Experiences of homonegativity and sexual risk behaviour in a sample of Latino gay and bisexual men
Bibliographic record
Abstract
This study examines the relationship between homonegativity, racism and poverty and HIV-risk-related behaviour among an Internet-based sample of 226 Latino gay and bisexual men. Participants had a median level of education at graduate school level or higher and a median monthly income in the US$1600-2400 range. Income and education in this sample are higher than participants in most other studies of Latino gay and bisexual men, providing information about HIV risk in a previously understudied segment of the population. Three negative binomial regressions were used to predict unprotected receptive anal intercourse, unprotected insertive anal intercourse and unprotected sex under the influence of drugs in the past 30 days, with education, Latino acculturation, income, experiences of racism and homonegativity as predictors. Greater experiences of homonegativity, fewer experiences of racism, lower income and higher Latino acculturation predicted unprotected receptive anal intercourse. Only lower Latino acculturation predicted unprotected insertive anal intercourse. Greater experiences of homonegativity, higher income and higher Latino acculturation predicted unprotected sex under the influence of drugs. This suggests that experiences of homonegativity have a detrimental impact on health behaviours. Future research should aim to further understand the relationship between experiencing homonegativity and engaging in risky sexual behaviour.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".