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Record W4408700962 · doi:10.1080/26895269.2025.2478105

“I was lucky”: exploring the healthcare experiences of trans and non-binary youth in Alberta

2025· article· en· W4408700962 on OpenAlexafffundabout
Emilie Maine, Teresa L. D. Hardy, Kristopher Wells

Bibliographic record

VenueInternational Journal of Transgender Health · 2025
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsMacEwan University
FundersCanada Research Chairs
KeywordsHealth careBinary numberPolitical scienceMathematicsArithmeticLaw

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.604
Threshold uncertainty score0.984

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.095
GPT teacher head0.412
Teacher spread0.317 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2025
Admission routes3
Has abstractyes

Explore more

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