Protection or police harassment? Impacts of punitive policing, discrimination, and racial profiling under end-demand laws among im/migrant sex workers in Metro Vancouver
Bibliographic record
Abstract
In 2014, Canada implemented end-demand sex work legislation which leaves the sale of sex under some circumstances legal. However, immigration policies based on discourses positioning sex work as exploitation and migration as trafficking continue to criminalize many im/migrant sex workers. Despite community reports of punitive policing, limited research has explored how police interactions with im/migrant sex workers have impacted labour conditions since this legislative shift. As part of a longstanding community-based Vancouver study, we drew on the conceptual framework of slow violence to analyze 20 in-depth interviews with sex workers born outside Canada. Despite rhetoric positioning im/migrant sex workers as victims deserving protection, participants described experiences of punitive, racialized, and stigmatizing police treatment. Fear of being 'outed' as a sex worker and living with precarious immigration status undermined participants' ability to seek police protections; yet when they did seek assistance after experiencing violence/theft, police were unsupportive or discriminatory. Our findings suggest that policies depicting im/migrant sex workers as victims act not to protect them, but to justify targeted repressive, racist policing that severely undermines women's occupational safety. Our results illustrate the harms of policies conflating sex work with trafficking; demonstrate the inherent opposition between legislative aims to protect those who sell sexual services and to abolish the sex industry; and interrogate who the state affirms as a deserving victim. The full decriminalization of sex work, removal of prohibitions on sex work among im/migrants, and community-led alternatives to the criminal justice system are urgently needed to uphold im/migrant sex workers' labour rights.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.007 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| 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".