Community-based Research with Eastern Canadian Sex Workers on the use of Information and Communication Technology to Manage Occupational Health and Safety
Bibliographic record
Abstract
In Canada, legal restrictions under Bill C-36 increase a sex worker’s occupational health and safety (OHS) risks by forcing the sex worker to work alone, placing the sex worker at risk for violence in the form of assault, robbery, non-negotiated sex acts, attempts to or removal of the condom, and clients trying to receive a sex act without paying for it. Other OHS risks experienced by sex workers are harassment, social isolation, and inadequate access to health services. To counteract these OHS risks, sex workers have begun using information and communication technologies (ICTs) to exchange tips and information. Through three interrelated studies, this dissertation seeks to understand how sex workers in Eastern Canada are currently using ICTs to access OHS information and manage OHS risks. Using a community-based research approach, and guided by the social ecological model, qualitative research methodologies were applied to gather insights as to whether the OHS information available via ICTs meets sex workers’ needs and explore sex workers’ suggestions for improvements in accessing OHS information. The first study in this dissertation, a scoping review, covers 12 countries, including Canada, and discusses the individual and institutional OHS risk mitigation strategies that sex workers access via ICTs. In the second study, 22 Eastern Canadian sex workers were interviewed. This study delivered a deeper understanding of the role ICTs play in a sex worker’s ability to find an online community where they can learn and exchange OHS strategies, and provided insights into the fragility of these communities, as the usage of ICTs for this purpose is prohibited by law. In the third study, a subset of sex workers from the previous study co-designed the digital prototype of a tool that could satisfy their needs for a central repository of OHS information. The overall vision for this digital OHS tool is a sex-worker friendly space, comprised of six core components: regional bad date resources, the work of sex work, supplies, STI information and education, sexual health, and harm reduction services. In designing their own OHS tool, sex workers apply their lived experience in mitigating the risks present in their profession.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.028 | 0.007 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".