Accounts of HIV Seroconversion Among Substance-Using Gay and Bisexual Men
Bibliographic record
Abstract
Statistical associations between substance use and seroconversion among gay and bisexual men abound. However, these associations often ignore men's own interpretations of their seroconversion. Using in-depth interviews with gay and bisexual men who reported using drugs or alcohol at the time of their seroconversion, we identify how these men explain the events that led to HIV transmission. Whereas a small minority of respondents reported substance use to explain their seroconversion, the majority reported three competing explanations. These participants claimed that they lacked sufficient knowledge about the behavioral risks that led to their seroconversion; that their decision to engage in unsafe sex was because of negative personal affect; and that they "trusted the wrong person." We link these findings to prevention and suggest that gay and bisexual men who use substances for recreational purposes will benefit from prevention efforts designed to address issues of gay and bisexual men rather than substance-using men.
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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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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".