“It Depends on Who You Are, What You Are”: ‘Community Safety’ and Sex Workers’ Experience with Surveillance
Bibliographic record
Abstract
Community safety has complex connotations for sex workers. This complexity is, in part, a function of the contradictory nature of ideas of community and the positioning of sex workers as both at-risk and risky, victims and criminals. ‘Community’ is simultaneously inclusive of everyone, including sex workers, and that which needs to be defended against the perceived dangers posed by sex work and sex workers. Denied in these contexts is any sense that harm may indeed flow from community to sex workers, not just the reverse. Drawing on data from a study with a diversity of sex working women in Toronto, Canada, this article argues that these contradictions are not the product of confusion, but in fact are constitutive of the ways in which communities are rhetorically and materially formed. They have structured legislative responses to sex work, reflect normative conceptions of community, bodies, and public space, and have actively produced unsafe and insecure conditions for sex workers. Indeed, sex workers themselves consistently identify the contradictory nature of ideas of community and the harm that flows from them. This is strongly evident in one of the key ways in which projects for ‘community safety’ are currently implemented, namely the installation of Closed Circuit Television Cameras (CCTV).
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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 | 0.010 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.030 | 0.037 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.004 | 0.007 |
| 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".