Poverty Reduction StrategyPapers and their contributionto health: An Analysis of ThreeCountries
Bibliographic record
Abstract
Poverty Reduction Strategy Papers (PRSPs) represent the World Bank and the International Monetary Fund's (IMF) most recent initiative for reducing the plight of the poor. This paper examines whether the PRSPs for Liberia, Afghanistan and Haiti follow World Bank guidance on health. The health data, analysis and strategy content of the three PRSPs are assessed with respect to the 'Health, Nutrition and Population' chapter of the World Bank's PRSP Sourcebook. This guidance states that PRSPs should include: health data on the poor and a clear analysis showing the determinants of ill health and pro-poor health strategies. Unfortunately, none of the PRSPs analysed comply with the guidance and, consequently, do not adequately portray the health situation within their countries. Thus health is not given a high priority in the PRSP process and is seemingly low on the agenda of both poor country governments and the International Financial Institutions (IFIs). If the situation for the world's poorest people is to improve, health and the right to health need to be promoted within PRSPs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.017 | 0.040 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".