Reducing stigma in healthcare and law enforcement: a novel approach to service provision for street level sex workers
Bibliographic record
Abstract
INTRODUCTION: Providing services for street level sex workers requires a multidisciplinary approach, addressing both health and safety concerns typical of their age and gender and those that arise specific to their line of work. Despite being a diverse population, studies have identified some specific health needs for sex workers including addictions treatment, mental health. Additionally, studies have shown a higher risk of physical and sexual assault for this population. The Persons at Risk program (PAR) in London, Ontario, Canada was started in 2005 to address the specific needs of street level sex workers by using a harm-reduction model for policing and healthcare provision. This qualitative study evaluated this model of care in terms of improving access to healthcare and essential police services for street level sex workers. METHODS: A total of 14 semi-structured interviews were conducted with current and former female street level sex workers enrolled in the PAR program. In addition, 3 semi-structured interviews were conducted with health and law enforcement professionals. The research team then analyzed and coded the transcripts using qualitative description to identify key themes in the data. RESULTS: Results indicated that participants represent a vulnerable population with increased safety concerns and healthcare needs relating to addictions, mental health and infectious disease. Despite this, participants reported avoiding healthcare workers and police officers in the past because of fear of stigma or repercussions. All participants identified the harm reduction approach of the PAR program as being essential to their continued engagement with the program. Other important aspects included flexible hours, the location of the clinic, streamlined access to mental health and addictions treatment and the female gender of the police and healthcare worker. CONCLUSIONS: The PAR program provides sex workers access to much needed primary healthcare that is flexible and without judgment. In addition, they are provided with a direct avenue to access law enforcement. We feel a similar model of care could be applicable to many cities across 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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.006 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".