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Record W2071537678 · doi:10.1002/casp.857

The health of employed women and men: work, family, and community correlates

2006· article· en· W2071537678 on OpenAlexaff
Nazeem Muhajarine, Bonnie Janzen

Bibliographic record

VenueJournal of Community & Applied Social Psychology · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsUniversity of SaskatchewanSaskatchewan Health
Fundersnot available
KeywordsSpousePsychologyCommunity healthAssociation (psychology)GerontologyQuality (philosophy)Social psychologyPublic healthMedicineSociologyNursing

Abstract

fetched live from OpenAlex

Abstract Research into clarifying the relationship between social roles and health has increasingly focused on studying the particular circumstances in which occupying multiple roles may enhance or diminish well‐being. This study examined the association between a general measure of well‐being—self‐rated health—and the perceived quality of work, family and community in a sample of employed urban‐dwelling Canadians in a mid‐size city, and whether the nature of the association differed for men and women. Few gender differences were found in the perceived quality of work, family and community. However, men and women differed significantly in the specific type of quality measures associated with general health. For women, satisfaction with one's partner/spouse and in the money available to meet basic family needs had a stronger association with self‐rated health. For men, the significant correlates were satisfaction with family relationships (other than one's partner) and the community physical environment. For both women and men, a more socially cohesive community was associated with better self‐rated health. Copyright © 2006 John Wiley & Sons, Ltd.

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)0.002
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 score0.325
Threshold uncertainty score0.647

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.053
GPT teacher head0.392
Teacher spread0.339 · 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

Citations14
Published2006
Admission routes1
Has abstractyes

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