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Record W2140560363 · doi:10.1017/s0714980811000675

Unequal Social Engagement for Older Adults: Constraints on Choice

2012· article· fr· W2140560363 on OpenAlexaffabout
Julia Rozanova, Norah Keating, Jacquie Eales

Bibliographic record

VenueCanadian Journal on Aging / La Revue canadienne du vieillissement · 2012
Typearticle
Languagefr
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPrivilege (computing)PsychologyContext (archaeology)Social engagementAltruism (biology)Social psychologyGerontologySociologyMedicinePolitical science

Abstract

fetched live from OpenAlex

RÉSUMÉ Bien que les associations positives entre l’engagement et le bien-être social dans la vie ultérieure ont été confirmées par certaines études, cette étude visait à comprendre pourquoi certaines personnes ainées ne peuvent pas être impliquées. Les auteurs ont analysé des expériences vécues de 89 ainés demeurant dans trois communautés rurales au Canada, raconté dans les entrevues demi-structuré, utilisant la méthode de comparaison constante. Cinq facteurs font des choix pour l’engagement social dans la vie ultérieure inégale parmi les personnes ainées qui diffèrent par le sexe, la classe, l’âge, et le statut de santé. L’engagement profond dans le travail de soin, l’altruisme obligatoire, les ressources personnelles, les occasions d’implication perçues objectivement et subjectivement disponibles, et les barrières ageistes autour des activités désirées comme le travail contraignent des choix pour les aînés qui manquent le privilège dans l’économie du marché, notamment pour les vieilles femmes à faibles revenus. Pour éviter nuire et stigmatiser les plus vieilles personnes vulnérables, les barrières sociales aux activités significatives doivent être abordées – par exemple, par la provision de sécurité de revenu ou renversant la discrimination en raison de l’âge dans l’accès au marché du travail.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.397
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0050.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.041
GPT teacher head0.322
Teacher spread0.281 · 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.

Study designNot applicable
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

Citations65
Published2012
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal on Aging / La Revue canadienne du vieillissementSame topicEmployment and Welfare StudiesFrench-language works237,207