Client demands for unsafe sex : the socio-economic risk environment for HIV among street and off-street sex workers
Bibliographic record
Abstract
Objective Among sex workers (SWs) in Vancouver, Canada, this study identified social, drug use, sex work, environmental-structural and client-related factors associated with being offered and accepting more money after clients' demand for sex without a condom. Design Cross-sectional study using baseline (February/10-October/11) data from a longitudinal cohort of 510 SWs. Methods A two-part multivariable regression model was used to identify factors associated with two separate outcomes: (1) being offered and (2) accepting more money for sex without a condom in the last six months, among those who had been offered more money. Results The sample included 490 SWs. In multivariable analysis, being offered more money for sex without a condom was more likely for SWs who used speedballs, had higher average numbers of clients per week, had difficulty accessing condoms and had clients who visited other SWs. Accepting more money for sex without a condom was more likely for SWs self-reporting as a sexual minority and who had experienced client violence and used crystal methamphetamine use less than daily (vs. none), and less likely for SWs who solicited for clients mainly indoors (vs. outdoor/public places). Conclusions These results highlight the high demand for sex without a condom by clients of SWs. HIV prevention efforts should shift responsibility toward clients to reduce offers of more money for unsafe sex. Programs that mitigate the social and economic risk environments of SWs alongside the removal of criminal sanctions on sex work to enable condom use within safer indoor work spaces 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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".