An analysis of the implementation of PEPFAR's anti‐prostitution pledge and its implications for successful HIV prevention among organizations working with sex workers
Bibliographic record
Abstract
INTRODUCTION: Since 2003, US government funding to address the HIV and AIDS pandemic has been subject to an anti-prostitution clause. Simultaneously, the efficacy of some HIV prevention efforts for sex work in areas receiving US government funding has diminished. This article seeks to explain why. METHODS: This analysis utilizes a case story approach to build a narrative of defining features of organizations in receipt of funding from the President's Emergency Plan for AIDS Relief (PEPFAR) and other US funding sources. For this analysis, multiple cases were compiled within a single narrative. This helps show restrictions imposed by the anti-prostitution clause, any lack of clarity of guidelines for implementation and ways some agencies, decision-making personnel, and staff on the ground contend with these restrictions. RESULTS: Responses to PEPFAR's anti-prostitution clause vary widely and have varied over time. Organizational responses have included ending services for sex workers, gradual phase-out of services, cessation of seeking US government HIV funds and increasing isolation of sex workers. Guidance issued in 2010 did not clarify what was permitted. Implementation and enforcement has been dependent in part on the interpretations of this policy by individuals, including US government representatives and organizational staff. CONCLUSIONS: Different interpretations of the anti-prostitution clause have led to variations in programming, affecting the effectiveness of work with sex workers. The case story approach proved ideal for working with information like this that is highly sensitive and vulnerable to breach of anonymity because the method limits the potential to betray confidences and sources, and limits the potential to jeopardize funding and thereby jeopardize programming. This method enabled us to use specific examples without jeopardizing the organizations and individuals involved while demonstrating unintended consequences of PEPFAR's anti-prostitution pledge in its provision of services to sex workers and clients.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".