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Record W1983297178 · doi:10.1177/0733464812469292

“You Don’t Want to Ask for the Help” The Imperative of Independence

2013· article· en· W1983297178 on OpenAlexaffabout
Sheri Bell, Verena Menec

Bibliographic record

VenueJournal of Applied Gerontology · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsUniversity of ManitobaDalhousie University
Fundersnot available
KeywordsIndependence (probability theory)Social exclusionPsychologyFocus groupGerontologyIndependent livingQuality of life (healthcare)PhotovoiceSocial psychologySociologyPublic relationsPolitical scienceEconomic growthMedicine

Abstract

fetched live from OpenAlex

Independence is highly valued in Western society. The emphasis on independence and consequent fear of dependence may, however, have a downside, potentially leading to social exclusion. Through photovoice methodology, we explored what older adults say about the importance of independence in their lives and how independence may relate to social exclusion. Data consisted of photographs, journals, interviews, and focus group transcripts from 30 participants residing in Manitoba, Canada, collected as part of a larger program of research on "age-friendly" communities. Findings highlighted the importance of resources and supports to help older adults remain independent and feel included and that fear of dependence and being perceived as "old" can lead to social exclusion. Policy initiatives designed to make communities more age-friendly are one way to enhance older adults' independence and, ultimately, quality of life. It is equally important, however, that such initiatives go hand-in-hand with reimaging aging and old age.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.006
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.378
GPT teacher head0.574
Teacher spread0.195 · 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

Citations45
Published2013
Admission routes2
Has abstractyes

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