Staying safe: how young women who trade sex in Toronto navigate risk and harm reduction
Bibliographic record
Abstract
Celling Sex was a community-based participatory research project that used a strengths-based approach to explore the agentic harm reduction practices employed by young women who trade sex and learn about their experience accessing health and social services. Fifteen racially diverse young women participated in interviews. They described how they tried to stay safe and advice for others. Each participant also individually made a brief digital video (cellphilm) to tell their story. Participants were invited to a private screening at which cellphilms were screened and common themes identified. The interviews and cellphilms were subsequently coded according to these themes. Participants identified a number of trading risks including: physical risks (unwanted pregnancy, STIs, and violence), social risks (racism and fetishisation), and mental health risks. To mitigate these concerns, participants detailed the harm reduction strategies they used which included use of technology, screening measures, boundary setting, and actively incorporating sexual health protections. Young women who trade sex are keenly aware of the risks inherent in transactional relationships and proactively negotiate and navigate harm reduction strategies in the context of deep systemic barriers. Further intervention may be necessary for them to actualise these strategies and access important forms of health and social support.
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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 | 0.002 | 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 | 0.001 | 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) | 0.000 | 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".