Examining the Academic Outcomes of 2SLGBTQ+ University Students in Ontario: Microaggressions and the Meditating Role of Psychological Well-Being
Bibliographic record
Abstract
Research on trans and LGBQ microaggressions on campuses and their consequences has grown, yet this literature is primarily from the United States and the effects of microaggressions on academic outcomes remain generally under-investigated. Trans/LGBQ microaggressions can negatively affect students’ psychological well-being, which matters for their academic outcomes, suggesting well-being might mediate the impact of microaggressions on academic outcomes. Using a convenience sample of 2SLGBTQ+ university students from Ontario (N = 3,344), we examine the association between trans/LGBQ microaggressions and academic satisfaction and school avoidance, testing if they are mediated by psychological well-being, controlling for demographics. We report findings for trans/LGBQ microaggressions separately to centre trans and gender-diverse (TGD) students’ experiences. For both groups, we found that microaggressions were associated with poorer academic outcomes. Except for one pathway among TGD students, we found that psychological well-being mediated the microaggressions–academic outcome relationships. We offer implications to support student services that are responsive to 2SLGBTQ+ students.
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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 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".