Criminalised Interactions with Law Enforcement and Impacts on Health and Safety in the Context of Different Legislative Frameworks Governing Sex Work Globally
Bibliographic record
Abstract
Abstract This chapter focuses on cis and trans sex workers’ experiences with law enforcement, and how various regimes of regulating sex work including full and partial criminalisation, legalisation, and decriminalisation shape the human rights and the work environments of sex workers globally including access to occupational health and safety, police protection, and legal recourse. Criminalisation and policing of sex work constitute forms of structural violence that perpetuate and exacerbate experiences of interpersonal violence and negative health outcomes among sex workers globally. Country spotlights from the global North and South provide examples of different regimes of regulation and draw attention to how laws and regulations interact with specific work environments in various settings to shape sex workers’ lived experiences of health, safety, and human rights. This chapter highlights how various approaches to criminalising and policing sex work undermine sex workers’ safety, health and human rights, including violence and poor health and concludes with an evidence-based call for the decriminalisation of sex work globally.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.012 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".