Prevalence and structural correlates of gender based violence among a prospective cohort of female sex workers
Bibliographic record
Abstract
OBJECTIVE: To examine the prevalence and structural correlates of gender based violence against female sex workers in an environment of criminalised prostitution. DESIGN: Prospective observational study. SETTING: Vancouver, Canada during 2006-8. PARTICIPANTS: Female sex workers 14 years of age or older (inclusive of transgender women) who used illicit drugs (excluding marijuana) and engaged in street level sex work. MAIN OUTCOME MEASURE: Self reported gender based violence. RESULTS: Of 267 female sex workers invited to participate, 251 women returned to the study office and consented to participate (response rate of 94%). Analyses were based on 237 female sex workers who completed a baseline visit and at least one follow-up visit. Of these 237 female sex workers, 57% experienced gender based violence over an 18 month follow-up period. In multivariate models adjusted for individual and interpersonal risk practices, the following structural factors were independently correlated with violence against female sex workers: homelessness (adjusted odds ratio for physical violence (aOR(physicalviolence)) 2.14, 95% confidence interval 1.34 to 3.43; adjusted odds ratio for rape (aOR(rape)) 1.73, 1.09 to 3.12); inability to access drug treatment (adjusted odds ratio for client violence (aOR(clientviolence)) 2.13, 1.26 to 3.62; aOR(physicalviolence) 1.96, 1.03 to 3.43); servicing clients in cars or public spaces (aOR(clientviolence) 1.50, 1.08 to 2.57); prior assault by police (aOR(clientviolence) 3.45, 1.98 to 6.02; aOR(rape) 2.61, 1.32 to 5.16); confiscation of drug use paraphernalia by police without arrest (aOR(physicalviolence) 1.50, 1.02 to 2.41); and moving working areas away from main streets owing to policing (aOR(clientviolence) 2.13, 1.26 to 3.62). CONCLUSIONS: Our results demonstrate an alarming prevalence of gender based violence against female sex workers. The structural factors of criminalisation, homelessness, and poor availability of drug treatment independently correlated with gender based violence against street based female sex workers. Socio-legal policy reforms, improved access to housing and drug treatment, and scale up of violence prevention efforts, including police-sex worker partnerships, will be crucial to stemming violence against female sex workers.
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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".