The role of sex work laws and stigmas in increasing HIV risks among sex workers
Bibliographic record
Abstract
Globally HIV incidence is slowing, however HIV epidemics among sex workers are stable or increasing in many settings. While laws governing sex work are considered structural determinants of HIV, individual-level data assessing this relationship are limited. In this study, individual-level data are used to assess the relationships of sex work laws and stigmas in increasing HIV risk among female sex workers, and examine the mechanisms by which stigma affects HIV across diverse legal contexts in countries across sub-Saharan Africa. Interviewer-administered socio-behavioral questionnaires and biological testing were conducted with 7259 female sex workers between 2011-2018 across 10 sub-Saharan African countries. These data suggest that increasingly punitive and non-protective laws are associated with prevalent HIV infection and that stigmas and sex work laws may synergistically increase HIV risks. Taken together, these data highlight the fundamental role of evidence-based and human-rights affirming policies towards sex work as part of an effective HIV response.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".