Correlates of paid sex among men who have sex with men in Chennai, India
Bibliographic record
Abstract
OBJECTIVES: To assess correlates of paid sex among men who have sex with men (MSM) in Chennai, India. METHODS: A randomised survey was conducted among 200 MSM recruited from public sex environments using time-space sampling. The association of predictors with paid sex was assessed with chi(2) tests and multiple logistic regression. RESULTS: Participants' mean age was 28.5 years (SD 8.7). Most (71.5%) were kothis; 60% had less than high school education and two-thirds had a monthly income less than 2000 Indian rupees. More than one-third (35.0%) reported daily/weekly harassment; 40.5% reported forced sex in the past year. The prevalence of paid sex was 59.5% (95% CI 52.7% to 66.3%). Univariate analyses indicated that paid sex was associated with kothi identity (chi(2) = 14.46; p<0.01), less than high school education (chi(2) = 4.79; p<0.05), harassment (chi(2) = 11.75; p<0.01) and forced sex (chi(2) = 3.98; p<0.05). Adjusted analyses revealed that paid sex was associated with kothi identity (adjusted odds ratio (AOR) 2.62, 95% CI 1.34 to 5.10) and harassment (AOR 2.34, 95% CI 1.16 to 4.72). MSM who engaged in paid sex (versus no paid sex) had a mean of 31 partners in the past month (versus 4, t = 6.17, p<0.001) and 71.2% used condoms consistently (versus 46.4%, chi(2) = 18.34; p<0.01). Overall, 32.5% were never tested for HIV. CONCLUSIONS: Epidemic rates of harassment and sexual violence against MSM who engage in paid sex, predominantly kothis, suggest that interventions should target structural factors placing these men at increased risk of HIV/sexually transmitted infections and other health-compromising conditions. The effectiveness of individual-level, knowledge-based and condom-focused preventive interventions may be constrained in the context of poverty, low education, harassment and sexual violence.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".