nRefugees primarily use their mobile wallets to\nobtain cash to pay monthly bills for rent and\nfood. Incentives are often given to withdraw\nall their money in a single transaction since\nthe initial cashing out each month is often\nexempt from fees. One report concluded:\n\n“ _Current humanitarian processes incentivise_\n_recipients to withdraw the full transfer_\n_amount. However, this undermines potential_\n_savings and trust in digital services by_\n_reinforcing the belief that only hard cash, as_\n_opposed to an electronic balance, has_\n_permanent value_ .” <sup>45</sup> [^45: _Humanitarian CT and FI lessons from Jordan, April 2020_]\n\nHowever, WFP has recently decided not to\ncover any withdrawal fees when transferring\nassistance to mobile wallets, with the\nobjective of incentivising digital transactions.\nThere are a range of other services\npotentially available through mobile wallets\nincluding:\n\n\n  - Person to person payments\n\n  - International payments and\nremittances\n\n  - Payment of bills (including phone topup)\n\n  - Savings and credit\n\n  - Insurance\n\n\n\nOne hypothesis is that refugees will become\nmore confident in the use of mobile wallets\nover time and expand the range of services\nthat they access. One potential area for\nexpansion is the payment of bills. The use of\nmobile services reduces the need and\ntransport costs for attending offices to pay\nbills. The Government significantly expanded\nthe use of eFAWATEERcom by government\ninstitutions from 21 in 2017 to 48 by the end\nof 2020. This is reflected by growth in this\nplatform but it still has very limited use by\nrefugees.\n\nAlthough non-Jordanians\nlag Jordanians in most\nmeasures of digital financial\nservices, this is not the\ncase with remittances.\n2017 data suggested that\n31.4% of non-Jordanians\nsent or received\nremittances through formal\nchannels in the previous\nyear, well above the rate of\n19.9% for Jordanians. <sup>46</sup> At\npresent mobile wallet\nproviders are", "source": "reliefweb", "subset": "annotate_aivin_part2", "spans": [{"key": "sample:reliefweb:001027:26:0:0", "start": 1762, "end": 1771, "surface": "2017 data", "probe_tag": "drop", "probe_score": 0.0001, "luna_label": 0, "luna_reason": "Bare date-only data qualifier lacks an identified source or producer."}]}, {"key": "aivin2-183", "text": " such as street lighting and water pumping would enable better\nservice provision, and could drive increased rural energy access among host populations\nacross this area of the Sahel.\n\n\n**•** In all three countries, transport-fuel savings and air-quality improvements through fleet\nsharing and fuel-management practices would make sense. For example, a fleet-sharing\npilot scheme led by UNICEF in five countries demonstrated that the vehicle fleets of\nagencies were 10–15 per cent too big, and that the initial investment could be recouped\nthrough the scheme within one year.\n\n\n**•** Opportunities to do things differently are routinely missed because decision-makers lack\nthe requisite data on energy use, costs and alternatives. We make several recommendations\nfor how humanitarian agencies, donors and host governments can open up to innovation in\nenergy use and seize its benefits.\n\n\n**•** As part of their commitment to ‘do no harm’, humanitarian agencies should commit to\nreducing their emissions footprint in host countries, and set targets for phasing out the\nuse of diesel for electricity generation. They can begin by following a ‘3M’ strategy:\n\n  - **–** **Measuring**  - collecting energy and emissions data.\n\n  - **–** **Monitoring**  - reporting on these data and identifying ‘low-hanging fruit’ where\n\nimprovements would pay back an initial investment in a short period.\n\n  - **–** **Motivating**  - introducing emissions reduction targets as key performance indicators\n\nand encouraging entrepreneurial activities by country teams. This could include\nencouraging the development of partnerships that would allow country teams to contract\nfor renewable energy services, or that would facilitate cooperation with other agencies\non fleet management and logistics efficiency.\n\n\n5   movingenergy.earth", "source": "reliefweb", "subset": "annotate_aivin_part2", "spans": [{"key": "reliefweb:000796:5:1:0", "start": 1192, "end": 1217, "surface": "energy and emissions data", "probe_tag": "drop", "probe_score": 0.0368, "luna_label": 0, "luna_reason": "The phrase describes collecting data as a planned measurement activity."}]}, {"key": "aivin2-184", "text": "- **UNHCR Italy (Rome):** Some ad hoc initiatives\npromoted under the two partnerships, an online\nconsultation portal and focus groups discussions but\nnot with this specific focus on info/communication. <sup>6</sup>\n\n\n     - **UNHCR Sudan:** In the 2019 Multi-Functional Team\nParticipatory Assessment, CwC has been chosen as a\nthematic area. As part of this, a CwC survey is being\nadministered to capture refugee information needs\nand preferences.\n\n\n     - **UNHCR Sudan (Kassala):** Communication with\nrefugees was a mandatory question/area of attention\nin the recently concluded participatory assessment\n(November 2019).\n\n\n     - **UNHCR TRS:** Preparatory research was conducted\nwith the aim of developing a tailored communication\nstrategy for TRS. The survey fed into the various\ncomponents of the project such as: demographic,\ngeographical scope of the campaign, communication\ntools appropriate for each community,\ncommunication channels of the target audience, etc.\n\n\nAnother important source of information on media use\nby refugees is anecdotal evidence obtained through\nface-to-face contacts in various forms such as home\nvisits, visits to community and reception centres, and\nexchanges.\n\n\n6 [Communicating with Communities In Lebanon fact sheet, December 2018.](https://www.unhcr.org/lb/wp-content/uploads/sites/16/2019/01/Communication-with-Communities-Fact-Sheet-December-2018.pdf)\n\n\n16 **WE DIDN’T THINK IT WOULD HAPPEN TO US**\n\n\n\nAt least four operations deploy **outreach volunteers** as\npart of their CwC strategy.\n\n\n- **UNHCR Chad** uses 100 volunteers to collect and\nanalyse data on persons on the move but also to\ndisseminate information. They refer persons in need\nof protection to the relevant partners.\n\n\n- *", "source": "reliefweb", "subset": "annotate_aivin_part2", "spans": [{"key": "sample:reliefweb:001467:15:0:0", "start": 360, "end": 370, "surface": "CwC survey", "probe_tag": "drop", "probe_score": 0.0, "luna_label": 0, "luna_reason": null}, {"key": "sample:reliefweb:001467:15:0:1", "start": 1591, "end": 1618, "surface": "data on persons on the move", "probe_tag": "drop", "probe_score": 0.0236, "luna_label": 0, "luna_reason": null}]}, {"key": "aivin2-185", "text": ". car(s)<br>7. other<br>8. prefer not to answer<br>9. Don’t own||\n|Housing, Land and Property||**K3**|K3_1 Do you wish to participate in Focus Group<br>Discussions related to the study in about two<br>months?|1. Yes<br>2. No||\n|Housing, Land and Property||**K3**|K3_2 Phone number?|||\n|End||**L1**|L Register GPS coordinates|||\n\n\n80", "source": "reliefweb", "subset": "annotate_aivin_part2", "spans": [{"key": "reliefweb:000440:79:4:0", "start": 309, "end": 324, "surface": "GPS coordinates", "probe_tag": "drop", "probe_score": 0.0269, "luna_label": 0, "luna_reason": "Survey form item records coordinates, indicating planned data collection rather than existing data use."}]}, {"key": "aivin2-186", "text": "for example: Gassner et al., 2008 <sup>1</sup> [^1: Gassner, K., A. Popov, and N. Pushak. 2008a. “Does the private sector deliver on its promises? Evidence from a\nglobal study in water and electricity”. _Gridlines 44512_ . PPIAF, The World Bank, Washington D.C.] ; Nagayama, 2010 <sup>2</sup> [^2: Nagayama, H. 2010. “Impacts on investments, and transmission/distribution loss through power sector reforms”.\n_Energy Policy_, 38(7), 3453‐3467.] ; Erdogdu, 2014 <sup>3</sup> [^3: Erdogdu, E. 2014. “Investment, security of supply and sustainability in the aftermath of three decades of power\nsector reform”. _Renewable and Sustainable Energy Reviews_, 31, 1‐8.] ; Jamasb et al., 2014 <sup>4</sup> [^4: Jamasb, T., R. Nepal, G Timilsina, and M. Toman. 2014. Energy Sector Reform, Economic Efficiency and Poverty\nReduction, Discussion Papers Series 529, School of Economics, University of Queensland, Australia.] ; Urpelainen\nand Yang, 2017. <sup>5</sup> [^5: Urpelainen, J., & Yang, J. 2017. Policy Reform and the Problem of Private Investment: Evidence from the Power\nSector. _Journal of Policy Analysis and Management_, 36(1), 38‐64.\n_6 http://rise.esmap.org/_\n_7 https://ppi.worldbank.org/_] Moreover, an evaluation of the impact of reform would not have been feasible to\nimplement in any meaningful depth given the scope of the data set covering 88 countries over a 25‐year\nperiod. Rather, the primary contribution of this paper is to provide a much more detailed characterization\nof", "source": "general_prwp", "subset": "annotate_aivin_part2", "spans": [{"key": "prwp:007194:6:0:0", "start": 1329, "end": 1359, "surface": "data set covering 88 countries", "probe_tag": "confusion", "probe_score": 0.4274, "luna_label": 0, "luna_reason": "Dataset is mentioned as scope context, not used for an attributed finding or analysis."}]}, {"key": "aivin2-187", "text": "using the Government of Jordan’s Household Income and Expenditure Survey (HIES) 2017/18.\n\n\nThe sampling frame for the refugee sample was\ndrawn from the ProGres registration database\nadministered by UNHCR <sup>1</sup> . This sample is stratified by rural/urban location and camp/non-camp\nlocation in four groups: Amman, other governorates-urban, other governorates-rural, camps. An\nex-post weight adjustment was also applied to the\nrefugee population to better reflect this population’s demographics using the ProGres database.\n\n\nThe Socio-Economic Situation of Refugees in\nJordan is a quarterly mobile phone panel survey conducted in 2022 with the main purpose to\nmonitor changes in vulnerability levels among\nrefugees over time. The questionnaire covered\ntopics about refugees’ households’ economic situation, food security, shelter, water, sanitation,\nand hygiene (WASH), and health. The survey\nwas centered on collecting information repeatedly from the same households (panel data) and it\nwas completed in four Rounds (Q1, Q2, Q3 and\nQ4 2022). <sup>2</sup> For Round 1 and Round 2, the survey covered Syrian and non-Syrian households\nresiding outside of camps across all 12 governorates in Jordan, <sup>3</sup> while in Round 3 and 4, the\n\n\n1. ProGres (Profile Global Registration System) is an\nregistration and case management tool developed by\nUNHCR which provides a common source of information\nabout individuals and it is used by different work units to\nfacilitate protection of persons of concern to the organization. ProGres is the main repository in UNHCR for storing\nindividuals’ data.\n2. In each round, the data were collected over the phone\nthe last two weeks of the last month of each quarter. The\nonly exception was the data collection for Q4 2022, which it\ntook place from 5/", "source": "reliefweb", "subset": "annotate_aivin_part2", "spans": [{"key": "reliefweb:001535:8:0:4", "start": 973, "end": 983, "surface": "panel data", "probe_tag": "confusion", "probe_score": 0.4694, "luna_label": 0, "luna_reason": "The sentence describes collecting panel data through the survey."}]}, {"key": "aivin2-188", "text": "\n|Frequency<br>Semi-annually|Frequency<br>Semi-annually|\n|Data Source<br>Implementation partners|Data Source<br>Implementation partners|\n|Methodology for Data<br>Collection <br>Grant disbursement records|Methodology for Data<br>Collection <br>Grant disbursement records|\n|Responsibility for Data<br>Collection <br>Data aggregated by PIU|Responsibility for Data<br>Collection <br>Data aggregated by PIU|\n|**Number of MSMEs owned by refugees supported with technology grants (Number) **|**Number of MSMEs owned by refugees supported with technology grants (Number) **|\n|Description <br>Number of refugee-owned MSMEs who applied for and received full grant amount (total number of MSMEs that received<br>in-kind grants and cash funding through the project).|Description <br>Number of refugee-owned MSMEs who applied for and received full grant amount (total number of MSMEs that received<br>in-kind grants and cash funding through the project).|\n|Frequency<br>Semi-annually|Frequency<br>Semi-annually|\n|Data Source<br>Implementation partners|Data Source<br>Implementation partners|\n|Methodology for Data<br>Collection <br>Grant disbursement records|Methodology for Data<br>Collection <br>Grant disbursement records|\n|Responsibility for Data<br>Collection <br>Data aggregated by PIU|Responsibility for Data<br>Collection <br>Data aggregated by PIU|\n|**Additional annual revenue generated by supported MSMEs (Percentage) **|**Additional annual revenue generated by supported MSMEs (Percentage) **|\n|Description<br>Increase in", "source": "refugee_pads", "subset": "annotate_aivin_part2", "spans": [{"key": "refugee_pads:000004:41:2:0", "start": 177, "end": 203, "surface": "Grant disbursement records", "probe_tag": "confusion", "probe_score": 0.2287, "luna_label": 0, "luna_reason": "Routine project grant records used for monitoring, not substantive data analysis."}, {"key": "refugee_pads:000004:41:2:2", "start": 314, "end": 336, "surface": "Data aggregated by PIU", "probe_tag": "confusion", "probe_score": 0.796, "luna_label": 0, "luna_reason": "Standalone project monitoring table entry, not an independently used data resource."}]}, {"key": "aivin2-189", "text": " participating on<br>each cultural<br>production work<br>|Project Management<br>Team/UN-Habitat<br>|\n|Of which, are female|Number of females<br>including cultural<br>practitioners, individuals in<br>cultural entities and<br>additional workers involved<br>in the implementation of<br>the cultural productions.|Quarterly<br>|Progress,<br>Monitoring<br>and<br>Evaluation<br>Reports. Esti<br>mates by<br>Project<br>Management<br>Team.<br>|Number of women will<br>be determined by<br>disaggregating the<br>beneficiary data of the<br>progress reports<br> <br>|Project Management<br>Team/UN-Habitat<br>|\n\n\nPage 35 of 66", "source": "jdc_operational", "subset": "annotate_aivin_part2", "spans": [{"key": "sample:jdc_operational:000012:40:1:0", "start": 501, "end": 517, "surface": "beneficiary data", "probe_tag": "confusion", "probe_score": 0.0507, "luna_label": 0, "luna_reason": null}]}, {"key": "aivin2-190", "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_aivin_part2", "spans": [{"key": "fcv_pads_east_africa:010463:51:0:0", "start": 1720, "end": 1736, "surface": "multi-level data", "probe_tag": "confusion", "probe_score": 0.4274, "luna_label": 0, "luna_reason": "Planned future reporting, not use of existing data."}]}, {"key": "aivin2-191", "text": " sources—for example, certain institutional changes that are likely to be\nintroduced at a certain point in the business cycle may be associated with outcomes that, in fact,\ncould be due to the cyclical factors themselves. <sup>5</sup> Moreover, while single-country longitudinal\nstudies may be useful for studying the impacts of some institutions that experience discrete\nchanges (e.g., minimum wages), they are less suited for other institutions (e.g., unions) that\nevolve more gradually over time.\n\n\nInteractions add to the challenge of identifying the effects of a specific law or policy. As\nEichhorst, Feil, and Braun (2008) point out, it has become evident that two types of interactions\nare important to consider. One concerns interactions between different labor market institutions,\nwith the impact of one being affected by another. <sup>6</sup> More generally, countries typically have\n“bundles” of complementary institutions (e.g., the lightly regulated Anglo-Saxon model, the\nNorthern European flexicurity model, etc.) which make it difficult to isolate the effect of\n\n\n4 In the first place, the institutions themselves are not exogenous variables but reflect the societies in which they\nexist. This includes, for example, the country’s legal tradition (Botero _et al._ 2004); the strength of its family ties\n(Alesina _et al._ 2010); and civic attitudes (Algan and Cahuc 2006).\n5 Model specifications can take into account this type of problem but require panel data series that are long enough\nto determine “normal” cyclical trends.\n6 One example of this is the relationship between social insurance contributions and minimum wages. How much\nthe contributions affect employment will depend in part on who actually pays which in turn is affected by the\nminimum wage which limits the potential for shifting the costs to low-wage employees.", "source": "general_prwp", "subset": "annotate_aivin_part2", "spans": [{"key": "prwp:005436:6:1:0", "start": 1467, "end": 1484, "surface": "panel data series", "probe_tag": "confusion", "probe_score": 0.2292, "luna_label": 0, "luna_reason": "Describes data required for model specifications, not existing data actually used."}]}, {"key": "aivin2-192", "text": " En Perú, no\nexiste correlación. El estado civil\nde los venezolanos en Perú está\ncorrelacionado con los salarios: los\nvenezolanos casados ganan en\npromedio un 2.5 por ciento más que\nlos solteros, con todos los demás\nfactores constantes. Si se tienen\nen cuenta otros factores (como la\neducación, la experiencia, el estado\ncivil y el tamaño del hogar), los salarios\nde las mujeres venezolanas son un\n28 por ciento inferiores a los de los\nhombres venezolanos en Colombia y\nun 27 por ciento inferiores en Perú.\n\n\n\n**Variable**\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nFuentes: Elaboración propia a partir de las siguientes encuestas: Chile: Encuesta de Migración (Banco\nMundial, SERMIG y Centro UC 2022) y Encuesta Nacional de Empleo (INE 2022). Colombia: Pulso de la\nMigración (DANE 2022) y Gran Encuesta Integrada de Hogares (DANE 2021). Ecuador: Encuesta a Personas\nen Movilidad Humana y en Comunidades Receptoras en Ecuador (INEC 2019) y Encuestas Telefónicas de\nAlta Frecuencia ALC (Banco Mundial 2022). Perú: Encuesta dirigida a la población venezolana que reside\nen el país (INEI 2022) y Encuesta Nacional de Hogares (INEI 2021).\n\n\nNota: Errores estándar entre paréntesis. *** Estadísticamente significativo al nivel del 1 por ciento. **\nEstadísticamente significativo al nivel del 5 por ciento. * Estadísticamente significativo al nivel del 10 por\nciento.\n\n\n\nLa diferencia en las comunidades\nde a", "source": "reliefweb", "subset": "annotate_aivin_part2", "spans": [{"key": "reliefweb:001322:41:4:1", "start": 676, "end": 703, "surface": "Encuesta Nacional de Empleo", "probe_tag": "confusion", "probe_score": 0.868, "luna_label": 1, "luna_reason": "Named employment survey cited as a source for reported salary analysis."}]}, {"key": "aivin2-193", "text": "**The World Bank**\nNiger COVID-19 Emergency Response Projet (P173846)\n\n\ngroup workshops and community meetings; (ii) diversification of means of communication and rely more on social\nmedia and online channels. Where possible and appropriate, create dedicated online platforms and chatgroups\n(whatsapp) appropriate for the purpose, based on the type and category of stakeholders; and (iii) use of traditional\nchannels of communications (TV, newspaper, local radios, dedicated phone-lines, and mail) when stakeholders to do\nnot have access to online channels or do not use them frequently. These traditional channels, such as local radios\ncan also be highly effective in conveying relevant information to stakeholders and allow them to provide their\nfeedback and suggestions.\n\n**64. Large volumes of personal data, personally identifiable information and sensitive data are likely to be collected**\n**and used in connection with the management of the COVID-19 outbreak under circumstances where measures to**\n**ensure the legitimate, appropriate and proportionate use and processing of that data may not feature in national**\n**law or data governance regulations, or be routinely collected and managed in health information systems.** In order\nto guard against abuse of that data, the Project will incorporate best international practices for dealing with such\ndata in such circumstances. Such measures may include, by way of example, data minimization (collecting only data\nthat is necessary for the purpose); data accuracy (correct or erase data that are not necessary or are inaccurate), use\nlimitations (data are only used for legitimate and related purposes), data retention (retain data only for as long as\nthey are necessary), informing data subjects of use and processing of data, and allowing data subjects the opportunity\nto correct information about them, etc. In practical terms, operations will ensure that these principles apply through\nassessments of existing or development of new data governance mechanisms and data standards for emergency", "source": "refugee_pads", "subset": "annotate_aivin_part2", "spans": [{"key": "sample:refugee_pads:000152:28:0:0", "start": 798, "end": 811, "surface": "personal data", "probe_tag": "confusion", "probe_score": 0.1234, "luna_label": 0, "luna_reason": null}]}, {"key": "aivin2-194", "text": " **.** Various\nelements have been introduced into the design of the AF to strengthen participating MLGs impact on\npromoting local economic development (LED) and job creation. Local firms in the formal sector face\nconsiderable constraints in establishing and sustaining their businesses, limiting prospects for the creation\nof more and better jobs. For example, according to World Bank Enterprise Survey Data for Uganda (2013),\nthe main constraints include infrastructure deficits and access to land; regulatory barriers and corruption;\nand access to finance <sup>20</sup> [^20: Highlighted as the biggest obstacles by 33.4, 31.7 and 12.3 percent of firms in Uganda, respectively.\n21World Bank (2016). _Re-positioning Local Governments for Economic Growth_ . The role of Local Governments in Promoting Local\nEconomic Development in Uganda – focusing on Jinja Municipal LG, and Arua and Nwoya District LGs.] . LGs have a role in helping or hindering the alleviation of these constraints to support\nprivate sector development and, consequently, job creation. The recent study undertaken by the World\nBank/Ministry of Local Government (MoLG) on LED <sup>21</sup> highlighted that LGs are currently doing little in\nthis direction, with their main relationship with the private sector centering on tax collection and requests\nfor donations. The study outlined some of the constraints faced by the private sector which are within the\nmandate of LGs. These fell under the four broad categories of infrastructure deficits, regulatory barriers,\nabsence of enterprise support and institutional capacity gaps within LGs.\n\n23. **_In line with the technical assessment and recent studies on LED in Uganda, design elements_**\n**_have therefore been introduced to support and incentivize MLGs to alleviate some of the local constraints_**\n**_that the private sector faces_** **.** LGs need a better understanding of their local economic potentials and the\nconstraints that key sectors face, a closer dialogue with the private sector, and improved incentives and", "source": "jdc_operational", "subset": "annotate_aivin_part2", "spans": [{"key": "jdc_operational:000006:16:1:0", "start": 374, "end": 418, "surface": "World Bank Enterprise Survey Data for Uganda", "probe_tag": "confusion", "probe_score": 0.8979, "luna_label": 1, "luna_reason": "Enterprise survey data supports identified constraints facing Ugandan firms."}]}, {"key": "aivin2-195", "text": " that<br>FMA RFOs will use on a monthly basis to verify expenses.<br>• Quality Assurance Representatives should be sent to the<br>regions on a monthly basis to provide a second check on<br>reports collected before they are reported as monthly<br>expenses.|<br>• The FMA has increased the number of field officers as agreed<br>during the contract re-negotiation to enhance their logistical<br>capability. <br>• The PSIs’ training has now been enhanced to include the<br>procurement module. <br>• The FMA financial reports are now detailed to include<br>Beneficiaries with performance and/or accountability issues. <br>• Physical verification of reports received from FMA to ensure<br>quality assurance is undertaken regularly by the NACC<br>finance division.|\n\n\n\n47", "source": "fcv_pads_east_africa", "subset": "annotate_aivin_part2", "spans": [{"key": "fcv_pads_east_africa:012656:54:1:0", "start": 499, "end": 520, "surface": "FMA financial reports", "probe_tag": "confusion", "probe_score": 0.1506, "luna_label": 0, "luna_reason": "Routine financial reporting and accountability paperwork, not substantive data reuse."}]}, {"key": "aivin2-196", "text": "*|30|365|\n|**Vietnam**|90|30|\n\n\n_Source: Living Life data_\n\n\n\n\n\n15 According to Ghana’s Income Tax Act (Act 896), one currency point is equivalent to one Ghana cedi.\n\n\n\n18 | P a g e", "source": "general_prwp", "subset": "annotate_aivin_part2", "spans": [{"key": "prwp:007528:19:2:0", "start": 41, "end": 58, "surface": "Living Life data_", "probe_tag": "confusion", "probe_score": 0.5991, "luna_label": 1, "luna_reason": "Source line identifies Living Life data underlying the presented table figures."}]}, {"key": "aivin2-197", "text": ").\n\n\n  - There is no information available on accommodation for\nchildren with their families in reception facilities.\n\n\n- For Italy, the calculation is based on the estimated 7,272 UASC registered in reception\naccording to the Ministry of Labour and Social Policies.\n\n3\n\n\n\nGreece\n\n\n\n**37%** **52%** **10%**\n\n\n\nBulgaria **33%** **36%** **30%**\n\n\n_Source:_ _<u>Hellenic Police, EKKA, Bulgarian State Agency for Refugees</u>_\n\n\nThe majority of UASC who arrived in Italy, Greece and Bulgaria\nbetween January and June 2019 were between 15 and 17 years\nold (86% overall). Age disaggregated data on children arriving to\nSpain is not available.\n\n\nUnaccompanied and Separated Children – Age breakdown\n\n\n0 - 4 years 5 - 14 years 15 - 17 years\n\n\nGreece **1%** **16%** **83%**\n\n\nItaly **1%** **6%** **93%**\n\n\nBulgaria **16%** **84%**\n\n\nSex Breakdown of Children by Country of Arrival\n\n\nOverall, the proportion of boys among arrivals remains high\n\n- nearly two-thirds of children who arrived through various\nMediterranean routes in the first half of 2019 were boys. Yet,\nthe proportion of girls arriving to Greece in the same period was\nsignificant - 42% of all child arrivals. This is due to the fact that\nchildren arriving to Greece are primarily accompanied, and the\nproportion of girls among accompanied children is overall much\nhigher as compared to children who travel alone.\n\n\nBOYS GIRLS\n\nGreece **58%** **42%**\n\n\nSpain **93%** **7%**\n\n\nItaly* **94%** **6%**\n\n\nBulgaria **83%** **17%**\n\n\n_Source:_ _", "source": "reliefweb", "subset": "annotate_aivin_part2", "spans": [{"key": "sample:reliefweb:001302:2:2:0", "start": 566, "end": 588, "surface": "Age disaggregated data", "probe_tag": "confusion", "probe_score": 0.2833, "luna_label": 0, "luna_reason": null}]}, {"key": "aivin2-198", "text": "meet the needs of teachers and schools. The first component of this project will fully apply this\napproach in the planning and delivery of teacher training. The establishment of unit-based\nteaching practice teams within each teacher education institution to conceptualize, plan, and\noversee the implementation of a teaching practice policy has proven to be an effective strategy\nfor developing up-to-date thinking on how to address the challenges involved in the practical\npreparation of teachers.\n\n39. _Selection of schools and teachers._ The selected schools and teachers, and the preparation\nof both to host and support the development of student teachers, is critical to the success of\nteaching practices. Intensive capacity building needs to be provided for the participating trainers\nof teachers, if the demonstration of teaching techniques and mentoring of student teachers are to\nbe up to date and effective.\n\n40. _Availability of teaching resources._ Facilities and materials used during teacher\ndevelopment programs should be those currently available or soon to be supplied to schools. If\nstudent teachers master those skills and learn how to make effective use of available teaching\naids and facilities in the implementation of student-focused, activity-oriented learning, the\nlikelihood is that they will effectively utilize more sophisticated equipment such as computers\nand video equipment, if and when these become available in schools.\n\n41. _Evaluate programs in a systematic manner._ Very little is known of the impact of inservice teacher professional-development activities on student learning outcomes in developing\ncountries as well as in WBG. While many countries have data on initial teacher education, very\nfew follow-up by collecting data on changes in teaching practices as a result of in-service\nprofessional-development programs. Lack of data and systematic evaluation are hindering the\nunderstanding of which staff development policies are most effective in enhancing teachers’\ncompetencies and performance.\n\n42. _Success requires systematic system support and follow-up_ . Schwille and Dembele\n(2007) <sup>11</sup> carried", "source": "refugee_pads", "subset": "annotate_aivin_part2", "spans": [{"key": "sample:refugee_pads:000171:17:0:0", "start": 1692, "end": 1725, "surface": "data on initial teacher education", "probe_tag": "confusion", "probe_score": 0.7195, "luna_label": 0, "luna_reason": null}]}, {"key": "aivin2-199", "text": "-Gender-Violence-Publications.pdf)</u>\n34 <u>[https://today.lorientlejour.com/article/1249052/despite-major-steps-forward-in-domestic-violence-law-coronavirus-lockdowns-expose-the-many-](https://today.lorientlejour.com/article/1249052/despite-major-steps-forward-in-domestic-violence-law-coronavirus-lockdowns-expose-the-many-shortcomings-that-remain.html)</u>\n<u>[shortcomings-that-remain.html](https://today.lorientlejour.com/article/1249052/despite-major-steps-forward-in-domestic-violence-law-coronavirus-lockdowns-expose-the-many-shortcomings-that-remain.html)</u>\n35 Ray, J. (Nov 2019), Gallup, Political, Economic Strife Takes Emotional Toll on Lebanese,\n<u>[https://news.gallup.com/poll/325715/political-economic-strife-takes-emotional-toll-lebanese.aspx,](https://news.gallup.com/poll/325715/political-economic-strife-takes-emotional-toll-lebanese.aspx)</u>\n36 <mark>Karam, Elie G et al. (2006) Prevalence and treatment of mental disorders in Lebanon: a national epidemiological survey.</mark>\n<mark>The Lancet, 367, 1000 --– 1006.</mark>\n\n\nJun 29, 2021 Page 7 of 17", "source": "jdc_operational", "subset": "annotate_aivin_part2", "spans": [{"key": "jdc_operational:000054:6:3:0", "start": 963, "end": 994, "surface": "national epidemiological survey", "probe_tag": "confusion", "probe_score": 0.1708, "luna_label": 0, "luna_reason": "Bibliographic reference entry, not data use in the passage."}]}, {"key": "aivin2-200", "text": "**The World Bank**\nEthiopia Statistics for Results Project (P147356)\n\n\nchallenges facing in the NSS. These constraints included declining funding resources, low overall statistical\ncapacity, and limited statistical and physical infrastructure.\n\n\n6. The engagement of the World Bank in funding this project was critical because CSA was not able\nto secure sufficient resources from the Government’s general budget to enhance its institutional and\ninfrastructural capacity. In addition, the World Bank also brought global knowledge in the area of data\nquality assurance and adherence to international standards. For example, since 2011, the Living Standards\nMeasurement Study (LSMS) team of the World Bank have been collaborating with the CSA to produce the\nbiennial Ethiopian Socio-Economic Survey.\n\n\n**Contribution to Higher-level Objectives**\n\n\n7. The project was designed to contribute to the goals of the GoE’s GTP and the Millennium\nDevelopment Goals (MDGs) and facilitate the post-2015 MDG agenda setting. Improvements in the quality,\nrelevance, and timeliness of priority statistics contribute to more effective development policy by (a)\nproviding the basis for monitoring and evaluating the Government’s GTP and for tracking the progress of\nMDGs and (b) providing feedback to policy makers and citizens on the effectiveness of public policy and\nthe use of public resources. In addition, the project was to contribute the goals outlined in the 2013–2016\nCountry Partnership Strategy (CPS) of Ethiopia, (Report no. 71884-ET). It was designed to support the NSDS,\nwhich was expected to provide the relevant indicators to be used in formulating, updating, monitoring, and\nevaluating the strategies and targets of the country’s social and economic development programs including\nits first and second GTPs.\n\n\n**Design and Implementation**\n\n\n8. The World Bank’s support to statistical capacity building in Ethiopia followed the principles of the\nStatistics for Results Facility Catalytic Fund (SRF-CF). The SRF-CF seeks", "source": "fcv_pads_east_africa", "subset": "annotate_aivin_part2", "spans": [{"key": "fcv_pads_east_africa:009263:8:0:0", "start": 764, "end": 795, "surface": "Ethiopian Socio-Economic Survey", "probe_tag": "confusion", "probe_score": 0.378, "luna_label": 0, "luna_reason": "The sentence says the survey is produced through the project collaboration."}]}, {"key": "aivin2-201", "text": " nonresponse in other statistical series, such as income data in OECD countries. In the US, for\ninstance, the problem is common in some of the Census Bureau series (Scheuren, 2005), in\nthe National Interview Health Survey (NHIS; Schenker et al., 2006), but also in agricultural\nand forestry surveys such as the Agricultural Resource Management Survey (ARMS, Ahearn\net al., 2011) and the National Survey on Recreation and the Environment (Zarnoch et al.,\n2010). Other examples include the Labor Force Survey of the Municipality of Florence in\nItaly (Giusti and Little, 2011), and the Labor Force Survey in South Africa (Vermaak, 2012).\nWhat several of these experiences have in common is the systematic approach to dealing\nwith missing data as datasets are released in the public domain and analyzed for research\nand policy purposes. Increasingly, the technique of choice for dealing with missing data in\npublic use datasets is “multiple imputation” (Rubin, 1987; 1996), which, provided that the\nassumptions regarding the missing data mechanism hold, allows for valid inference on a\nrestored “complete” dataset, while taking into account the uncertainty associated with the\nimputation process itself.\n\nAs the drive towards open data advances in the developing world, methodical approaches\nto reliably address structural gaps in critical data, such as GPS-based land areas, are likely\nto be of increasing interest to national statistical agencies, their international partners, and\n\n\n3", "source": "general_prwp", "subset": "annotate_aivin_part2", "spans": [{"key": "prwp:001882:4:1:4", "start": 583, "end": 617, "surface": "Labor Force Survey in South Africa", "probe_tag": "confusion", "probe_score": 0.7159, "luna_label": 1, "luna_reason": "Cited survey provides an example of nonresponse in statistical data."}]}, {"key": "aivin2-202", "text": "..................................................................................................67\n\n\nAnnex 3: UNHCR Global Resettlement Statistical Report 2018.................................................................. 73\n\n\nIntroduction **.** ................................................................................................................................................................................................73\n\n\n**Submissions** ....", "source": "reliefweb", "subset": "annotate_aivin_part2", "spans": [{"key": "reliefweb:000739:58:3:0", "start": 112, "end": 161, "surface": "UNHCR Global Resettlement Statistical Report 2018", "probe_tag": "confusion", "probe_score": 0.4693, "luna_label": 1, "luna_reason": "Named external statistical report identified as an annex resource."}]}, {"key": "aivin2-203", "text": " the underserved MSMEs on the _collines_ of Burundi; and (v) mitigation of financial integrity risks\nrelated to the rapid expansion of financial services, such as anti-money laundering and financing of terrorism.\n\n15. **Despite government efforts to improve the business climate, it still faces many challenges that stem from**\n**ineffective implementation and limited institutional capacity, notably in protection of property rights (including**\n**intellectual property rights and consumer rights) and contract enforcement** . The concentration of ownership of\neconomic assets, weak competition, and a high degree of informality erode the confidence of private investors, which is\nfurther affected by years of political instability and institutional weaknesses.\n\n\n**C. Relevance to Higher Level Objectives**\n\n16. **The project aligns with the national priority of establishing the private sector as the main engine of**\n**development and growth, as outlined in the Burundi** **_pays émergent en_** **2040 and** **_pays_** **_développé en_** **2060 Vision, the**\n**National Development Plan of Burundi (** **_Plan National de Développement du Burundi_** **or PND) 2018** **–** **27.** The project will\n\n\n21 SME Finance Forum. “MSME Finance Gap.” https://www.smefinanceforum.org/data-sites/msme-finance-gap\n22 The US$50 million Burundi Digital Foundations Project (P176396) aims to increase broadband internet access, especially to underserved\ncommunities, and improve the government’s capacity to deliver public services digitally. Wider access and adoption of broadband, as well as data<u>enabled services, will facilitate adoption of digital technologies by entrepreneurs and MSMEs and", "source": "refugee_pads", "subset": "annotate_aivin_part2", "spans": [{"key": "refugee_pads:000004:17:2:0", "start": 1227, "end": 1243, "surface": "MSME Finance Gap", "probe_tag": "confusion", "probe_score": 0.7216, "luna_label": 0, "luna_reason": "Reference-list entry naming a linked source without shown data use."}]}, {"key": "aivin2-204", "text": "**The World Bank**\nUganda Digital Acceleration Program (P171305)\n\n\ncurrent hurdles faced by host communities and refugees in Uganda. Figure 9 summarizes key results of\na survey conducted in the Bidi Bidi refugee settlement between October 2018 and January 2019.\n\n  - Deployment of “containerized” schoolroom/community access centers, that can be transported into an\n\narea for quick set up. These centers typically have their own power source, satellite internet connection,\nruggedized computer terminals/tablets, etc.\n\n  - Specific assistance to promote the adoption/take-up of digital services highly-valued by host\n\ncommunities and refugees. Studies will be undertaken to i) understand the role of mobile money in\npromoting resilience and the gaps for wide adoption and ii) understand the shortcomings in SIM card\nregistration procedures. <sup>62</sup> [^62: As documentation requirements for SIM card registration increase, these have a negative impact on those who are\nundocumented, sometimes depriving them of (legal) access to mobile communications, and mobile money.] Adequate solutions to the identified problems will be sought to contribute to\na greater inclusion of refugees within host communities.\n\n  - Development and deployment of innovative digital solutions to ease communication, interaction, and\n\naccess to and sharing of information for persons with disabilities.\n\n\n**Figure 9. Survey of digital use of refugees of the Bidi Bidi camp**\n\n\n_Source: GSMA, The digital lives of refugees: How displaced populations use mobile phones and what gets in the_\n_way, 2019_\n\n\n<u>Subcomponent 1.4: Enabling environment for the digital connectivity</u>\n\n  - Supporting the set-up and resourcing of the Digital Uganda Vehicle – a specialized technical team tasked\n\nwith overseeing the implementation of the Digital Uganda Vision. The Vehicle will provide strategic\nsupport for MDAs to develop sectoral digital strategies, promote best practices within government\ninstitutions and build partnerships with the private sector.\n\n  - Supporting implementation of telecommunications regulations related to the Communications\n\nAmendment Act of 2016, to ensure a conducive enabling environment for growing private sector\ninvestment and optimal", "source": "jdc_operational", "subset": "annotate_aivin_part2", "spans": [{"key": "jdc_operational:000063:18:0:0", "start": 170, "end": 222, "surface": "survey conducted in the Bidi Bidi refugee settlement", "probe_tag": "confusion", "probe_score": 0.7323, "luna_label": 1, "luna_reason": "Past survey findings are presented in Figure 9 and sourced to a GSMA report."}, {"key": "jdc_operational:000063:18:0:1", "start": 1397, "end": 1430, "surface": "Survey of digital use of refugees", "probe_tag": "confusion", "probe_score": 0.6462, "luna_label": 0, "luna_reason": "Figure caption fragment, not an independently used data mention"}]}, {"key": "aivin2-205", "text": " social\nmanagement plans. To date the signaled increases in funding indicates that ERA is\ncommitted to preserving a high quality network. In addition, as can be seen from the\ndevelopment of relevant tools, ERA is committed to improving institutional performance\nand continues to seek ways to enhance the systems that have been developed through\nAPL3. Road Asset Management data obtained from ERA show that maintenance was\nperformed on a steady 72 percent of the network (while the network in good and fair\ncondition is shown as 91 percent), which serves to inform that the maintenance levels have\nat least kept pace with the levels at the start of the project. However, to achieve more\nsustainable gains, ERA would need to increase the level of maintenance as the data shows\nan increase in maintenance at a pace of only 3 percent on average annually, during the\nproject period, while the network increased at a pace of 4.3 percent on average annually.\nFurthermore, ERA should give serious consideration to significantly boost its capacity to\nbetter manage the long term environmental and social impacts.\n\n\n18", "source": "fcv_pads_east_africa", "subset": "annotate_aivin_part2", "spans": [{"key": "fcv_pads_east_africa:018257:27:1:0", "start": 351, "end": 377, "surface": "Road Asset Management data", "probe_tag": "confusion", "probe_score": 0.8618, "luna_label": 1, "luna_reason": "ERA asset-management data supports maintenance coverage and network-condition findings."}]}, {"key": "aivin2-206", "text": "about some management practices. Both the human capital of the manager and the management\n\n\npractices potentially determine the capacity of the business to adjust to the COVID-19 shock, and\n\n\nwe therefore include these variables in our specifications. The measures of the human capital of\n\n\nthe manager are the years of experience in the sector; whether he or she has a post-graduate de\n\ngree; whether he or she studied abroad; and whether he or she has worked in a multinational or a\n\n\nlarge business before. The indicators on management practices in the FAT are whether the busi\n\nness offers incentives to improve performance; the number of key performance indicators (KPI)\n\n\nmonitored; the frequency of measurement of KPI; and the time horizon of production targets. <sup>3</sup> We\n\n\nfollow ( _18_ ) and combine these four measures into a z-score, which we then include in our linear\n\n\nregressions. <sup>4</sup>\n\n\nOur specifications control for other pre-pandemic characteristics also available in the FAT: the\n\n\nage, size, and sector of the business; whether the business is an exporter; and whether the business\n\n\nis foreign owned.\n\n###### **2.2 The COV-BPS data**\n\n\nThe COV-BPS is an initiative of the World Bank Group to track the impact of the COVID-19\n\n\npandemic on the private sector across the world ( _1_ ). In Cear´a-Brazil, Senegal, and Vietnam, the\n\n\nCOV-BPS was applied on a sub-sample from the FAT. Combined, the FAT and COV-BPS data offer\n\n\na representative sample of businesses in each country right before and soon after the COVID-19\n\n\nshock. <sup>5</sup>\n\n\nOur measure of business performance from the COV-BPS is the reported percentage change\n\n\nin sales in the 30 days prior", "source": "general_prwp", "subset": "annotate_aivin_part2", "spans": [{"key": "prwp:002152:7:0:0", "start": 1156, "end": 1168, "surface": "COV-BPS data", "probe_tag": "confusion", "probe_score": 0.8671, "luna_label": 1, "luna_reason": "Named COV-BPS data provide business-performance measures and representative sample evidence."}]}, {"key": "aivin2-207", "text": ".................... 14\n\n2.6 Compilation of SDG indicators about FDPs **.** .........................................................................................16\n\n**<u>3. Main data sources</u>** **<u>18</u>**\n\n3.1 Review of main data sources **.** ................................................................................................................... 18\n\n3.1.1 Population Census **.** .........................................................................................", "source": "reliefweb", "subset": "annotate_aivin_part2", "spans": [{"key": "reliefweb:000141:1:1:0", "start": 380, "end": 397, "surface": "Population Census", "probe_tag": "confusion", "probe_score": 0.05, "luna_label": 0, "luna_reason": "Standalone table-of-contents heading, not evidence of census data use."}]}, {"key": "aivin2-208", "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": "refugee_pads", "subset": "annotate_aivin_part2", "spans": [{"key": "refugee_pads:000093:31:0:0", "start": 577, "end": 591, "surface": "School surveys", "probe_tag": "confusion", "probe_score": 0.1078, "luna_label": 0, "luna_reason": "Planned project monitoring survey, with no existing finding or demonstrated data use."}]}, {"key": "aivin2-209", "text": " data centers, and the supply and installation of government cloud services. This was designed to\nsimplify and improve the implementation of sector specific e-Services by a variety of MDAs. In the past few\n\n46 Activities partially supported by RCIP-5\n47 National Broadband Policy for Uganda, September 2018.\n48 Gap Analysis, Recommendations and Consultancy Report. Commonwealth Telecommunications Organization. January 2019.\n49 Critical infrastructures refer to physical, non-physical, and cyber resources or assets and systems that are essential for maintaining\ngovernment operations and the minimum functioning of the economy and society, for example in security, transportation, energy\nand finance.\n50 The UN eGovernment Development Index (EGDI) ranges from 0 to 1. It is a composite measure of the following 3 dimensions of egovernment: provision of online services, telecommunication connectivity, and human capacity.\n<u>[https://publicadministration.un.org/egovkb/en-us/Data/Country-Information/id/179-Uganda/dataYear/2018](https://publicadministration.un.org/egovkb/en-us/Data/Country-Information/id/179-Uganda/dataYear/2018)</u>\n\n\nJul 22, 2019 Page 7 of 28", "source": "jdc_operational", "subset": "annotate_aivin_part2", "spans": [{"key": "jdc_operational:000063:6:2:0", "start": 709, "end": 741, "surface": "UN eGovernment Development Index", "probe_tag": "confusion", "probe_score": 0.2958, "luna_label": 0, "luna_reason": "Index is defined, but its data are not used for a finding or analysis."}]}, {"key": "aivin2-210", "text": "**_Kenya_** **_Youth_** **_Employment_** <sup>**_and Opportunities_**</sup> <sup>**_Project_**</sup> <sup>**_(KYEOP)_**</sup>\n\n**_Reports_** **_and Financial_** <sup>**_Statements-For the financial year ended June 30,_**</sup> <sup>**_2020_**</sup>\n\n\n**SIGNIFICANT** **ACCOUNTING** **POLICIES** <sup>**(Continued)**</sup>\n\n\nDuring the year there were <sup>no</sup> <sup>loan</sup> <sup>disbursements</sup> <sup>were</sup> <sup>received</sup> <sup>in</sup> <sup>form</sup> <sup>of</sup> <sup>direct</sup>\n\npayments from third parties.\n\n\n**i)** **Exchange** **rate differences**\n\n\n\nThe accounting records are <sup>maintained</sup> <sup>in</sup> <sup>the</sup> <sup>functional</sup> <sup>currency</sup> <sup>of the</sup> <sup>primary</sup> <sup>economic</sup>\n\nenvironment in which the Project <sup>operate", "source": "fcv_pads_east_africa", "subset": "annotate_aivin_part2", "spans": [{"key": "fcv_pads_east_africa:011397:36:0:0", "start": 584, "end": 602, "surface": "accounting records", "probe_tag": "confusion", "probe_score": 0.4447, "luna_label": 0, "luna_reason": "Routine project accounting records, not substantive data reuse."}]}, {"key": "aivin2-211", "text": "Between 2007 and 2009, the Marriage Transitions in Malawi (MTM) project collected\n\n\ninnovative, longitudinal data from a random sample of nearly 1,200 initially never-married\n\n\nwomen and men in the Central Region of Malawi, ranging in age from 14-20 for females and 17\n\n25 for males. The study was designed to understand the links between pre-marital relationships\n\n\nand sexual activity, the transition into marriage, socioeconomic status, and HIV/AIDS.\n\n\nRespondents provided detailed information on socio-economic characteristics, marriage and\n\n\nfertility, and sexual partnering. Two particular features of this longitudinal data set stand out.\n\n\nFirst, respondents were interviewed at short intervals, up to five times within a 24-month\n\n\nwindow. Most panel studies in Sub-Saharan Africa conduct survey rounds at a minimum of\n\n\nyearly intervals (and often longer), which necessitates a reliance upon retrospective reporting of\n\n\nevents, and may bias estimates due to recall error (such as on dating and marriage). <sup>3</sup> [^3: The issue of recall bias in reporting events is also relevant for migration data. For example, lacking panel data\nwhich follows movers over time, studies may need to use life history calendars to collect information on moves, the\ntiming of moves, and the reason for the move. This is the approach of Reed, Andrzejewski, and White (2010) in\ntheir study of how migration links with education, employment, marital status, and childbearing in Ghana.] Second –\n\n\nand most relevant for this study – respondents who left the sample, due to relocation outside of\n\n\nthe study site, were tracked by the research team. Such tracking allows us to identify the\n\n\nsocioeconomic characteristics and demographic behaviors of mobile respondents.\n\n\nThere are multiple ways to define migration. Using the MTM data to explore the\n\n\nsocioeconomic dimensions of migration, we take several approaches to measuring migration. In\n\n\nthe most general approach, we look at the distance in kilometers (based on GPS data) between\n\n\nthe baseline (summer 2007) and follow-up (summer 2009) residence. That", "source": "general_prwp", "subset": "annotate_aivin_part2", "spans": [{"key": "prwp:005364:10:0:0", "start": 614, "end": 635, "surface": "longitudinal data set", "probe_tag": "confusion", "probe_score": 0.8524, "luna_label": 1, "luna_reason": "Existing longitudinal dataset supports concrete findings about interviews and respondent tracking."}]}, {"key": "aivin2-212", "text": "vpl.com.ua 5\n\n##### LOCATIONS OF DSPP EMPLOYEES WHO USE THE UIDB\n\n\n                      - Donetsk region: Avdiivka, Bakhmut, Vuhledar, Druzhkivka, Myrnohrad, Kurakhove,\nKostiantynivka, Mariupol, Mangush and Selidove;\n\n\n\n\n\n\n\n\n- Zaporizhzhia region: Berdiansk, Melitopol, Orikhiv, Prymorsk, Pryazovske and\nChernigivka;\n\n\n- Kharkiv region: Novopskov, Severodonetsk, Lysychansk and Vovchansk;\n\n\n- Dnipropetrovsk region: Pokrov.\n\n\n\n\n\n**60.9%** of employees who account for IDPs using the UIDB also use the previous register concurrently.\n\n\n\n\n\n\n**• 26 % - yes;**\n\n**• 61 % - no;**\n\n**• 13% - did not answer or were unable to answer.**\n\n\nExamples of poor UIDB performance include sudden slowdown / stoppage, rendering it impossible\nto enter IDP data into the UIDB or access IDP data.\n\n\n**The monitoring showed great variance among local DSPP employees’ understanding of**\n\n\n**• 40,8 % - crosschecking IDP data, i.e. reconciliation of information available to the DSPP**\n**with data from other registers;**\n\n**• 69.7 % - elimination of double entries for the same IDPs / double social benefits;**\n\n**• 11.8 % - elimination of monetary assistance when provided inappropriately** <sup>**11**</sup> **;**\n\n**• 18.4 % - verification of length of IDP stay on the territory controlled by the Government**\n**of Ukraine with the State Border Service of Ukraine (State Border Service) register to**\n*", "source": "reliefweb", "subset": "annotate_aivin_part2", "spans": [{"key": "reliefweb:000490:4:0:1", "start": 735, "end": 743, "surface": "IDP data", "probe_tag": "confusion", "probe_score": 0.4484, "luna_label": 0, "luna_reason": "Generic data mention describes UIDB access, not substantive use or an attributed finding."}]}, {"key": "aivin2-213", "text": " The sustainability of the sanitation measures will be carefully assessed from the point of view\nof good practices, cost effectiveness, affordability and the Djibouti water shortage environment.\n\n\n6. **Social**\n\n\n_6.1 Summarize key social issues relevant to the project objectives, and specify the project's social_\n_development outcomes._\n\n\nDjibouti is a small country and many key social issues were identified in the 1997 Poverty\n\nAssessment. The issues raised included the percentage of the population classified as poor in 1996\n(50-80% reaching the upper-bound when refugees, nomads and homeless are taken into account); large\nnumbers of refugees, nomads, and homeless populations; the majority of the poor live in urban areas\n(85%) even if the incidence of extreme poverty is overwhelmingly rural. Urban households can take\nadvantage of safety nets derived from the commodity market and services, and job opportunities are\nnot available in rural areas. The key problems faced by children include: (a) the high number of street\nchildren who have fled war ravaged Somalia and Ethiopia; (b) late entrance into school by poorer\nchildren (one out of four starts school at age 9 and leaves school at age 14); (c) health issues (diarrhea\n\nand malnutrition) are a leading cause of death for children under age 5. Other problems affecting the\nwhole population include respiratory infections on the increase (due to malnutrition); endemic health\nproblems (AIDS, tuberculosis, malaria, cholera); the widespread practice of Female Genital Mutilation\n(FGM); sanitation costs are high for poorer households not connected on the main water network as", "source": "refugee_pads", "subset": "annotate_aivin_part2", "spans": [{"key": "sample:refugee_pads:000041:23:1:0", "start": 420, "end": 444, "surface": "1997 Poverty\n\nAssessment", "probe_tag": "confusion", "probe_score": 0.0723, "luna_label": 1, "luna_reason": null}]}, {"key": "aivin2-214", "text": "|80|119|117|426|\n|South Lebanon|37|50|38|27|152|\n|Total|318|330|314|313|1275|\n|percent of total|24.52|25.44|24.21|24.13|98.30|\n\n\n\n6. Based upon the rehabilitation unit costs and existing surface areas presented in Table 3\nbelow, the cost of works was calculated for all 399 eligible schools. As a result, the total needed\nbudget to repair all these schools is US$121 million. With the proposed amount of\nsubcomponent financing, the project can finance the full rehabilitation of the first 10 schools of\nthe priority list.\n\n\n7. Project preparation included the preparation of a database which accounts for many of the\nschool facilities characteristics in order to prepare criteria and indicators for the selection of\npriorities. These show that out of the 1,275 schools during school year 2014-15:\n\n\n    - Some 708 schools do not belong to MEHE and rent is paid for 540 of them;\n\n    - 306 (20 percent) of school buildings were not originally designed as schools;\n\n    - Almost 95 percent of the public schools have Syrian students during the 1st shift;\n\n    - 89 schools have second shifts for Syrians;\n\n    - 652 schools are located in vulnerable areas as per the Education Working Group\n\nstandards.\n\n\n27", "source": "jdc_operational", "subset": "annotate_aivin_part2", "spans": [{"key": "sample:jdc_operational:000030:35:1:0", "start": 577, "end": 585, "surface": "database", "probe_tag": "confusion", "probe_score": 0.4667, "luna_label": 0, "luna_reason": null}]}, {"key": "aivin2-215", "text": "also be provided to properly levy, collect and account for local duties and taxes. NaCSA staff would be\ngiven an opportunity to visit Community Driven Development Projects in comparable countries to\ncapitalize on their experiences. Regional and district line ministry staff would be trained in community\nmobilization, conflict resolution, social capital building, and technical appraisal skills.\n\n\n(b) Substantial IEEC activities linked to the various sub-projects are envisaged. These activities\nwould be undertaken using existing IEC materials endorsed by the various line ministries. For example,\nin the case of the rehabilitation of a health post, IEC messages could be envisaged to inform the\npopulation on the proper use of insecticide treated bed nets as a means of preventing malaria.\n\n\n(c) Monitoring and evaluation at the community, district, regional and central levels would be\ngiven high priority, and linked regularly and directly with NaCSA decision making on NSAP policy,\nstrategy and operational matters. These activities would be directly undertaken, or commissioned by,\nstaff of NaCSA's Planning, Monitoring and Evaluation Directorate. The Project Design Matrix (logical\nframework, Annex 1) would form the basis for monitoring NSAP outputs, outcomes and impact. An\nassessment of project status would accompany each NaCSA work program and budget submitted\nsemi-annually to the NaCSA Board. Other M&E activities would include a pre-project Social\nAssessment; establishment of NSAP baseline data (in conjunction with the collection of data for the\nCRRP Implementation Completion Report); social assessments during implementation; annual technical\naudits; beneficiary assessments; incorporation of NaCSA into GOSL's semi-annual public expenditure\ntracking surveys (PETS); and independent impact assessments.\n\n\nIn addition to conventional sub-project monitoring and evaluation (incorporated in the\nsub-project cycle as outlined in the Operations Manual), a pilot participatory monitoring and evaluation\nsystem would be introduced in a representative sample of the predominant types of CDP sub-projects.\nBeneficiary communities would identify quantitative and qualitative indicators", "source": "fcv_pads_east_africa", "subset": "annotate_aivin_part2", "spans": [{"key": "fcv_pads_east_africa:017745:36:0:1", "start": 1743, "end": 1778, "surface": "public expenditure\ntracking surveys", "probe_tag": "confusion", "probe_score": 0.3091, "luna_label": 0, "luna_reason": "Planned incorporation into future monitoring activities, not existing data use."}]}, {"key": "aivin2-216", "text": "# WPS3818\n\n### **The Use of Willingness to Pay Experiments:** **Estimating demand for piped water connections in Sri Lanka**\n\n##### **_Subhrendu K. Pattanayak, Caroline van den Berg,_** **_Jui‐Chen Yang, and George Van Houtven 1_**\n\nAbstract\n\n\n_This paper shows how Willingness to Pay surveys can be used to gauge household demand for improved network_\n_water and sanitation services when a private sector transaction is considered. We do this by presenting a case‐_\n_study from Sri Lanka, where we surveyed approximately 1,800 households in 2003. Using multivariate_\n_regression, we show that a complex combination of factors drives demand for service improvements. While_\n_poverty and costs are found to be key determinants of demand, we also find that location, self‐provision, and_\n_perceptions matter as well, and that sub‐sets of these factors matter differently for sub‐samples of the population._\n_To evaluate the policy implications of the demand analysis, we use the model to estimate uptake rates of_\n_improved service under various scenarios – demand in sub‐groups, the institutional decision to rely on private_\n_sector provision, and various financial incentives targeted to the poor. The simulations show that in this_\n_particular environment in Sri Lanka, demand for piped water services is low, and that it is unlikely that under_\n_the present circumstances the goal of nearly universal piped water coverage is going to be achieved. Policy_\n_instruments, such as subsidization of connection fees, could be used to increase demand for piped water, but it is_\n_unclear whether the benefits of the use of such policies would outweigh the costs._\n\n\n**JEL classification** : **H4** Publicly Provided Goods; **", "source": "general_prwp", "subset": "annotate_aivin_part2", "spans": [{"key": "prwp:003032:0:0:0", "start": 266, "end": 292, "surface": "Willingness to Pay surveys", "probe_tag": "confusion", "probe_score": 0.5996, "luna_label": 1, "luna_reason": "Survey data support analysis of household demand for improved water services."}]}, {"key": "aivin2-217", "text": " pas d’une part d’avoir des données biométriques (empreintes\ndigitales et / ou balayage de l’iris) pour une meilleure vérification de l’identité de la personne, ou\nne facilitent pas la prévention de la fraude en temps réel sur le terrain, et sont non-accessible\naux autres acteurs d’autre part. Il est à noter également l’absence de données désagrégées par\nâge, genre et diversité permettant de comprendre et de répondre aux besoins spécifiques des\ndifférents groupes de personnes affectées. En outre, le risque d’infiltration des personnes nonaffectées et le double enregistrement remettant en cause la fiabilité des données et informations\ncollectées.\n\n\nSur les 162,755 personnes déplacées internes enregistrées dans la province du Lac, la majorité\nne dispose pas de documents d’état civil, à l’instar des populations hôtes. Toutefois, il n’y a pas\nde données exactes sur le nombre de personnes déplacées qui ont des besoins de document\n\n\n5", "source": "reliefweb", "subset": "annotate_aivin_part2", "spans": [{"key": "reliefweb:000987:6:2:0", "start": 28, "end": 48, "surface": "données biométriques", "probe_tag": "confusion", "probe_score": 0.0963, "luna_label": 0, "luna_reason": "States biometric data are unavailable, without analysis or substitute use."}]}, {"key": "aivin2-218", "text": " percent of the population, or more than 10 million\npersons. The Government budget was reduced by more than 50 percent due in part to decreasing oil\nrevenues as supplies have dwindled, limiting its capacity to provide basic services to an already\nimpoverished population. Food insecurity and malnutrition levels in the country have surpassed\nemergency levels. Yemen is among the 10 countries in the world with the highest rates of food insecurity,\nwith the country ranked third for the highest malnutrition in the world: 58 percent of children under 5 are\nstunted, and more than 1 in 10 children is acutely malnourished. Based on the World Food Program’s\n(WFP) recent Comprehensive Food Security Survey (2009), 7.5 million persons are caught in the chronic\npoverty trap. The situation is further compounded by climate change, increasing influx of refugees from\nthe Horn of Africa, high population growth, and low literacy.\n\n\n3. **Fiscal sustainability is the foremost economic issue in Yemen,** as government spending is\ndriven by a large public sector wage bill and unsustainably high fuel subsidies. Insufficient budget\nresources are a severe constraint on the Government’s ability to provide essential services and to address\npoverty. A steep decline in oil revenues is evident, attributable in part to oil price fluctuations, but mainly\nto production decline as reserves diminish. The authorities have borrowed domestically to finance a\ngrowing deficit (estimated at **_7_** percent for 20 lo), but have not significantly adjusted expenditure. Human\ndevelopment and poverty alleviation efforts are constrained by the limited fiscal resources. Macroeconomic choices have a direct implication on the Government’s ability to sustain present social\nprograms and future initiatives towards poverty reduction.\n\n\n4. **At the same time, the Government has demonstrated a commitment to poverty reduction**\n**and has developed and is implementing a Development Plan for Poverty Reduction Strategy**\n**(DPPR).** One of the main pillars of the strategy is to", "source": "refugee_pads", "subset": "annotate_aivin_part2", "spans": [{"key": "refugee_pads:000080:7:1:0", "start": 668, "end": 702, "surface": "Comprehensive Food Security Survey", "probe_tag": "confusion", "probe_score": 0.7431, "luna_label": 1, "luna_reason": "WFP survey provides the cited estimate of 7.5 million people in chronic poverty"}]}, {"key": "aivin2-219", "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_aivin_part2", "spans": [{"key": "jdc_operational:000006:67:2:0", "start": 354, "end": 381, "surface": "up-dated population figures", "probe_tag": "confusion", "probe_score": 0.875, "luna_label": 1, "luna_reason": "Existing FY 2017/18 population figures are used as inputs to estimate road benefits."}]}, {"key": "aivin2-220", "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": "fcv_pads_east_africa", "subset": "annotate_aivin_part2", "spans": [{"key": "fcv_pads_east_africa:016919:31:1:0", "start": 170, "end": 184, "surface": "NaCSA M&E data", "probe_tag": "confusion", "probe_score": 0.149, "luna_label": 0, "luna_reason": "Names monitoring data without an attached finding or substantive analytical use."}]}, {"key": "aivin2-221", "text": "**Figure 1.2. Female adolescents reporting forced sexual initiation, as a percent of those reporting**\n**having had sex (Population-Based Surveys 1993-1999)**\n\n\n\nNew Zealand\n\n\nUnited States\n\n\nMozambique\n\n\nGhana\n\n\nSouth Africa\n\n\nUnited Republic of Tanzania\n\n\nCameroon\n\n\nPeru\n\n\nCaribbean\n\n\n\n\n\n\n\n\n\n\n\n48%\n\n\n\n**Source:** Population-Based Surveys 1993-1999. All figures cited in Jewkes, Sen, and Garcia Moreno, 2002.\n\nSexual violence within marriage is also common, with approximately 10-13 percent of women reporting\nhaving been forced by a partner to have sex against their will at some point (Heise, Ellsberg, and\nGottemoeller, 1999). Sexual violence often accompanies physical battery by intimate partners, and in\nmany settings, women and men believe that men have the right to beat their partners for refusing sex\n(Figure 1.3). Women who experience physical violence by intimate partners may be less able to negotiate\nwhen and how they have sex. Nonetheless, large variations exist in patterns and prevalence levels\nbetween and within countries. For example, a study from León, Nicaragua found that nearly all women\nwho reported sexual violence had also experienced physical violence (Ellsberg et al, 2000). In contrast,\nresearch from Indonesia suggests that sexual violence often occurs outside the context of physical\nviolence and may be even more common than physical violence (Hakimi et al., 2001).\n\n**Figure 1.3. Percentage of men and women who say that men have the right to beat their wives when**\n**they refuse to have sex.**\n\n\n81%\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n|Col1|Col2|\n|---|---|\n|||\n\n\n\nEgypt (rural) Egypt (urban) Ghana West bank / Gaza\n\nstrip\n\n\n\nNicaragua (rural) Singapore\n\n\n\n**Source:** Various population-based surveys, cited in Heise, Ellsberg, and Gottemoeller, 1999.\n\n\n\n11", "source": "general_prwp", "subset": "annotate_aivin_part2", "spans": [{"key": "prwp:002832:10:0:0", "start": 121, "end": 145, "surface": "Population-Based Surveys", "probe_tag": "confusion", "probe_score": 0.8953, "luna_label": 1, "luna_reason": "Source surveys underpin the figure on forced sexual initiation."}]}, {"key": "aivin2-222", "text": " spreadsheets for analysis. RCOs varied in the amount\nand type of data they recorded on service users but had\nthe potential to record more socio-economic data that\ncould be used to establish user profiles.\n\n\n**5.2 SUPPLEMENTARY EDUCATION**\n\n\nThe research deliberately included several RCOs who\nprovided supplementary education, an area in which\noutcomes were expected to be relatively easy to measure\nand record. RCO supplementary schools in the sample all\ntaught community languages to children and young\npeople. For one newly arrived community, this was a\npriority. For most RCOs improving educational attainment\nin mainstream schools was also a priority. In addition to\nproviding tuition in community languages, schools also\nprovided instruction in culture and religion.\n\n\nProvision varied from Saturday schools to after school\nclasses and homework clubs. One school offered\ninstruction in maths and English at all levels from SATS\nto GCSE; others also offered instruction in mainstream\nsubjects. Some schools helped parents to support their\nchildren’s education, providing information on education\nin the UK, the importance of a good environment for\nlearning at home and how to engage with schools.\n\n\nSupplementary schools were often seen as places where\nother issues could be addressed, particularly other learning\nneeds. One school hosted parenting and anti-terrorism\nsessions delivered by the local authority. The same school\nhad set up a separate youth charity run by young people\nfrom the community who mentored pupils. ESOL for\nparents was provided by some supplementary schools.\n\n\n19", "source": "reliefweb", "subset": "annotate_aivin_part2", "spans": [{"key": "reliefweb:001328:18:2:0", "start": 139, "end": 158, "surface": "socio-economic data", "probe_tag": "confusion", "probe_score": 0.1064, "luna_label": 0, "luna_reason": "Describes potential future data recording, not existing data use."}]}, {"key": "aivin2-223", "text": "**The World Bank**\nLebanon Health Resilience Project (P163476)\n\n\n48. **The MoPH, through the PMU’s two coordinators (PHCC and hospital), will be responsible for**\n**monitoring the daily progress of the project,** focusing on improved accessibility of beneficiaries to the\npackage of services, proper procurement, and capacity building of hospitals. The PMU will be\nresponsible for preparing and submitting semiannual progress reports that, among other things, provide\ndetailed reporting on services, procurement, and expenditures. It will also conduct mid-term and postcompletion evaluations to gauge progress toward the PDO and assess the impact of the project on\ntargeted beneficiaries.\n\n49. **The HIS system developed by the MoPH will be further refined and expanded under the**\n**project to all newly enrolled PHCCs to support the implementation and monitoring of the program** .\nData will be collected and used to: (i) supervise the performance of PHCCs; (ii) monitor the progress of\nbeneficiary accessibility; (iii) monitor hospital improvements; and (iv) improve the provision of services\non the basis of intermediate output and outcome data. The data will be verified directly by MoPH\nsupervisory systems and external evaluation, and indirectly through triangulation with other data\nsources such as hospital claims.\n\n50. **Beneficiary feedback and grievance redress mechanisms will also play an important role in**\n**monitoring the project.** The EPHRP made significant progress toward establishing grievance redress\nmechanisms at the central and facility levels. This project will continue to strengthen the system by\nsupporting the MoPH hotline and finalizing the automated Grievance Module to create one platform\nthat integrates registration databases from the different sources to track and manage grievances. This\nwill provide the MoPH with timely access to grievance data to address grievances.\n\n\n51. **The WB will conduct regular implementation support missions** during which implementation\nprogress,", "source": "refugee_pads", "subset": "annotate_aivin_part2", "spans": [{"key": "refugee_pads:000108:28:0:1", "start": 1307, "end": 1322, "surface": "hospital claims", "probe_tag": "confusion", "probe_score": 0.2578, "luna_label": 1, "luna_reason": "Existing hospital claims are used as a triangulation data source."}]}, {"key": "aivin2-224", "text": "**The World Bank**\nUganda Secondary Education Expansion Project (P166570)\n\n\ngovernment subsidies and grew to represent about 59 percent of the schools offering secondary education and\nslightly above half of the total students enrolled. Still, the Uganda secondary enrollment rate stands at a level\nwhich is significantly below that of regional comparators.\n\n7. **The issue of insufficient resources is compounded by an array of inefficiencies that undermine the**\n**performance and productivity of the entire system.** These include, inter alia:\n\n\na) **An insufficient number and inadequate distribution of free of charge public secondary schools**\n\nthroughout Uganda to address the existing and growing demand generated by the projected population\ngrowth, the rise in primary school completion, and the recent significant inflow of refugees.\n\n\nb) **Low internal efficiency due to very low survival rate throughout the education cycles** . In 2017, the\n\nprimary survival rate stood at 56 percent, which is considerably below the primary survival rate in Kenya\nat close to 100 percent, Ethiopia at 72 percent, and Rwanda at 68 percent (Figure 3). <sup>7</sup> [^7: End of primary education here refers to 6th grade for the ease of cross-country comparison.] As a result of this\nlow overall productivity, it takes almost twice as many years of schooling than normal to produce a\ngraduate in primary and secondary education. For instance, on average it took 12.6 years for a primary\nschool student to graduate the cycle in 2013 (primary cycle in Uganda is seven years), which is only\nmarginally better than the 14 years it took in 2008. The inefficiencies persist through secondary school,\nlargely as a consequence of low volumes of students progressing through primary grades and later to\nlower secondary. As a result, the cost of service provision at the secondary level in 2013 was 2.3 times\nhigher than what it should have been. <sup>8</sup>\n\nFigure 3: Survival Rates", "source": "jdc_operational", "subset": "annotate_aivin_part2", "spans": [{"key": "jdc_operational:000018:13:0:0", "start": 954, "end": 975, "surface": "primary survival rate", "probe_tag": "confusion", "probe_score": 0.2241, "luna_label": 0, "luna_reason": "Bare rate phrase without a named or generic data source."}]}, {"key": "aivin2-225", "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_aivin_part2", "spans": [{"key": "fcv_pads_east_africa:016286:29:1:0", "start": 862, "end": 876, "surface": "NaCSA M&E data", "probe_tag": "confusion", "probe_score": 0.2118, "luna_label": 0, "luna_reason": "Project M&E data listed as future monitoring/reporting evidence, not existing external data use."}, {"key": "fcv_pads_east_africa:016286:29:1:1", "start": 961, "end": 969, "surface": "M&E data", "probe_tag": "confusion", "probe_score": 0.1144, "luna_label": 1, "luna_reason": "Existing agency monitoring data is listed as a source for project indicators."}]}, {"key": "aivin2-226", "text": " 2014), administrative data are not sufficient to assess employment rates, requiring\nreliance on household surveys. However, operationalizing these definitions in Labor Force\nSurveys has been fairly difficult and has been applied inconsistently across countries and even in\nthe same country over time.\n\nThe main difficulty with measuring women’s employment has been with self-employment and\nunpaid family work that women undertake in the context of household enterprises and farms.\nOur work suggests that information about such work can best be obtained by asking about the\nhousehold’s involvement in specific activities such as crop production, livestock rearing, other\nagricultural processes, and non-agricultural activities and then inquiring in detail about who\namong household members is involved in either running or managing these activities or in\nsupport roles. Distinguishing between employment and other forms of work would then depend\non whether these activities are carried out at least in part for purposes of market exchange.\n\nClearly, an individual approach to inquiring about employment is also necessary, but that\napproach should be supplemented by this enterprise-based methodology to obtain a fuller picture\nof women’s and potentially children’s involvement in economic activity in LMICs. Accurate\ndata on women’s employment is critically important for informing policies and programs to\nsupport women’s employment and economic development. For instance, common surveys in\nSub-Saharan Africa that differentially sample and survey women-owned businesses yield\ndifferent policy implications for supporting such businesses (Hardy, Kagy, and Jimi 2022).\n\nFuture research should revisit the relationship between women’s employment and other\noutcomes with better measures of employment. For instance, the additional employment\ncaptured with different measures could have a differential relationship with women’s\n\n\n24", "source": "general_prwp", "subset": "annotate_aivin_part2", "spans": [{"key": "prwp:001600:25:1:0", "start": 163, "end": 182, "surface": "Labor Force\nSurveys", "probe_tag": "confusion", "probe_score": 0.3571, "luna_label": 0, "luna_reason": "Names survey type but does not cite or use existing survey data."}]}, {"key": "aivin2-227", "text": " to query the UNHCR Refugee Information Management System (RIMS) to\nverify IDs. Instead, they must verify identification manually by requesting additional documentation\nor by contacting the Office of the Prime Minister (the government entity responsible for refugee\nregistration) directly. Even with these manual processes, providers cannot verify the photo of the\nrefugee, leaving the verification process incomplete. Providers are especially vigilant about verifying\nthe identification of displaced persons because AML/CFT regulations sanction South Sudan and\nDemocratic Republic of Congo, the two countries from where most of the refugees in Uganda\noriginate. In these cases, financial institutions are responsible for ensuring that the relevant funds\nare not financing conflict or involved in money laundering activities. Even when the identification is\navailable and authenticated, or additional identification has been provided, some refugees report\nthat remittances are denied because their names are either misspelled or inverted by the sender.\nThis is common when translating names from French or when there is confusion about first/last\nname conventions.” <sup>113</sup> [^113: https://uncdf-cdn.azureedge.net/media-manager/88675?sv=2016-05-31&sr=b&sig=wm9IHf28t4bIpiAQsl8PqVWb%2BRMA8JLEGU%2FasC4kKtE%3D&se=2018-11-02T18%3A00%3A49Z&sp=r]\n\n\n111 http://www.uncdf.org/article/2593/study-know-your-customer-requirements-dfs-uganda\n112 Executive Summary: Uganda country assessment on affordable and accessible remittances for forcibly displaced\npersons and host communities https://uncdf-cdn.azureedge.net/media-manager/88675?sv=2016-05-31&sr=b&sig=wm9IHf28t4bIpiAQsl8PqVWb%2BRMA8JLEGU%2FasC4kKtE%3D&se=2018-11-02T18%3A00%3A49Z&sp=r\n113 https://uncdf-cdn.azureedge.net/media-manager/88675?sv=2016-05-31&sr=", "source": "reliefweb", "subset": "annotate_aivin_part2", "spans": [{"key": "reliefweb:001415:40:1:0", "start": 14, "end": 57, "surface": "UNHCR Refugee Information Management System", "probe_tag": "confusion", "probe_score": 0.6951, "luna_label": 1, "luna_reason": "Named refugee information system queried to verify identification."}]}, {"key": "aivin2-228", "text": "Annex 4\nPage 4 of 5\n\nextensive retraining of teachers and head-teachers. Temporary teachers will now be recruited\nearlier so that they can benefit from pedagogic training.\n\n\n**E. Justification of Public Finance to Support the Program**\n\nThere is a global consensus that universal access to basic education is the right of each child and this\nhas been widely endorsed most recently at the Education for All Conference in Dakar. The positive\nexternalities of basic education provide ample public finance justification for supporting universal\nbasic education with public funds. In addition, Djibouti's economic future depends heavily on the\nquality and productivity of its work-force as it has few other resources. Basic education is an\nessential pre-condition to improve workforce quality and productivity. Thus, public funding for it is\nalso justified on the grounds of improving Djibouti's development potential.\n\nPublic support for universal basic education in Djibouti can also be justified on the grounds of\nreducing income and gender inequities in enrollment which the Government proposes to address\nthrough a variety of ways discussed above. Random surveys of school children will be done over the\nten year period (including a base-line in 2001) to assess progress in reducing gender gaps and income\ngaps in enrollment.\n\n\n**F. Project Approach versus Budget Support Approach**\n\nThe project approach is considered more appropriate in Djibouti's case because given the urgent fiscal\nconstraints, budget support money may get diverted to finance immediate current needs and the\nschools may never get built. The supply of school places and the quality of schooling is easier to\naddress through a project approach.\n\n\n**G. Fiscal Impact of Program**\n\nAnnex 4, Table 1 illustrates the potential fiscal impact. This appears to be quite manageable. The\nrequired cost estimates include all levels of education, ministry overheads and potential grants to the\nprivate sector. The Government projects the most likely scenario for Djibouti's growth to be 2.4% per\nyear during the period 2000-2010 and expects the budget to grow slightly slower", "source": "refugee_pads", "subset": "annotate_aivin_part2", "spans": [{"key": "refugee_pads:000038:40:0:0", "start": 1148, "end": 1181, "surface": "Random surveys of school children", "probe_tag": "confusion", "probe_score": 0.3714, "luna_label": 0, "luna_reason": "Planned surveys will be conducted over the project period."}]}, {"key": "aivin2-229", "text": "**The World Bank**\nUganda Digital Acceleration Program (P171305)\n\n\n3. **Uganda hosts Africa’s largest refugee population for whom digital connectivity could offer improved access to**\n**basic services and economic opportunity.** As a result of ongoing outbreaks of unrest, drought and socio-economic\ncrises across the neighboring Horn of Africa sub-region <sup>10</sup>, Uganda currently hosts over 1.4 million refugees <sup>11</sup>    - mostly\nin the Northern and Western regions of the country – making it the largest refugee-hosting country in Africa. <sup>12</sup>\nAccording to the United Nations Children’s Fund (UNICEF), women and children constitute 86% of the refugee\npopulation in Uganda. <sup>13, 14</sup> Despite the country’s many challenges, Uganda has maintained an open-door policy and\nis expected to receive an additional influx of refugees from South Sudan and the Democratic Republic of Congo in\n2019. <sup>15</sup>\n\n\nSectoral and Institutional Context\n\n\n4. **The digital sector represents one of the fastest growing sectors in Uganda, with positive spill-over effects on**\n**various other sectors of the economy.** The ICT sector’s contribution to the country’s GDP has considerably increased,\nfrom 6.6% in 2015 to 8.7% in 2016, <sup>16</sup> recording average annual growth rates of up to 20%. <sup>17</sup> This trend is driven by i)\na series of conducive Government policies <sup>18</sup>, and ii) the significant uptake of mobile phone subscribers, which grew\nfrom 14.7 million in 2010 to 21.7 million in 2018, representing an", "source": "jdc_operational", "subset": "annotate_aivin_part2", "spans": [{"key": "jdc_operational:000063:3:0:0", "start": 1447, "end": 1471, "surface": "mobile phone subscribers", "probe_tag": "confusion", "probe_score": 0.8071, "luna_label": 0, "luna_reason": "Subscriber counts are quoted without naming a data source or dataset."}]}, {"key": "aivin2-230", "text": "*_.6.5_** **19.0** **15.7**\n\n**3.** **DLI 3:** Pregnant women 48% **56%**\nreceiving at least one antenatal\ncare visit\n\nDisbursement amount **(US$** mil): **_5.50_** **8.80** 14.3 **11.9**\n\n**4.** **DLI 4:** Contraceptive **31%** **35%**\nPrevalence Rate\nDisbursement amount **(US$** mil): **9.85** **10.65** **20.5** **17.1**\n\n**5.** **DLI** **5:** Health Centers **_55%_** **60%** **70%** **75%** **80%**\nreporting **HMIS** data in time\nDisbursement amount **(US$** mil): **1.0** **1.0** **1.0** **1.0** **1.0** **_5.0_** 4.2\n\n\n**6.** **DLI** **6:** Development and Protocol and Implemented in Implementation Review and Scaled up to\nimplementation of Balanced roll out plan 20 Woredas in **3** continues in 20 decision on 200 woredas\nScore card approach to assess developed regions with Woredas in **3** national scale-up across the\n\nperformance and related appropriate regions taken based on the country\nnumber of impact evaluation\ninstitutional incentives", "source": "fcv_pads_east_africa", "subset": "annotate_aivin_part2", "spans": [{"key": "fcv_pads_east_africa:017835:36:1:0", "start": 417, "end": 421, "surface": "HMIS", "probe_tag": "confusion", "probe_score": 0.0654, "luna_label": 0, "luna_reason": "HMIS appears within a DLI table metric, not as independently used data."}]}, {"key": "aivin2-231", "text": "\n𝑤𝑖,𝑝ℎ𝑜𝑛𝑒 = 𝑤𝑖,𝑝𝑟𝑒\n\n\n\n1\n𝑝𝑖\n\n\n\n<mark>4.</mark> <mark>Using the entire LSMS-ISA sample, we run a multivariate logistic regression in which the</mark>\n<mark>dependent variable is a binary variable that is equal to 1 for LSMS-ISA households that</mark>\n<mark>were successfully interviewed for the phone survey and equal to 0 otherwise. The</mark>\n<mark>independent variables included represent a range of household, dwelling, and head of</mark>\n<mark>household attributes that predict the likelihood of a completed phone survey interview.</mark>\n\n\n18", "source": "general_prwp", "subset": "annotate_aivin_part2", "spans": [{"key": "prwp:002105:19:2:0", "start": 69, "end": 84, "surface": "LSMS-ISA sample", "probe_tag": "confusion", "probe_score": 0.7654, "luna_label": 1, "luna_reason": "Existing LSMS-ISA sample is used in multivariate logistic regression."}]}, {"key": "aivin2-232", "text": "rio de enumeración” <sup>36</sup> consistente\nen siete preguntas con filtros de aplicación\nque exploraban el historial migratorio del\nhogar. El objetivo del formulario fue clasificar\na la población entre hogares de estudio\n(hogares en los que al menos una persona\nreportara haber cambiado de residencia\nal interior de Honduras entre 2004 y 2014\npor causas relacionadas con violencia o\ninseguridad) y hogares de comparación. <sup>37</sup> [^37: Para el estudio, se entiende por hogar a una o varias\npersonas, unidas o no por vínculos familiares, que viven\njuntas para proveer y satisfacer sus necesidades alimenticias,\nque habitan una vivienda.]\n\n**Selección de hogares:** se determinó\nencuestar a todos los hogares de población\nde estudio encontrados en la enumeración\ny encuestar a uno de población de\ncomparación, seleccionado de forma\naleatoria, por cada tres hogares de estudio\nencontrados. En los casos en que se\nencontraron menos de tres hogares de\nestudio por segmento siempre se realizó una\nencuesta en los hogares de comparación.\n\n**Encuesta:** el instrumento de encuesta <sup>38</sup> [^38: Ver anexo II] se\ndiseñó para recopilar la siguiente información:\n\n- Datos de la vivienda: tipo, tenencia,\nservicios, etc.\n\n- Datos del hogar: activos, recursos,\nparticipación, redes sociales,\nintegración, etc.\n\n- Datos de las personas del hogar:\ncaracterísticas demográficas, migración,\nsalud, educación, empleo, etc.\n\n- Historial de migración y hechos\nvictimizantes\n\n- Intenciones futuras\n\n\n36 Ver anexo I\n37 Para el estudio, se entiende por hog", "source": "reliefweb", "subset": "annotate_aivin_part2", "spans": [{"key": "sample:reliefweb:001615:26:2:0", "start": 1169, "end": 1189, "surface": "Datos de la vivienda", "probe_tag": "drop", "probe_score": 0.046, "luna_label": 0, "luna_reason": null}, {"key": "sample:reliefweb:001615:26:2:1", "start": 1226, "end": 1241, "surface": "Datos del hogar", "probe_tag": "confusion", "probe_score": 0.2977, "luna_label": 0, "luna_reason": null}, {"key": "sample:reliefweb:001615:26:2:2", "start": 1314, "end": 1345, "surface": "Datos de las personas del hogar", "probe_tag": "confusion", "probe_score": 0.3922, "luna_label": 0, "luna_reason": null}]}, {"key": "aivin2-233", "text": " (a) Designated Account (DA) denominated in U.S.\ndollars where disbursements from IDA will be deposited and payment in U.S. dollars will be made from and (b)\nProject Account: This will be denominated in local currency. Transfers from the DA (for payment of transactions\nin local currency) will be deposited on this account in accordance with project objectives.\n\n\n27. The signatories for the project accounts will be in accordance with the Public Finance Management Act,\nTreasury Accounting Instructions, and the National Information Technology Authority Act 2009.\n\n\n**Disbursement Arrangements**\n\n\n28. The project will be on a Report Based Disbursement Method. An initial disbursement will be deposited in\nthe project DA based on a six-month cash flow forecast for the project based on the approved work plan.\nSubsequent disbursement will be based on the semi-annual IFRs submitted to the World Bank together with the\nrelevant applications. The IFRs will be submitted for disbursement every six months as a minimum but can submit\nmore requests as need arises. In compliance with the report-based guidelines, the project will be expected to: (a)\nsustain satisfactory FM rating during project supervision, (b) submit IFRs consistent with the agreed form and\ncontent within 45 days of the end of each reporting period, and (c) submit a Project Audit Report by the due date.\n\n\nPage 59 of 76", "source": "refugee_pads", "subset": "annotate_aivin_part2", "spans": [{"key": "refugee_pads:000075:71:1:0", "start": 856, "end": 872, "surface": "semi-annual IFRs", "probe_tag": "confusion", "probe_score": 0.3325, "luna_label": 0, "luna_reason": "Interim financial reports support project disbursement administration, not substantive data analysis."}]}, {"key": "aivin2-234", "text": "the Government of Chad assists with their resettlement in four designated areas. WFP gives\npriority to women as the designated recipients of vouchers or direct food transfers. For direct\nfood transfers, a local food management committee is established; WFP requires 50 percent of its\nmembers to be women.\n\n9. Vouchers will be distributed monthly at designated distribution sites, where the\ncontracted NGO partners will check registration cards against the local beneficiary lists. Many\nrefugees and returnees have lost their national identification cards in their flight from CAR, so\nbeneficiaries of the food assistance component of the project will receive registration cards with\ntheir photos. To limit the possibility of unauthorized reproduction and redemption, each voucher\nwill also have a specific security code and a 3D printed hologram. Beneficiaries with vouchers\nand registration cards will enter shops or distribution areas set up by local traders, where they\ncan redeem the vouchers and collect commodities of their choosing, corresponding to the\nvoucher value. The voucher allows purchase of staple foods, legumes, oil, canned fish, tomatoes,\nand onions (14 items altogether). This approach gives individuals some flexibility in their food\nchoices, including the ability to obtain fresh foods. It also supports local markets and traders and\nstrengthens supply chains.\n\n10. Each partner NGO will reconcile its monthly distribution of vouchers against those\nredeemed by the traders and compensates the traders accordingly. The NGOs will receive\nadvanced funds, sufficient to cover one month’s distribution only, to pay the traders. Once those\nfunds are exhausted, an NGO must submit a verified, reconciled account of the use of those\nfunds to receive a further advance to handle the next month’s voucher distribution.\n\n11. Because agriculture is a highly seasonal occupation, and because everyone—the refugees,\nreturnees, and host population—depends highly on local markets to buy food, voucher provision\nin the lean season has the potential to trigger food price inflation, which would reduce the\npurchasing power of all of these groups. For that reason, direct food transfers will be", "source": "jdc_operational", "subset": "annotate_aivin_part2", "spans": [{"key": "sample:jdc_operational:000007:35:0:0", "start": 456, "end": 479, "surface": "local beneficiary lists", "probe_tag": "confusion", "probe_score": 0.3836, "luna_label": 1, "luna_reason": null}]}, {"key": "aivin2-235", "text": "Road\n\n\nof the resettlement plan, including the impacts physical relocation and time\nlikely to be needed to restore their livelihood and standards of living. The World\nBank preference is given to land-based resettlement strategies for displaced persons\nwhose livelihoods are land-based.\n\n\n**Difference of Ugandan Laws and the World Bank Policy on**\n\n\nThere are some difference between the World Bank Policy and the Ugandan laws on\nresettlement. While the Ugandan laws restrict themselves to fair, adequate and\nprompt compensation (Which is interpreted to mean cash), the World Bank policy\nextends it to providing alternative land and resettling the persons.\n\n\nThe World Bank requirements are more favorable to than the provisions of\nUgandan Law. The Government of Uganda does not wish to set precedents as to\ncompensation amounts. However, GOU is strongly committed to fulfill World Bank\nrequirements. Appropriate compensation approaches are therefore needed, with a\nfirst part of compensation meeting Ugandan Law requirements, and an additional uplift\naiming at with World Bank requirements where they are not complied with by the\nsole Ugandan provisions\n\n\n**Land Ownership**\n\n\nThere is a diversity of land ownership along the right of way but the most prominent\nland holding, according to the available is cadastral information and title deeds, and\nthe observations and discussions with the various communities, Mailo land is\nprominent between Kampala and Zirobwe. On the Mailo land tenure; there are\ndifferent ownership interests between the registered owners and lawful occupants.\nAll those with vested interests therefore will be treated fairly during the land\nacquisition and compensation. Serious scrutiny of ownership will be affected during\ncadastral survey and community consultations at the local level.\n\n\nFor the purposes of this road project, the following major categories of people will\nhave interest in the land to be affected:\n\n\nMailo land owners registered)\n\n\nCustomary land owners (on former public land-untitled)\n\nowners or bona- fide occupants on Mailo\nland)\n\n\nVarious attempts have been made to address developmental concerns arising from\nthese various systems with", "source": "fcv_pads_east_africa", "subset": "annotate_aivin_part2", "spans": [{"key": "fcv_pads_east_africa:014353:22:0:0", "start": 1307, "end": 1344, "surface": "cadastral information and title deeds", "probe_tag": "confusion", "probe_score": 0.1025, "luna_label": 1, "luna_reason": "Existing land records support a concrete finding about prominent Mailo land ownership."}]}, {"key": "aivin2-236", "text": " Climate Data Center, Washington D.C., 52p.\n\nKogan. F.N.: 2001. “Operational Space Technology for Global Vegetation Assessment”.\n\n_Bull. Amer. Meteor. Soc_ . **82**, 1949-1964.\n\nKogan, F.N.: 1997. “Global Drought Watch from Space”. _Bull. Amer. Meteor. Soc._, **78**,\n\n621-636.\n\nKogan, F.N.: 1990. “Remote sensing of weather impacts on vegetation in non\nhomogeneous areas”. _Int. J. Remote Sens.,_ **11**, 1405- 1419.\n\nKogan, F.N.: 1995. “Droughts of the Late 1980s in the United States as Derived from\n\nNOAA Polar Orbiting Satellite Data”. _Bull. Amer. Meteor. Soc_ . **76**, 655-668.\n\nMcCarthy, J., Canziani, O., Leary, N., Dokken, D., and White, K. (eds.): 2001. _Climate_\n\n_Change 2001: Impacts. Adaptation, and Vulnerability_ <u>. Third Assessment Report</u>\nof the Intergovernmental Panel on Climate Change, Cambridge University Press,\nCambridge.\n\nMendelsohn, R., Nordhaus, W., and Shaw, D.: 1994. \"The Impact of Global Warming on\n\nAgriculture: A Ricardian Analysis” _American Economic Review_ **84** : 753-771.\n\nMendelsohn, R., Dinar, A., and Sanghi, A.: 2001. \"The Effect of Development on the\n\nClimate Sensitivity of Agriculture\", _Environment and Development Economics_ **6,**\n85-101.\n\nMendelsohn, R. and Dinar, A.: 2003. “Climate, Water, and Agriculture”, _Land_", "source": "general_prwp", "subset": "annotate_aivin_part2", "spans": [{"key": "prwp:002629:40:1:0", "start": 504, "end": 538, "surface": "NOAA Polar Orbiting Satellite Data", "probe_tag": "confusion", "probe_score": 0.2153, "luna_label": 0, "luna_reason": "Bibliographic title in a reference-list entry, not evidence of data use."}]}, {"key": "aivin2-237", "text": "*\n**insufficient water access, and disability**,\nrespectively. <sup>13</sup> Based on the MSNA and\nOffice of the Prime Minister (OPM)/UNHCR\nestimates, approximately 5-7% of refugees\nhave a disability. <sup>14,15</sup>\n\nOther key vulnerabilities include household\ndemographic factors like female-headed\nhouseholds (FHHs) and households with\na high age dependency ratio (ADR).\nAccording to the MSNA, **64% of refugee**\n**households are female-headed** . <sup>16</sup> FSNA\nfindings indicate that FHHs are more likely\nto be food insecure. <sup>17</sup> Similarly, MSNA\nfindings indicate that single-female-headed\nhouseholds are more likely to have both\nfood and WASH needs. <sup>18</sup> The average ADR\namong refugee households is 1.7. Several\nsettlements had especially high average\nADRs, such as Palabek, Rhino Camp,\nRwamwanja, and Bidibidi, indicating a **high**\n**economic and social burden within the**\n**household** . <sup>19</sup>", "source": "reliefweb", "subset": "annotate_aivin_part2", "spans": [{"key": "reliefweb:001668:1:2:0", "start": 466, "end": 479, "surface": "FSNA\nfindings", "probe_tag": "confusion", "probe_score": 0.4269, "luna_label": 1, "luna_reason": "FSNA findings provide evidence that female-headed households are more food insecure."}]}, {"key": "aivin2-238", "text": "**B.** **Technical**\n\n\n61. Access to certified seed, fertilizer, equipment, and agricultural services will help to\nrestore and maintain livelihoods in the areas affected by the crisis and enable returnees, refugees,\nand host communities to become less dependent on food distribution. Agricultural production in\nChad remains essentially at the subsistence level, with limited marketable surplus. In this\ncontext, the challenge is first to ensure the short-term distribution of these agricultural goods and\nservices to generate a supply response. A critical assumption is that the proposed project will be\nable to restore the production capacity and improve food security of the beneficiary farmers and\nat the same time prevent malnutrition among the most vulnerable and affected groups, especially\nyoung children. The project will use a voucher system already implemented by WFP.\n\n62. A 2009 study reports that households rely on markets to meet 87 percent of their food\nconsumption needs. A more recent market assessment (March 2014) finds a similar pattern\namong newly arrived returnees and refugees from CAR. <sup>22</sup> [^22: “Etude des marchés des céréales en relation avec la sécurité alimentaire, les programmes de transferts monétaires\net les achats locaux,” World Food Programme, March 2014.] These findings point to a lack of\npurchasing power as the main constraint to adequate and diversified food intake. The market\nassessment indicates that the local food economy is robust and well integrated. WFP’s use of\nvouchers enhances markets for small-scale Chadian farmers as well as CAR returnees engaged in\nagricultural activities. This strategy will further enhance market integration and provide new\nopportunities for returnees, refugees, and the host population to contribute to and participate in\nthe local economy.\n\n\n**C.** **Financial Management**\n\n\n63. The PIU for the EAPSP is endowed with a financial management system that meets the\nBank’s financial management requirements. For the proposed project, the EAPSP will enter into\nservice agreements for supplies and technical assistance with WFP and FAO.", "source": "refugee_pads", "subset": "annotate_aivin_part2", "spans": [{"key": "refugee_pads:000019:26:0:0", "start": 1003, "end": 1020, "surface": "market assessment", "probe_tag": "confusion", "probe_score": 0.6944, "luna_label": 1, "luna_reason": "2014 market assessment provides findings about food-market patterns."}]}, {"key": "aivin2-239", "text": "s were estimated to have\nbeen driven by state-level conflict actors. In 2019, this dropped to 30 percent, with over half citing\ncommunal violence over property, livestock, and access to resources as drivers of their displacement.\n\n\n11. **Returns in South Sudan reflect pre-conflict patterns of population movement, with returnees**\n**being more likely to return to areas within or near their original villages/towns.** An IOM assessment\ncommissioned by the World Bank found <sup>30</sup> [^30: IOM “Draft Population Movement Analysis October 2019.”] that a large majority (87 percent) of IDPs and refugee returns\nare to areas of habitual residence, with relocation to third areas accounting for just 6 percent. <sup>31</sup> [^31: IOM DTM. The movements of the remaining 7 percent of returnees could not be clearly determined.] Most\nreturns are within the same county (64 percent) or within the same state (23 percent) with only a minority\n(13 percent) returning home from outside the state. <sup>32</sup> [^32: IOM DTM. Some displaced opt to settle more permanently in urban centers (as in Wau or Malakal) or may remain in cities\nbecause they are unable to return to their villages due to security concerns, or the occupation of their land and houses by other\ngroups (for example, Bor or Bentiu).] With an estimated urban population of 18 percent,\nmost returnees tend to be concentrated in rural and peri-urban areas where they remain vulnerable to\nshocks induced by climate volatility, administrative mismanagement, and ongoing conflict due to\nincreasing competition over resources, HLP, and access to basic services. Yet, urban areas are not immune\nto the impact of returns. A total of 34 identified urban agglomerations host only 5.4 percent of\nreturnee/IDP locations and host 24 percent of IDP camps and an estimated 14–18 percent of returnees. <sup", "source": "jdc_operational", "subset": "annotate_aivin_part2", "spans": [{"key": "jdc_operational:000058:6:1:0", "start": 731, "end": 738, "surface": "IOM DTM", "probe_tag": "confusion", "probe_score": 0.8241, "luna_label": 1, "luna_reason": "Named IOM displacement-tracking source cited for return-movement percentages."}]}]