Depression in Lesbian, Gay, and Bisexual Members of the Canadian Armed Forces
Bibliographic record
Abstract
PURPOSE: Lesbians, gay men, and bisexuals have been shown to have different risks for mood and anxiety disorders than heterosexuals in population studies, but there is a paucity of research in this area in military populations. This study examined the relationship between sexual orientation and depression in the Canadian Armed Forces (CAF). METHODS: Data were drawn from the Canadian Forces Mental Health Survey 2013 (n = 8165), a representative sample of Regular and Reserve members of the Canadian military. Binomial logistic regression was used to predict 12-month and lifetime odds ratios for major depressive episode (MDE) stratified by sexual orientation and sex. RESULTS: Gay male members had higher risk (AOR = 3.80, 95% CI 1.60-9.05) for lifetime MDE, but not for past 12-month MDE compared to heterosexual males. There was no significant difference in risk for lesbians or bisexuals compared to heterosexuals. CONCLUSIONS: The results suggest that gay male members of the CAF are at higher risk for a history of MDE, but not current MDE. This may be a result of ongoing discrimination and stigma faced by gay men in the military or may reflect MDE that occurred before military service. The lack of difference in MDE risk for lesbian and bisexual members compared to heterosexual members is an important positive finding.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".