O12.1 Exploring relationship duration among gay and bisexual men: a longitudinal event-level analysis
Bibliographic record
Abstract
Background We characterized event-level relationship patterns of gay and bisexual men (gbMSM)’s long- and short-term with the goal of improving intimacy, well-being, and the control of sexually transmitted infections. Methods Between 2012–2015, sexually-active gbMSM, aged >16, were recruited in Metro Vancouver using respondent-driven sampling. Participants completed computer-assisted self-interviews at six-month intervals for up to 12 visits. At each visit, participants described their last sexual encounter with up to five of their most recent partners. Relationship duration was measured as the months between their first and most recent sexual encounter with each partner. Multivariable generalized estimating equations with RDS-chain, participant, and visit effects were used to identify sociodemographic, psychosocial, and behavioural factors associated with relationship duration. Results A total of 10,424 events were reported by 762 gbMSM (median=13/person, Q1-Q3:5–24). Median relationship duration was <1 month (Q1-Q3: 0–3) and the median number of sex events between partners was 1 (Q1-Q3: 1–1). Analyses indicate that longer relationship duration was associated with increasing age of participants (p<0.001); indigenous ethnicity (versus White; p=0.003); marijuana use before/during sex (p=0.014); and having met at a bathhouse (p=0.004), bar/club (p<0.001), through friends (p<0.001), or at another location (p=0.002; versus ‘online’). Shorter relationship duration was associated with higher communal altruism (p=0.019); bisexual identity (versus gay; p=0.004); Latin American ethnicity (versus White; p=0.028); living with HIV (p=0.0004); not knowing the event-level partner’s serostatus (p<0.001); engaging in insertive condom-protected anal sex with even-level partner (p=0.031); engaging in event-level group sex (p=0.001); and having sex at a park (p=0.004), hotel (p=0.043), private sex party (p=0.019), or other location (p=0.002; versus ‘home’). Conclusion Partner meeting location, personal identity, and risk management behaviours are key correlates of relationship duration – with shorter, often one-time, relationships being characterized by both risk (e.g., group sex, public sex, unknown partner serostatus) and risk management (e.g., condom use). Disclosure No significant relationships.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 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".