Stigma and HIV risk behaviors of transgender women in Nepal: implications for HIV prevention
Bibliographic record
Abstract
The growing HIV epidemic among Metis (i.e. transgender women) in Nepal has important implications for this at-risk population and the country overall. In order to develop interventions targeting this population, researchers must better understand the unique cultural context within which risk behavior occurs. This study was conducted to explore the social context of HIV risk behavior among Metis in Kathmandu, Nepal. Qualitative data were collected using in-depth interviews with fourteen Metis. These data were taken from a larger study with a purposeful convenience sample of men who have sex with men in Kathmandu, Nepal. Seven Metis reported currently being sex workers, while seven reported not currently engaging in sex work but having a history of providing sex for money. Utilizing a phenomenological approach, we found that stigma towards Metis resulting in discrimination by family members, law enforcement, and employers had an important effect on HIV risk for Metis. Specific HIV-related risks identified were rape and abuse by law enforcement officers leading to inconsistent condom use due to fear of carrying condoms in public. Low access and ability to carry condoms paired with high reported numbers of sexual partners revealed an environment ripe for the spread of HIV among Metis and their partners.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".