Structural Violence Against<i>Kothi</i>–Identified Men Who Have Sex with Men in Chennai, India: A Qualitative Investigation
Bibliographic record
Abstract
This qualitative investigation explored the experiences and contexts of stigma and discrimination among HIV-positive and high-risk kothi-identified men who have sex with men (MSM) in Chennai, India, and ramifications for HIV prevention. MSM were recruited through community agencies (n = 10) and public sex environments (n = 8), along with three key informants. In-depth, semistructured interviews were conducted, audiotaped, and transcribed. Narrative thematic analysis and a constant comparative method were used to identify themes. Findings revealed multiple intersecting social and institutional contexts and experiences of stigmatization, discrimination, and violence across police, community, family, and health care systems, as well as illuminating consequences for MSM. Multisystemic structural violence places kothis at extreme vulnerability for HIV infection and AIDS. Public mass media antidiscrimination campaigns, education and training of health care providers and police, funding of indigenous MSM community organizations, and decriminalization of consensual sex between same-sex adults may help to combat stigma, discrimination, and violence against MSM, which is fundamental to effective HIV prevention.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.007 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.004 |
| 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".