Sex Work, Health, and Human Rights
Bibliographic record
Abstract
Introduction\nThis open access book provides a comprehensive overview of the health inequities and human rights issues faced by sex workers globally across diverse contexts, and outlines evidence-based strategies and best practices.\nSex workers face severe health and social inequities, largely as the result of structural factors including punitive and criminalized legal environments, stigma, and social and economic exclusion and marginalization. Although previous work has largely emphasized an elevated burden and gaps in HIV and sexually transmitted infection (STI) services in sex work, less attention has been paid to the broader health and human rights concerns faced by sex workers. This contributed volume addresses this gap.\nThe chapters feature a variety of perspectives including academic, community, implementing partners, and government to synthesize research evidence as well as lessons learned from local-level experiences across different regions, and are organized under three parts:\n\nBurden of health and human rights inequities faced by sex workers globally, including infectious diseases (e.g., HIV, STIs), violence, sexual and reproductive health, and drug use\nStructural determinants of health and human rights, including legislation, law enforcement, community engagement, intersectoral collaboration, stigma, barriers to health access, im/migration issues, and occupational safety and health\nEvidence-based services and best practices at various levels ranging from individual and community to policy-level interventions to identify best practices and avenues for future research and interventions\n\nSex Work, Health, and Human Rights is an essential resource for researchers, policy-makers, governments, implementing partners, international organizations and community-based organizations involved in research, policies, or programs related to sex work, public health, social justice, gender-based violence, women's health and harm reduction.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".