Gender-based analysis of medical and aesthetic intervention needs and priorities of trans and non-binary people in Québec, Canada
Bibliographic record
Abstract
This study explored gender-specific needs and priorities in gender-affirming care among trans and non-binary (TNB) people in Québec, Canada. A cross-sectional study was conducted using a questionnaire distributed through organizations working with TNB people. This questionnaire included questions on four categories of gender-affirming interventions (hormonal interventions, facial interventions, upper/lower body interventions, and genital interventions) and open-ended questions. Descriptive bivariate analyses and chi-square tests were performed to describe participants (n = 223) and identify significant group differences. Participants identified as transmasculine (30.9%), transfeminine (37.7%), or non-binary (31.4%), with the greatest proportion (40.8%) aged between 26 and 40 years. Hormonal interventions represented the greatest need (95.5%) and the highest priority for all genders. Gendered differences were identified for all intervention needs, particularly for upper- and lower-body interventions (100% transmasculine, 63.1% transfeminine, 82.9% non-binary; p < 0.001) and facial interventions (18.8% transmasculine, 97.6% transfeminine, 41.4% non-binary; p < 0.001). Our study shows significant gendered differences in needs and priorities for gender-affirming interventions among TNB people in Québec. Our findings highlight the importance of inclusive, gender-responsive healthcare, and support broadening public coverage of gender-affirming interventions to ensure equitable access to care for TNB people.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".