Mind the gap: predicting the positive mental health of adult sexual minority Canadians
Bibliographic record
Abstract
The goal of the study is to investigate possible predictors of positive mental health, and whether they differ across sexual identity adult groups. Using data from the 2012 Canadian Community Health Survey on Mental Health, multivariate analyses were conducted, including interaction terms, to assess the effects of sexual orientation on various mental illness, health-risk behaviors, and sociological indicators and their correlations with positive mental health. Substantial effect sizes were observed across all sexual identity groups for psychological distress, social provisions and sense of belonging in terms of their influence on positive mental health. However, various mental health disorders, suicidality, and whether or not care needs were being met varied considerably in the disaggregated analysis, suggesting that there are key differences among sexual minority groups when it comes to predicting positive mental health. This study represents perhaps the largest population-based analysis of positive mental health, which is both theoretically informed and psychometrically verified, on sexual minority adults. Findings raise important concerns regarding the lower than average levels of positive mental health for all sexual minorities, which may be explained, at least in part, to the health care system's tendency to focus primarily on individual treatment needs rather than broader socio-structural aspects within a mental health promotion framework.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".