Geosexual Archetype, Preventive Behaviors, and Sexually Transmitted Infections Among High-Risk Men Who Have Sex With Men
Bibliographic record
Abstract
BACKGROUND: Social geography plays an important role in transmission of sexually transmitted infections (STIs) among men who have sex with men. Previous qualitative work had identified 7 "geosexual archetypes," each with distinct travel patterns for sex and potentially important differences in STI rates. The objective of this article was to explore what could be learned about STI transmission by looking at STI prevention strategies (condom use and preexposure prophylaxis use) and prevalence of STIs among these geosexual archetypes. METHODS: We analyzed data from the Sex Now 2019 online survey in Canada. Men who have sex with men who reported 3 or more partners in the past 6 months were included in the analysis (n = 3649). RESULTS: The most common archetype was "geoflexible" (sex at home, partner's home, and other places; 35.6%), followed by "privates" (sex only at own/partner's home; 23.0%); the least common archetypes was "rover" (sex not at home or partner's place; 4.0%). There were significant variations in both STI prevention strategies and prevalence of bacterial STIs in the past year by geosexual archetype. In particular, among those who were HIV negative, those who reported a geoflexible archetype and used preexposure prophylaxis but did not use condoms consistently had a 52.6% prevalence of bacterial STIs, which was much higher compared with all other groups. Within other archetypes, those living with HIV had the highest prevalence of bacterial STIs. CONCLUSIONS: Geosexual archetype together with participant's STI prevention strategies was a strong predictor of bacterial STI risk. Understanding how place is connected to bacterial STIs is key in prevention as individuals do not live in isolation.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".