Family and community level stigma and discrimination among women living with HIV/AIDS in a high HIV prevalence district of India
Bibliographic record
Abstract
To examine HIV/AIDS-related stigma and discrimination in a high-HIV-prevalence district in India, we used data from a cross-sectional survey conducted recently among randomly selected married HIV-positive women, 15–29 years of age. Overall, 88% of respondents experienced stigma and discrimination from family and community. Factors associated with stigma and discrimination differed in the family and community contexts. Higher age gap between spouses and poor household status were significant in explaining the stigma and discrimination from husbands. Older age of the husband and lower household economic status significantly increased the stigma and discrimination from husbands’ family as well as from friends and neighbors. Different interventions should be developed for family and community contexts focusing on counseling for husbands, couples, family, and educational programs at the community level to reduce stigma and discrimination.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".