“I was lucky”: exploring the healthcare experiences of trans and non-binary youth in Alberta
Bibliographic record
Abstract
Background: Canadian healthcare is publicly funded, with the roles and responsibilities within the health care system divided between the federal, provincial and territorial governments. Provinces and territories have most of the responsibility for delivering health and other social services. There is a paucity of research exploring the specific health care experiences of transgender and non-binary youth in the province of Alberta. Aims: This study investigates the healthcare experiences of transgender and non-binary (TNB) youth (ages 14-25) in Alberta. The research within this paper highlights results from a larger qualitative research project exploring the wider experiences of TNB youth in Alberta. This paper focuses explicitly on healthcare themes emerging from our research project. Given the health disparities between cisgender and transgender youth, our study aims to provide insights into the experiences of TNB youth navigating and accessing healthcare within the province. Methods: Twenty-five participants were interviewed via semi-structured interviews. Results: This study identified five themes in the participants' experiences: medical provider's lack of knowledge; the youth feeling as though they were "getting lucky"; the effects and impact of wait times; the complexities of navigating the healthcare system; and feeling dignified in making informed choices. Conclusion: We recommend rescinding current discriminatory legislation and increasing dedicated funding and support for specialized gender-affirmative health clinics (including surgical capacity), social service agencies, and educational programs, as well as improved navigational supports.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.008 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.005 |
| 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".