Examination of Identity Negotiation, Sexual Health Behavior, and Healthcare-Seeking Behavior of Transgender Sex Workers in India
Bibliographic record
Abstract
The current study, which expects to fill in the gap in research on transgender sex workers in India, examines the sexual identity negotiation, risk perception and condom compliance, sexual health screening and testing behavior, contextual barriers to healthcare seeking, and barriers to community mobilization among this population. The study was conducted in the red-light districts of Kolkata and rural subdivisions of West Bengal, and Eastern India. Transgender sex workers comprise 15% of the sex workers’ populace in India, yet they are an understudied and underserved group in the commercial sex sector. It is anticipated that the study will help to formulate future programmatic interventions that can cater more effectively to the health needs of Indian transgender commercial sex workers, contribute to the HIV/STI risk reduction among this group, and reduce barriers to attaining health.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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".