T12-O-05 Projet polyvalence: HIV/AIDS and STD prevention with swingers in Montreal
Bibliographic record
Abstract
To determine the HIV/STD prevention needs of individuals with swingers (people who exchange their sexual partners) in Montréal. To develop HIV/STD prevention educational materials that respond to the identified needs of swingers Qualitative interviews with 30 swingers in Montréal. Interviews asked people to identify the kinds of educational material they would like to see. Recruitment in swinger newspapers, swinger bars, clubs and saunas, and mainstream media. Data analysis with a community based advisory committee whose members have extensive knowledge of swinger communities and practices. Development of educational posters based on the interviews (action component of the research). Swingers identified a need to present information relevant to their sexual lives and practices: for example, to speak about the need to change a condom if one changes sexual partners. Owners and managers of swinging establishments had few formal links with public health. Availability of condoms was cited as an important issue to be addressed by many participants. Need to develop HIV/STD education that is inclusive of swinger lifestyles (multiple partners) Need to increase prevention outreach in swinger bars, saunas, nightclubs, events Need to improve links between swinger establishments and public health Creation of educational poster with a website and phone number (www.polyvalence.ca)
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.001 |
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".