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Record W2559240781 · doi:10.7748/nop.2016.e852

Sociolegal and practice implications of caring for LGBT people with dementia

2016· article· en· W2559240781 on OpenAlexaboutno aff
Elizabeth Peel, Helen Taylor, Rosie Harding

Bibliographic record

VenueNursing Older People · 2016
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsLesbianAutonomyDementiaSexual orientationPsychologyComing outAffect (linguistics)Health careOlder peopleQuarter (Canadian coin)Gender studiesGerontologyMedicineSociologySocial psychologyDiseasePolitical science

Abstract

fetched live from OpenAlex

The needs of lesbian, gay, bisexual and trans (LGBT) people with dementia are poorly recognised. This is due partly to assumptions that all older people are heterosexual or asexual. One quarter of gay or bisexual men and half of lesbian or bisexual women have children, compared with 90% of heterosexual women and men, which means LGBT older adults are more likely to reside in care homes. Older LGBT people may be unwilling to express their sexual identities in care settings and this can affect their care. Members of older people's informal care networks must be recognised to ensure their involvement in the lives of residents in care settings continues. However, healthcare professionals may not always realise that many LGBT people rely on their families of choice or wider social networks more than on their families of origin. This article explores sociolegal issues that can arise in the care of older LGBT people with dementia, including enabling autonomy, capacity and applying legal frameworks to support their identities and relationships. It also highlights implications for 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 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)0.025
metaresearch head score (Gemma)0.046
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: none
Teacher disagreement score0.028
Threshold uncertainty score0.134

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0250.046
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0280.050
Scholarly communication0.0110.009
Open science0.0030.022
Research integrity0.0080.010
Insufficient payload (model declined to judge)0.0060.001

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 head0.034
GPT teacher head0.391
Teacher spread0.357 · 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

Citations16
Published2016
Admission routes1
Has abstractyes

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