Donor Agendas, Community Priorities and the Democracy of International HIV/AIDS Funding
Bibliographic record
Abstract
Each year, donors channel $7.6 billion into HIV programming in affected countries. With this funding often comes significant control over interventions at country level, though there is considerable skepticism about the value of donor-driven strategies. Locally conceived approaches are believed to be more effective, but it is not always clear that donors are responding accurately or appropriately to the priorities of communities. Concept notes submitted to the Global Fund to Fight AIDS, Tuberculosis and Malaria by eight African countries were systematically measured to determine their responsiveness to community priorities. National Civil Society Priorities Charters were used as a measure of community-identified needs. Malawi’s concept note was by far the most responsive to civil society priorities and Zambia’s was the least. The concept notes were the most responsive to civil society priorities on key populations’ issues, and the least responsible on priorities related to voluntary medical male circumcision. Statistically significant relationships were found between the responsiveness of Global Fund concept notes and Afrobarometer indicators on democracy, participation and civic engagement. There was also a significant relationship found between the voice and accountability rankings from the World Governance Indicators. This makes a compelling case to show that a context of democracy is linked to civil society’s ability to influence HIV/AIDS funding decisions at national level. Understanding the factors which hinder or enable community-led program development is critical for a more effective HIV response.
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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 | 0.027 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.007 | 0.013 |
| Scholarly communication | 0.014 | 0.005 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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".