Crystal Methamphetamine Use Among Female Street-based Sex Workers : Moving Beyond Individual-Focused Interventions
Bibliographic record
Abstract
Given growing concern of the sexual risks associated with crystal methamphetamine use and the dearth of research characterizing the use of methamphetamine among street-based sex workers (FSWs), this study aimed to characterize the prevalence and individual, social, and structural contexts of crystal methamphetamine use among FSWs in a Canadian setting. Drawing on data from a prospective cohort, we constructed multivariate logistic models to examine independent correlates of crystal methamphetamine among FSWs over a two-year follow-up period using generalized estimating equations. Of a total of 255 street-based FSWs, 78 (32%) reported lifetime crystal methamphetamine use and 24% used crystal methamphetamine during the two-year follow-up period, with no significant associations between methamphetamine use and sexual risk patterns. In a final multivariate GEE model, FSWs who used crystal methamphetamine had a higher proportional odds of dual heroin injection (adjOR = 2.98, 95%CI: 1.35–5.22), having a primary male sex partner who procures drugs for them (adjOR = 1.79, 95%CI: 1.02–3.14), and working (adjOR = 1.62, 95%CI: 1.04–2.65) and living (adjOR = 1.41, 95%CI: 1.07–1.99) in marginalized public spaces. The findings highlight the crucial need to move beyond the individual to gender-focused safer environment interventions that mediate the physical and social risk environment of crystal methamphetamine use among FSWs.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".