Community acceptance and HIV sexual risk among gay and bisexual men in a ‘typical’ Canadian city
Bibliographic record
Abstract
Included in Statistics Canada's largest geographical “peer group,” London, Ontario is typical of many mid-size Canadian cities. A local health forum identified community acceptance and homophobia as key factors impacting LGBTQ health; we studied these with regard to HIV-related sexual risk in gay and bisexual men. Survey data were collected from 201 gay and bisexual men in Middlesex-London, Ontario; 173 reported their HIV status as negative/unknown and were included in this analysis. Unadjusted and adjusted prevalence risk ratios (PRRs) were modelled using modified Poisson regression. First, a model was fit for non-modifiable sociodemographic and background factors. Community factors were then added: social support; internalized homonegativity; perceptions of community acceptance of people like oneself (based on orientation, racialization, gender identity). Older age was associated with decreased risk; other sociodemographic and background factors were not. For each 10-year increase in age, prevalence of high-risk sex decreased by 24% (PRR=0.76; 95% CI: 0.60, 0.95). Controlling for age, we found an interaction between perception of broader community acceptance and gay community acceptance of people like oneself. As broader community acceptance increased, high-risk sex decreased; however, this effect varied depending upon perceptions of gay community acceptance, with men feeling most accepted within the gay community having the smallest reductions in high-risk sex. This interaction raises a series of questions. Among these: How do community norms and availability of partners shape sexual risk-taking? Are conventional “contextualized” measures of sexual risk sufficient, or do they miss important risk-mitigation strategies used within gay communities?
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".