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Record W2144257333 · doi:10.1177/0164027514549258

Caregiver Well-Being

2014· article· en· W2144257333 on OpenAlexaffabout
Neena L. Chappell, Carren Dujela, André Smıth

Bibliographic record

VenueResearch on Aging · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicIntergenerational Family Dynamics and Caregiving
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsIntersectionalityPsychologyDementiaSelf-esteemCognitionGerontologyDevelopmental psychologyClinical psychologyMedicinePsychiatryGender studiesSociology

Abstract

fetched live from OpenAlex

We know much about caregiving women compared with caregiving men and caregiving spouses compared with caregiving adult children. We know less about the intersections of relationship and gender. This article explores this intersection through the well-being (burden and self-esteem) of caregivers to family members with dementia. Throughout British Columbia, Canada, 873 caregivers were interviewed in person for on average, over 1½ hours. The results reveal that daughters experience the highest burden but also the highest self-esteem, suggesting the role is less salient for their self-identities. Wives emerge as the most vulnerable of the four groups when both burden and self-esteem are considered. The data confirm the usefulness of the intersectionality framework for understanding co-occupancy of more than one status and indicate that positive cognitive well-being and negative affective well-being can be differentially related. Multivariate analyses confirm the importance of caregiver, not patient, characteristics for burden and self-esteem.

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)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.047
GPT teacher head0.409
Teacher spread0.362 · 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 designObservational
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

Citations159
Published2014
Admission routes2
Has abstractyes

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