Lack of Sexual Minorities' Rights as a Barrier to HIV Prevention Among Men Who Have Sex with Men and Transgender Women in Asia: A Systematic Review
Bibliographic record
Abstract
This study set out to assess the relationship between variation in human rights for sexual minorities in Asian countries and indicators of HIV prevention among men who have sex with men (MSM) and transgender women. To quantitatively measure the relationship between variation in HIV prevention and variation in human rights for sexual minorities, this study developed the Sexual Orientation and Gender Identity (SOGI) Human Rights Index (an original index with scores ranging from 0.0 to 1.0). Subsequently, this study collected 237 epidemiological and behavioral studies from 22 Asian countries and performed a series of meta-analyses in order to calculate national averages for five indicators of HIV prevention: HIV prevalence, inconsistent condom use, recent HIV testing, adequate HIV knowledge, and exposure to HIV prevention services. A change of human rights for sexual minorities from a score of 0.0 to 1.0 as measured by the SOGI Human Rights Index was correlated with a decrease in unprotected anal intercourse by 25.5% (p=0.075), and increases in recent HIV testing by 42.9% (p=0.011), HIV knowledge by 29.5% (p=0.032), and exposure to HIV prevention services by 37.9% (p=0.119). The relationship between HIV prevalence and variation in human rights for sexual minorities was not statistically significant. Our study found correlations between human rights and indicators of HIV prevention, further supporting the need for increased rights among marginalized populations. The paucity of studies from many Asian countries as well as the disparity in how indicators of HIV prevention are measured reveals a need for increased coverage and standardization of MSM serological and behavioral data in order to better inform evidence-based policymaking.
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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 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".