Policies in Poverty Reduction Strategy Papers: dominance or diversity?
Bibliographic record
Abstract
Poverty Reduction Strategy Papers (PRSPs) were introduced in 1999 by the World Bank and International Monetary Fund as a requirement for Heavily Indebted Poor Countries (HIPCs) to gain access to debt relief and concessional loans. They signalled a new focus by including a participatory framework of “nationally driven” policies. Employing 81 PRSPs for 58 countries, published during 2000–2008, this paper develops a unique scorecard to evaluate the alignment of policies in PRSPs with three dominant development paradigms. It finds that the New York Consensus, which was forged around the Millennium Development Goals (MDGs), is driving the content of PRSPs, while the Washington Consensus and Post-Washington Consensus have become secondary influences. This could be the first step in breaking down the hegemony of perceived ideas in the development policy landscape.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.140 | 0.250 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.014 | 0.028 |
| Science and technology studies | 0.008 | 0.018 |
| Scholarly communication | 0.031 | 0.022 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".