Survival Sex Work and Increased HIV Risk Among Sexual Minority Street-Involved Youth
Bibliographic record
Abstract
OBJECTIVES: Exchanging sex for money, drugs, or other commodities for survival is associated with an array of HIV risks. We sought to determine if street-involved drug-using sexual minority youth are at greater risk for survival sex work and are more likely to engage in risk behaviors with clients. METHODS: We examined factors associated with survival sex work among participants enrolled in the At Risk Youth Study using logistic regression. Self-reported risk behaviors with clients were also examined. RESULTS: Of 558 participants eligible for this analysis, 75 (13.4%) identified as a sexual minority and 63 (11.3%) reported survival sex work in the past 6 months. Sexual minority males (adjusted odds ratio = 16.1, P < 0.001) and sexual minority females (adjusted odds ratio = 6.87, P < 0.001) were at significantly greater risk for survival sex work. Sexual minority youth were more likely to report inconsistent condom use with clients (odds ratio = 4.30, P= 0.049) and reported a greater number of clients in the past 6 months (median = 14 vs. 3, P = 0.008). CONCLUSIONS: Sexual minority street youth are not only more likely to engage in survival sex work but also demonstrate elevated HIV risk behavior. These findings suggest that harm reduction and HIV prevention programs for sexual minority youth who exchange sex are urgently required.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.003 | 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".