Gender and Ethnicity Differences in HIV-related Stigma Experienced by People Living with HIV in Ontario, Canada
Bibliographic record
Abstract
This study aimed to understand gender and ethnicity differences in HIV-related stigma experienced by 1026 HIV-positive individuals living in Ontario, Canada that were enrolled in the OHTN Cohort Study. Total and subscale HIV-related stigma scores were measured using the revised HIV-related Stigma Scale. Correlates of total stigma scores were assessed in univariate and multivariate linear regression. Women had significantly higher total and subscale stigma scores than men (total, median = 56.0 vs. 48.0, p<0.0001). Among men and women, Black individuals had the highest, Aboriginal and Asian/Latin-American/Unspecified people intermediate, and White individuals the lowest total stigma scores. The gender-ethnicity interaction term was significant in multivariate analysis: Black women and Asian/Latin-American/Unspecified men reported the highest HIV-related stigma scores. Gender and ethnicity differences in HIV-related stigma were identified in our cohort. Findings suggest differing approaches may be required to address HIV-related stigma based on gender and ethnicity; and such strategies should challenge racist and sexist stereotypes.
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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 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".