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Record W2732417271 · doi:10.1093/geroni/igx004.2203

PREPARATIONS FOR END OF LIFE AMONG LGBT OLDER CANADIANS

2017· article· en· W2732417271 on OpenAlexaffabout
B. deVries, Gloria Gutman, Line Chamberland, Janet Fast, Jacqueline Gahagan, Áine M. Humble, Steven E. Mock

Bibliographic record

VenueInnovation in Aging · 2017
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsUniversity of WaterlooDalhousie UniversityMount Saint Vincent UniversityUniversité du Québec à MontréalUniversity of AlbertaSimon Fraser University
Fundersnot available
KeywordsTransgenderLesbianPsychologyGender studiesIntervention (counseling)Focus groupGerontologySexual minorityHuman immunodeficiency virus (HIV)MedicineSociologyFamily medicinePsychiatry

Abstract

fetched live from OpenAlex

Research over the last decade has documented the unique historical experiences and demographic characteristics of lesbian, gay, bisexual and transgender (LGBT) older adults. To explore the influence of these and other variables on end-of-life planning, focus groups were held in five Canadian cities (Vancouver, Edmonton, Montreal, Toronto, and Halifax) with lesbians and bisexual women (n=29), gay and bisexual men (n=39) and transgender individuals (n=23) age 55+. All groups described difficulty identifying potential caregivers and engaging others in discussion of end-of-life issues. Lesbians and bisexual women highlighted the need for community intervention, gay and bisexual men issues of trust and the legacy of HIV, transgender persons the insensitivity of health care settings. The findings show both similarities and differences between LGBT groups and while focused on the experiences of stigmatized sexual minority groups, have broad implications for others challenging traditional family norms. Service provider data (n= 26) compliment the LGBT data.

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)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.034
Threshold uncertainty score0.192

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0190.002
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0070.000

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 head0.060
GPT teacher head0.416
Teacher spread0.356 · 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 designObservational
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

Citations0
Published2017
Admission routes2
Has abstractyes

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