Seeking sexual partners on the Internet. A marker for risky sexual behaviour in men who have sex with men
Bibliographic record
Abstract
Objective: In order to generate a generalizable estimate regarding risk for STI and HIV acquisition in men who have sex with men (MSM) who seek partners on the internet, we examined the sexual practices of MSM who seek partners on the internet compared to MSM who do not, using a community-based sample of MSM from British Columbia. Methods: ‘Sex Now’, a questionnaire that was developed to examine trends in sexual behaviour in gay men, was offered to men attending Gay Pride events throughout the province of British Columbia, Canada between May and August 2004. Logistic regression analysis was used to model the association between seeking sexual partners online and other variables of interest, using odds ratio as the measure of association. Results: Of the 2,312 MSM who completed the survey, 766 (33.1%) had used the internet to find a partner in the past year. In logistic regression analyses, MSM who found partners on the internet were more likely to have had more than 10 sexual partners in the past year (overall, insertive and receptive), and to engage in sexual activities in public venues. They were also more likely to agree with the statement “I think most guys in relationships have
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".