Information and Communication Technologies in Commercial Sex Work: A Double-Edged Sword for Occupational Health and Safety
Bibliographic record
Abstract
Over the previous decade, there has been a notable shift within sex work marketplaces, with many aspects of the work now facilitated via the internet. Many providers and clients are also no longer engaging in in-person negotiations, opting instead for communications via technological means, such as through mobile phones, email, and the internet. By analysing the qualitative interviews of indoor-based providers, clients, and agency managers, this paper addresses the occupational health and safety concerns that indoor sex workers experience in the digital age, as well as how technology use can both support and hinder their capacity to promote their health and safety. Using thematic analysis, we arrived at three salient and nuanced themes that pertain to the intersection of sex work, technology use, and occupational health and safety: screening; confidentiality, privacy, and disclosure; and malice. As socio-political context can affect the occupational health and safety concerns that providers experience, as well as their capacity to prevent or mitigate these concerns, we highlight our findings in light of prevailing societal stigma and a lack of legal recognition and protections for sex work in Canada.
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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 | 0.011 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.021 | 0.042 |
| Scholarly communication | 0.022 | 0.010 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 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".