Associations of sexual risk taking among Kenyan female sex workers after enrollment in an HIV-1 prevention trial.
Bibliographic record
Abstract
BACKGROUND: Female sex workers (FSWs) often lack the ability to negotiate safer sex and are at high risk for HIV-1 infection and sexually transmitted infections (STIs). METHODS: Seronegative FSWs were enrolled in an STI/HIV-1 prevention trial in Nairobi, Kenya. Demographics and sexual risk taking were assessed every 3 months. Predictors of reduced risk taking were defined using multivariate logistic regression. RESULTS: Four hundred sixty-six FSWs were enrolled and followed for just over 2 years each. A spectrum of sex work was apparent: FSWs working in night clubs were younger, charged more for sex, and used condoms more frequently; FSWs working from home were older, charged less, and used condoms the least; and those working in bars were intermediate. Increases in reported condom use were most significant and sustained for FSWs working from home and charging less for sex and were poorly maintained for bar-based FSWs. Self-reported lower condom use, higher client numbers, and alcohol use were associated with higher STI rates. CONCLUSIONS: Home-based FSWs and those charging less for sex used condoms the least at baseline but showed the greatest and most sustained improvements over time. Potential response heterogeneity in FSW subgroups should be considered in the design of HIV-1 prevention programs.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".