Conceptualizing Geosexual Archetypes: Mapping the Sexual Travels and Egocentric Sexual Networks of Gay and Bisexual Men in Toronto, Canada
Bibliographic record
Abstract
BACKGROUND: There are complex, synergistic, and persistent sexually transmitted infection (STI) epidemics affecting gay, bisexual and other men who have sex with men (gbMSM) in every major urban centre across North America. We explored the spatial architecture of egocentric sexual networks for gbMSM in Toronto, Canada. METHODS: Our integrative mixed methods study included in-depth interviews with 31 gbMSM between May and July 2016. During interviews, participants mapped their egocentric sexual network for the preceding 3 months geographically. At the end, a self-administered survey was used to collect sociodemographic characteristics, online technology use, and STI testing and history. RESULTS: We identified 6 geosexual archetypes: hosters, house-callers, privates, rovers, travellers, and geoflexibles. Hosters always, or almost always (≥80%), hosted sex at their home. House-callers always, or almost always (≥80%), had sex at their partner's home. Rovers always or almost always (≥80%) had sex at public venues (eg, bath houses, sex clubs) and other public spaces (eg, parks, cruising sites). Privates had sex in private-their own home or their partner's (part hoster, part house-caller). Travellers had sex away from their home, either at a partner's home or some other venue or public space (part house-caller, part rover). Geoflexibles had sex in a variety of locations-their home, their partner's home, or public venues. All hosters and rovers, and to a lesser extent, geoflexibles, reported a history of syphilis and human immunodeficiency virus. CONCLUSIONS: Prioritizing interventions to hosters, rovers, and geoflexibles may have an important impact on reducing STI transmission.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.011 | 0.005 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".