‘I was just doing what a normal gay man would do, right?’: The biopolitics of substance use and the mental health of sexual minority men
Bibliographic record
Abstract
Drawing on 24 interviews conducted with gay, bisexual, queer and other men who have sex with men (GBM) living in Toronto, Canada, we examined how they are making sense of the relationship between their mental health and substance use. We draw from the literature on the biopolitics of substance use to document how GBM self-regulate and use alcohol and other drugs (AODC) as technologies of the self. Despite cultural understandings of substance use as integral to GBM communities and subjectivity, GBM can be ambivalent about their AODC. Participants discussed taking substances positively as a therapeutic mental health aid and negatively as being corrosive to their mental wellbeing. A fine line was communicated between substance use being self-productive or self-destructive. Some discussed having made ‘problematic’ or ‘unhealthy’ drug-taking decisions, while others presented themselves as self-controlled, responsible neoliberal actors doing ‘what a normal gay man would do’. This ambivalence is related to the polarizing binary community and scientific discourses on substances (i.e. addiction/healthy use, irrational/rational, uncontrolled/controlled). Our findings add to the critical drug literature by demonstrating how reifying and/or dismantling the coherency of such substance use binaries can serve as a biopolitical site for some GBM to construct their identities and demonstrate healthy, ‘responsible’ subjectivity.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.029 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.005 |
| 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".