‘The Swarm Principle’: A Sub-National Spatial Analysis of Aid Targeting and Donor Coordination in Sub-Saharan Africa
Bibliographic record
Abstract
Do bilateral and multilateral foreign aid donors target poverty? To answer that question, we present a framework for assessing the quality of aid targeting sub-nationally. If donors cluster aid in areas with concentrated poverty, or spread out aid in areas of diffuse poverty, then we conclude that donors are targeting aid well. Furthermore, because co-financing may be a mechanism that improves coordination and information-sharing among donors, we examine whether the frequency of donor co-financing increases the quality of aid targeting. Recently released sub-national georeferenced foreign aid data for all bilateral and multilateral donors are available in five sub-Saharan African countries, making it possible to map the placement of foreign aid along with sub-national poverty levels. Results indicate that foreign donors target poverty in some countries but not others, and higher co-financing is associated with lower quality targeting across all cases.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".