Examining The Mental Health Experiences of LGBTQ+ Identifying Muslim Students in Ontario’s Post-Secondary Institutions
Bibliographic record
Abstract
This qualitative study explores the unique mental health experiences of Ontario’s LGBTQ+ Muslims in post-secondary settings. The study looks at how LGBTQ+ Muslim students’ mental wellness (i.e., sense of belonging, feeling affirmed in their intersecting identities of being Muslim and belonging to LGBTQ+ community) is affected as they try to navigate systemic barriers and make space for themselves in various settings (i.e., academic, LGBTQ+ affirming spaces, Muslim-specific spaces, student services) on campuses in Ontario, Canada. The study sample consists of four LGBTQ+ identified Muslim students across post-secondary institutions in Ontario and participants discussed their emotional, mental, and sense of belonging experiences on campus. Participants provide suggestions on improving the available support offered through their institutions. Key results from the thematic analysis of data suggest that the participants’ mental health are negatively impacted due to experiencing exclusion at various levels at educational institutions and such experiences impact their identity as LGBTQ+ Muslim students. Furthermore, institutions offer limited supports and resources. As a result, LGBTQ+ Muslim students seek resources outside of campuses, as well as peer support, to cope with these experiences of exclusion and sense of “unbelonging.” Additionally, due to the ongoing COVID-19 pandemic, LGBTQ+ Muslim students experience both positive and negative outcomes, such as loss of access to in-person communities on campus and connecting with other LGBTQ+ Muslims across the globe via online platforms. Participants recommend that culturally competent training for staff and faculty at these institutions be applied to create more inclusive and accessible spaces on campus.
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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 | 0.001 |
| Science and technology studies | 0.011 | 0.006 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 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".