HIV infection among female sex workers in concentrated and high prevalence epidemics
Bibliographic record
Abstract
PURPOSE OF REVIEW: This article reviews the current state of the epidemiological literature on female sex work and HIV from the past 18 months. We offer a conceptual framework for structural HIV determinants and sex work that unpacks intersecting structural, interpersonal, and individual biological and behavioural factors. RECENT FINDINGS: Our review suggests that despite the heavy HIV burden among female sex workers (FSWs) globally, data on the structural determinants shaping HIV transmission dynamics have only begun to emerge. Emerging research suggests that factors operating at macrostructural (e.g., migration, stigma, criminalized laws), community organization (e.g., empowerment) and work environment levels (e.g., violence, policing, access to condoms HIV testing, HAART) act dynamically with interpersonal (e.g., dyad factors, sexual networks) and individual biological and behavioural factors to confer risks or protections for HIV transmission in female sex work. SUMMARY: Future research should be guided by a Structural HIV Determinants Framework to better elucidate the complex and iterative effects of structural determinants with interpersonal and individual biological and behavioural factors on HIV transmission pathways among FSWs, and meet critical gaps in optimal access to HIV prevention, treatment, and care for FSWs globally.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".