Heterosexism, Depression, and Campus Engagement Among LGBTQ College Students: Intersectional Differences and Opportunities for Healing
Bibliographic record
Abstract
LGBTQ people experience health disparities related to multilevel processes of sexual and gender marginalization, and intersections with racism can compound these challenges for LGBTQ people of color. Although community engagement may be protective for mental health broadly and for LGBTQ communities in buffering against heterosexism, little research has been conducted on the racialized dynamics of these processes among LGBTQ communities. This study analyzes cross-sectional survey data collected among a diverse sample of LGBTQ college students (n = 460), which was split by racial status. Linear regression models were used to test main effects of interpersonal heterosexism and engagement with campus organizations on depression, as well as moderating effects of campus engagement. For White LGBTQ students, engaging in student leadership appears to weaken the heterosexism-depression link-specifically, the experience of interpersonal microaggressions. For LGBTQ students of color, engaging in LGBTQ-specific spaces can strengthen the association between sexual orientation victimization and depression.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".