International Organizations and Ideas About Poverty in Sub‐Saharan Africa
Bibliographic record
Abstract
This study explores how international organizations (IOs) shape ideas about poverty and anti‐poverty policymaking in sub‐Saharan Africa (SSA). It argues that, beyond the use of conditionality, IOs significantly influence conceptions of poverty in SSA through various mechanisms, including technical assistance, personnel training, and capacity building, collaborating with civil society organizations, publications, conferences, seminars, and as think tanks. The analysis focuses on the World Bank (WB) and the Organization for Economic Co‐operation and Development (OECD), two organizations that have had a long‐standing relationship with SSA countries and have made significant contributions to development in the region. However, unlike the WB, whose activities in SSA are well known, the OECD's role in SSA is much less known. Therefore, this study broadens the discussion of the role of IOs in domestic policy development in SSA by incorporating the OECD. At the same time, the study offers a comparative perspective missing from empirical studies about IOs, which tend to focus on only one organization at a time.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.007 | 0.016 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.000 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".