hivstigma.com, an innovative web-supported stigma reduction intervention for gay and bisexual men
Bibliographic record
Abstract
An intervention to address stigma directed toward HIV-positive men and to enhance the sexual health of gay and bisexual men was developed through a community-based process involving HIV prevention workers, public health, government and researchers. The intervention aimed to diminish stigma, create greater support for HIV-positive men, make disclosure safer and easier, discourage reliance on disclosure to prevent transmission and encourage testing. The question, 'If you were rejected every time you disclosed, would you?' was widely disseminated in the gay community and supported by the Web site, hivstigma.com, to encourage participation in blog-based discussions. Eight bloggers moderated lively discussions over 5 months. There were 20 844 unique visitors to the site averaging more than 5 min each; 4384 visitors returned more than 10 times. About 1,942 men answered a pre-test survey on a popular gay dating site and 1791, a post-test evaluation. Results show a statistically significant shift among those aware of the intervention toward reduced stigma-related attitudes and behaviors and toward recognition that HIV-positive gay men face stigma in the gay community and that stigma reduces the likelihood of HIV disclosure.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".