MétaCan
Menu
Back to cohort

Social Capital and the Care Networks of Frail Seniors

2009· article· fr· W2008508311 on OpenAlexaffabout
Norah Keating, Donna Dosman

Bibliographic record

VenueCanadian Review of Sociology/Revue canadienne de sociologie · 2009
Typearticle
Languagefr
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsSocial capitalSociologyContext (archaeology)HumanitiesSocial mobilityPolitical scienceSocial scienceGeographyPhilosophy

Abstract

fetched live from OpenAlex

Le capital social a constitué un cadre important pour la conceptualisation de la place des liens sociaux dans la qualité de vie. La famille n'a pas fait partie des groupes d'intérêts dans les recherches sur le capital social. Néanmoins, dans le contexte de la recherche et de la politique publique sur le vieillissement, le discours contemporain sur les familles et sur les soins est congruent avec les hypothèses sur le capital social. Les auteurs s'inspirent de la documentation sur le capital social pour encadrer leur compréhension du capital social inhérent aux familles ayant des personnes âgées de santé fragile. Ils émettent l'hypothèse de leur capacité de bénéficier des soins des membres de la famille. Les données proviennent de l'Enquête sociale générale sur le vieillissement et le soutien social (ESG 2002) de Statistique Canada. Social capital has been a key framework in conceptualizing the place of social ties in quality of life. Families have not been among groups of interest in social capital research. Yet within the context of research and public policy on aging, the contemporary discourse on families and care is congruent with social capital assumptions. In this paper, we draw on social capital literature to frame our understanding of the social capital inherent in families of frail older adults, and hypothesize their abilities to benefit family members. Data are drawn from Statistics Canada 2002 General Social Survey on Aging and Social Support.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.642
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0010.009
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.033
GPT teacher head0.305
Teacher spread0.272 · 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 designTheoretical or conceptual
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

Citations54
Published2009
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Review of Sociology/Revue canadienne de sociologieSame topicHealth disparities and outcomesFrench-language works237,207