Community-Based HIV and STI Prevention in Women Working in Indoor Sex Markets
Bibliographic record
Abstract
Community research into women's experiences in the indoor commercial sex industry illustrated an urgent need for sexually transmitted infection (STI) and HIV education, prevention, testing, and treatment and culturally appropriate services to support the sexual and reproductive health of commercial sex workers (CSWs). This work also revealed that a high number of immigrant--primarily Asian--women are involved in the indoor sex industry. In response, the authors developed a community-academic research partnership to design and implement a blended outreach research program to provide STI and HIV prevention interventions for indoor CSWs and their clients. This Community Health Worker Model HIV Prevention and Health Promotion Program incorporated health education, primary care referrals, STI testing using self-swab techniques, and a point-of-care HIV screening test. Here the authors report on program implementation, design, and the experiences of participants and team members and provide research and vaccination recommendations for future work in this area. This work work affirms that community-based service providers can be a key entry point for indoor CSWs to access health care and sexual health promotion and education and may be a solution to missed opportunities to provide culturally and contextually appropriate education and services to this population.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".