The sexualised use of cannabis among young sexual minority men: “I’m actually enjoying this for the first time”
Bibliographic record
Abstract
The objective of this study was to identify how cannabis use features within the sexual lives of young sexual minority men who use substances, and how this might intersect with features of their contemporary socio-cultural contexts in a setting where non-medical cannabis was recently legalised: Vancouver, Canada. Forty-one sexual minority men ages 15 to 30 years were recruited between January and December 2018 to participate in in-depth, semi-structured 1-2 h interviews about their experiences of using substances (e.g. cannabis) for sex. Drawing on constant comparative analytic techniques, two themes emerged with regards to participants' perceptions of, and experiences with, the sexualised use of cannabis. First, participants described how they used cannabis for sex to increase sexual pleasure and lower inhibitions. Second, participants described using cannabis for sex to reduce feelings of anxiety and shame, and foster intimacy and connection with sexual partners. These findings identify how the sexualised use of cannabis functions as a 'strategic resource' for sexual minority men to deliberately achieve both physiological and psychoactive effects, while concurrently underscoring the extent to which the contexts, patterns and motivations associated with cannabis use for sex parallel those associated with this form of Chemsex.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".