Factors associated with condom use negotiation by female sex workers in Bangladesh
Bibliographic record
Abstract
Negotiation for condom use by female sex workers with their male clients can enhance condom use. A cross-sectional study was conducted among 1395 female sex workers; 439 from two brothels, 442 from 30 hotels, and 514 from streets of two cities in Bangladesh to determine the predictors of condom use negotiation. Consistent condom use rates in the 7 days prior to interview were reported to be 16.2%, 21.7%, and 4.5% among the brothel, hotel, and street-based female sex workers, respectively. Overall, 28.1% of female sex workers negotiated for condom use with their clients. Participation in behaviour change communication (BCC) programmes (AOR, 1.5; 95% CI, 1.2-2.0) and self-perceived risk of human immunodeficiency virus infection (AOR, 1.8 95% CI, 1.6-2.1) were positive predictors for condom negotiation. Compared to the hotel-based female sex workers, street (AOR, 0.6; 95% CI, 0.4-0.9) and brothel-based female sex workers (AOR, 0.7; 95% CI, 0.5-0.9) were less likely to negotiate for condom use. Female sex workers in Bangladesh are at high risk for sexually transmitted infection / human immunodeficiency virus infection because of low overall negotiation for condom use. Participation in BCC programmes had positive effect on condom negotiation by female sex workers, and should be strengthened in commercial sex venues.
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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 | 0.004 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".