A Call to Disrupt Heteronormativity and Cisnormativity in Physical Therapy: Perspectives of 2SLGBTQIPA+ Participants on Future Directions for PT Curricula
Bibliographic record
Abstract
Purpose: To explore the perspectives of individuals with self-reported expertise and/or lived experiences regarding aspects of 2SLGBTQIPA+ health that should be included in pre-licensure physical therapy (PT) curricula across Canada, including how, when, and by whom this content should be delivered. Method: We conducted a critical qualitative, cross-sectional study with semi-structured virtual interviews. We analyzed participants' perspectives thematically using the DEPICT method. Results: Thirteen participants across Canada with a variety of gender identities and sexual orientations were interviewed. Participants described how transformative change on 2SLGBTQIPA+ issues in PT requires an approach that is based on interrupting heteronormativity and cisnormativity in PT curricula. Participants explained how this could be achieved by (1) emphasizing both historical inequities and present-day considerations for safe and inclusive practice, (2) introducing the content early and integrating it throughout the programme using a variety of large- and small-group sessions, and (3) including 2SLGBTQIPA+ individuals in content delivery and creation. Conclusions: This study brings attention to the need for the PT profession to understand how the pervasive social structures of heteronormativity and cisnormativity shape education and practice, and offer strategies for disrupting complicity with these systems of inequality.
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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 | 0.015 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.025 | 0.022 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".