Conformity to Masculinity Norms and Mental Health Outcomes Among Gay, Bisexual, Trans, Two-Spirit, and Queer Men and Non-Binary Individuals
Bibliographic record
Abstract
Homophobia and biphobia negatively impact the mental health of gay, bisexual, trans, Two-Spirit, and queer men and non-binary individuals (GBT2Q) and sexual and gender minority men, but little is known about the impact of gender-related oppression. The current study examines the impact of pressure to conform to masculine norms in Canada-based GBT2Q individuals. Specifically, the associations between (a) gender expression and pressure to be masculine and (b) pressure to be masculine and depression, anxiety, and self-rated mental health were investigated. Drawing from an online national cross-sectional survey of 8,977 GBT2Q individuals and sexual and gender minority men living in Canada aged 15 years or older, 56.4% ( n = 5,067) of respondents reported experiencing pressure to conform to masculine norms. Respondents were more likely to report masculine pressure if they were younger than 30 years, described their gender expression as fluid, identified their sexuality as queer, were an ethnoracial minority, and were trans. Pressure to be masculine was associated with increased odds of depression, anxiety, and reporting poor or fair mental health. The current study provides evidence of the detrimental impact of pressure to conform to masculine norms on the mental health of gay, bisexual, trans, Two-Spirit, and queer men and non-binary peoples.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".