MétaCan
Menu
Back to cohort
Record W4408778876 · doi:10.1177/13591053251327263

Feeling ‘not enough’ or ‘too much’: Exploring how LGBTQ+ adults experiencing disability navigate Canadian health contexts

2025· article· en· W4408778876 on OpenAlexaffabout
Shannon S. C. Herrick, Erica Bennett, Andrea Bundon

Bibliographic record

VenueJournal of Health Psychology · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicDisability Rights and Representation
Canadian institutionsUniversity of British ColumbiaUniversity of Calgary
Fundersnot available
KeywordsAbleismHeterosexismThematic analysisFeelingHealth careQueerNarrativePsychologyQualitative researchHuman sexualityTransgenderNarrative inquiryLesbianGender studiesSocial psychologySociologyPolitical science

Abstract

fetched live from OpenAlex

Disability and LGBTQ+ communities experience healthcare disparities, however, most research has looked at these communities separately which erases the unique health experiences of people who belong to both. This project sought to explore intersections between gender, sexuality and disability within Canadian health contexts through three life-story interviews with seven adults (aged 25-35; 21 interviews total) who identified as LGBTQ+ and experiencing disability. Thematic narrative analysis resulted in interrelated themes associated with axes of self-identification that demonstrated how participants navigated tensions between being perceived as not disabled, trans and/or queer 'enough' or 'too much' within healthcare settings. Participants relayed stories of strategically omitting and/or sharing aspects of their intersectional identities with healthcare providers to receive the care they needed. This study, in demonstrating some of the difficult compromises and decisions LGBTQ+ adults who experience disability navigate to access healthcare, highlights how ableism, cis-heterosexism and racism intertwine to shape medical systems.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.606
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
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 head0.148
GPT teacher head0.481
Teacher spread0.333 · 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.

Study designNot applicable
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

Citations1
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Health PsychologySame topicDisability Rights and RepresentationFrench-language works237,207