Internet solicitation linked to enhanced occupational health and safety outcomes among sex workers in Metro Vancouver, Canada 2010–2019
Bibliographic record
Abstract
OBJECTIVES: Examine the independent association between online solicitation and sex workers' (SWs') occupational health and safety (OHS), particularly violence and work stress. METHODS: Data were drawn from a cohort of women SWs (N=942, 2010-2019) in Vancouver, Canada. Analyses used descriptive statistics and bivariate and multivariable logistic and linear regression using generalised estimating equations (GEE); explanatory and confounder modelling approaches were used. RESULTS: 33.9% (n=319) of participants solicited online and 14.1% (n=133) primarily solicited online in the last 6 months in at least one study visit. In multivariable GEE analysis, factors associated with primarily soliciting online included younger age (adjusted OR (AOR) 0.95 per year older, 95% CI 0.93 to 0.97), sexual minority status (AOR 2.57, 95% CI 1.61 to 4.10), gender minority status (AOR 3.09, 95% CI 1.80 to 5.28), higher education (AOR 2.13, 95% CI 1.34 to 3.40), higher sex work income (AOR 1.03 per $100 weekly, 95% CI 1.01 to 1.06), being an im/migrant to Canada (AOR 2.40, 95% CI 1.26 to 4.58) and primarily servicing in informal indoor workspaces (AOR 3.47, 95% CI 2.32 to 5.20). In separate GEE confounder models, primarily soliciting online significantly (1) reduced odds of physical/sexual workplace violence (AOR 0.64, 95% CI 0.39 to 1.06) and (2) reduced work stress (β coefficient -0.93, 95% CI -1.59 to -0.26). DISCUSSION/CONCLUSIONS: Younger workers, gender/sexual minorities, im/migrants and those in informal indoor spaces had higher odds of soliciting online. Confounder models indicate access to online solicitation methods may support enhanced OHS. Decriminalisation of sex work-including advertising via online platforms-remains necessary to support SWs' OHS.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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 teacher head, 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".