Offer of financial incentives for unprotected sex in the context of sex work
Bibliographic record
Abstract
INTRODUCTION AND AIMS: Commercial sex workers (CSW) are often portrayed as vectors of disease transmission. However, the role clients play in sexual risk taking and related decision making has not been thoroughly characterised. DESIGN AND METHODS: Participants were drawn from the Vancouver Injection Drug Users Study, a longitudinal cohort. Analyses were restricted to those who reported selling sex between June 2001 and December 2005. Using multivariate generalised estimating equation, we evaluated the prevalence of and factors associated with being offered money for sex without a condom. RESULTS: A total of 232 CSW were included in the analyses, with 73.7% reporting being offered more money for condom non-use, and 30.6% of these CSW accepting. Variables independently associated with being offered money for sex without a condom included daily speedball use [adjusted odds ratio (AOR) = 1.21, 95% confidence interval (CI): 0.23-0.62], daily crack smoking (AOR = 1.51, 95% CI: 1.04-2.19), daily heroin injection (AOR = 1.76, 95% CI: 1.27-2.43) and drug use with clients (AOR = 3.22, 95% CI: 2.37-4.37). Human immunodeficiency virus seropositivity was not significant (AOR = 0.98, 95% CI: 0.67-1.44). DISCUSSION AND CONCLUSIONS: Findings highlight the role clients play in contributing to unprotected sex through economic influence and exploitation of CSW drug use. HIV serostatus has no bearing on whether more money is offered for sex without a condom. Novel interventions should target both CSW and clients.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.022 | 0.001 |
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".