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Record W2141540140 · doi:10.1177/0193945913507635

Cultural Frames, Qualities of Life, and the Aging Self

2013· article· en· W2141540140 on OpenAlexafffundabout
Gail Low, Anita Molzahn, Mary Kalfoss

Bibliographic record

VenueWestern Journal of Nursing Research · 2013
Typearticle
Languageen
FieldPsychology
TopicAging and Gerontology Research
Canadian institutionsUniversity of Alberta
FundersSocial Sciences and Humanities Research Council of CanadaEuropean CommissionUniversity of VictoriaU.S. Department of Justice
KeywordsNorwegianPsychosocialPerceptionPsychologyGerontologyIndividualismSuccessful agingAffect (linguistics)Social psychologyMedicinePsychotherapist

Abstract

fetched live from OpenAlex

We used the Self-Concept Enhancement Tactician (SCENT) model to explore whether older Norwegians and Canadians would tactically self-enhance on qualities considered significant within their cultures in their self-perceptions of aging. Qualities were measured using the WHOQOL-BREF and WHOQOL-OLD. Self-perceptions of aging were measured by the Attitudes to Aging Questionnaire. The study is a secondary analysis of data collected in a larger study; 393 older Norwegians and 202 older Canadians were included. The Norwegian and Canadian group self-enhanced their perceptions of psychosocial loss based on harmonious social relationships and being part of a larger social group. For self-perceptions of physical change, both groups self-enhanced on being self-sufficient and being part of a larger social group. Our findings suggest that Norwegians and Canadians are not highly individualistic people and also provide evidence of a bicultural self-perception of aging. Nurses should consider how cultural and individual perspectives affect the care priorities of older people.

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)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.258
Threshold uncertainty score0.594

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.165
GPT teacher head0.501
Teacher spread0.336 · 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

Citations9
Published2013
Admission routes3
Has abstractyes

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