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Record W3122269903 · doi:10.1177/0733464820984893

“We Are Resilient, We Made It to This Point”: A Study of the Lived Experiences of Older LGBTQ2S+ Canadians

2021· article· en· W3122269903 on OpenAlexafffundabout
Arne Stinchcombe, Katherine Kortes-Miller, Kimberley Wilson

Bibliographic record

VenueJournal of Applied Gerontology · 2021
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsLakehead UniversityUniversity of GuelphBrock University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsGerontologyLesbianPsychological resilienceQueerTransgenderFocus groupSuccessful agingGender studiesPopulationPsychologyLife course approachPopulation ageingSociologyMedicineDevelopmental psychologySocial psychologyDemography

Abstract

fetched live from OpenAlex

Promoting health and well-being for older adults is a priority among many jurisdictions worldwide. Canada's population is aging and becoming increasingly diverse; one axis of a diverse aging population is aging members of lesbian, gay, bisexual, transgender, queer, and two-spirit (LGBTQ2S+) communities. We sought to examine the lived experiences of older LGBTQ2S+ people in Canada to understand the barriers and facilitators to healthy aging among members of these communities. A total of 10 focus groups were held in 10 cities from across Canada. Sixty-one older LGBTQ2S+ people (Mean age = 67) participated in the study. Data were analyzed using a constructivist grounded theory approach. Through analysis, we identified themes related to the importance of community capacity, resources, resilience, and personal histories in shaping aging experiences. The findings highlight the importance acknowledging diverse sexual and gender identities and the role of the life course in developing and implementing approaches that promote healthy aging.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.038
Threshold uncertainty score0.276

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0300.011
Scholarly communication0.0050.003
Open science0.0020.006
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0020.000

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 head0.052
GPT teacher head0.365
Teacher spread0.312 · 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 source (direct Gemma or distilled Codex), 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

Citations6
Published2021
Admission routes3
Has abstractyes

Explore more

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