Bye Bye Binary: Exploring Non-Binary Youths' Experiences of Mental Health, Discrimination, and Community Belongingness
Bibliographic record
Abstract
In recent years, there has been an increase in research focusing on the impacts of social exclusion and discrimination on the mental health of transgender populations. Despite this, few studies have focused on the experiences of gender non-conforming, or “non-binary” individuals. This community-based participatory research (CBPR) study (N = 10) used the arts-informed method of body mapping, individual interviews, and group discussions to examine non-binary young peoples’ experiences of discrimination in relation to mental health. Participants consisted young people (ages 16-25) living in Waterloo, Ontario. A visual analysis, thematic analysis, and member-checking session were employed to analyze collected data. In the following thesis document, I present two manuscripts where I share a) a methodological reflection of engaging with qualitative and arts-based approaches, and b) results pertaining to mental health, discrimination, and community belongingness. I describe how I, a non-binary researcher, grappled with my positionality within the research context, theoretical frameworks, and commitments to undertaking research with and for community. Implications for institutional policy, curriculum, and pedagogy within post-secondary institutions are discussed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.013 | 0.001 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".