Minority Stressors, Social Provisions, and Past-Year Suicidal Ideation and Suicide Attempts in a Sample of Sexual Orientation and Gender Identity/Expression Minority People in Canada
Bibliographic record
Abstract
Purpose: Mental health disparities in sexual orientation and/or gender identity and/or expression (SOGIE) minority groups are well-documented, with research consistently showing higher levels of suicidality, even in Canada, considered one of the world's most accepting countries of SOGIE minority groups. Adverse outcomes in these groups are often framed using minority stress theory, with social support frequently studied as an integral buffer to these outcomes. This analysis explores facets of minority stress and social support associated with past-year suicidal ideation and suicide attempts. Methods: A cross-sectional internet survey of SOGIE diverse people in Canada ( n = 1542) was conducted. Binary logistic regression calculated bivariate and multivariate factors associated with past-year suicidal ideation and suicide attempts. Backward elimination (retaining sociodemographic factors and self-rated mental health) identified salient minority stress and social support (provisions) factors. Results: Over half (56.72%) of participants had ever thought of dying by suicide, with 24.84% having attempted suicide. During the past year, 26.80% had thought of dying by suicide, with 5.32% having attempted suicide. Victimization events, and guidance (e.g., someone to talk to about important decisions) and attachment (e.g., close relationships providing emotional security) social provision subscales remained salient after backward elimination procedures. Conclusion: Our findings emphasize that a fulsome, multilevel approach considering structural, community, and individual strategies to address overt discrimination, integrating social connections and guidance, is necessary to prevent dying by suicide.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".