“What if this happiness doesn’t last forever?”: Stressors faced by racialized SOGIE refugees
Bibliographic record
Abstract
Racialized refugees with diverse SOGIE (Sexual Orientation, Gender Identity, and Expression) experience the unique intersection of racism, homo- and/or transphobia, and anti-refugee sentiments. As a result, this group (herein: racialized SOGIE refugees) often face poor mental health and well-being. The purpose of this study is to identify stressors faced by racialized SOGIE refugees in Ontario through the lens of Meyer’s Minority Stress Theory and Crenshaw’s intersectionality theory. The interviews from ten racialized SOGIE refugees and two service providers living in Ontario were taken from a larger study looking at the life trajectories of SOGIE refugees. Participants identified both explicit and implicit stressors in their daily lives, ranging from feelings of isolation and community disconnect, to anticipatory fear of stigma and violence. Consistent with the distinction of distal and proximal stressors proposed by Minority Stress Theory, this negatively affected their well-being. Our results point to a need to acknowledge the unique positionality of racialized SOGIE refugees in Ontario, and to find ways to facilitate positive mental health and well-being despite the presence of minority stress.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.012 | 0.006 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".