MétaCan
Menu
Back to cohort
Record W4403625449 · doi:10.1177/07334648241295570

“I Needed to be That Voice”: A Multi-Party Study of the Healthcare and Social Service Experiences and Needs of Transgender and Gender-diverse Older Adults in Canada

2024· article· en· W4403625449 on OpenAlexafffundabout
Hannah Kia, Celeste Pang, Kaan Göncü, Brittany A. E. Jakubiec, Kinnon R. MacKinnon, Ingrid Handlovsky, Lori E. Ross

Bibliographic record

VenueJournal of Applied Gerontology · 2024
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsUniversity of VictoriaUniversity of British ColumbiaPublic Health OntarioYork UniversityUniversity of TorontoMount Royal University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsIntersectionalityFocus groupConceptualizationTransgenderOppressionQualitative researchSociologyContext (archaeology)Gender studiesGerontologyHealth carePsychologyMedicinePolitical sciencePoliticsSocial science

Abstract

fetched live from OpenAlex

The social contexts of transgender and gender-diverse (TGD) older adults remain under-examined. In this qualitative study, which involved six virtual focus groups with a total of 21 participants inclusive of TGD adults ages 50+, service providers, and community advocates, we sought to examine the healthcare and social service experiences and needs of TGD older adults in Canada. Drawing theoretically on critical gerontology and intersectionality, and methodologically on interpretive description, we examined the perspectives of different participant groups to develop insight into TGD older adults' issues and priorities in the context of their engagements with systems of care. Our findings revealed the role of histories of marginalization, precarity, contemporary sources of intersectional oppression, and resistance in shaping the experiences of this population, while also highlighting community-driven ground-up activities to address evolving needs. Drawing on this conceptualization, we explored the implications of our research for ongoing inquiry, policy, and practice.

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)0.000
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.267
Threshold uncertainty score0.430

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.109
GPT teacher head0.369
Teacher spread0.260 · 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

Citations4
Published2024
Admission routes3
Has abstractyes

Explore more

Same venueJournal of Applied GerontologySame topicLGBTQ Health, Identity, and PolicyFrench-language works237,207