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Record W2130041843 · doi:10.1080/03630241003601111

Women's Retirement and Self-Assessed Well-Being: An Analysis of Three Measures of Well-Being Among Recent and Long-Term Retirees Relative to Homemakers

2010· article· en· W2130041843 on OpenAlexaff
Michelle Pannor Silver

Bibliographic record

VenueWomen & Health · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicRetirement, Disability, and Employment
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPerspective (graphical)Well-beingTerm (time)PsychologyGerontologyHealth and Retirement StudyDepressive symptomsDemographyDemographic economicsMedicineEconomicsPsychiatrySociologyAnxiety

Abstract

fetched live from OpenAlex

Focusing on women from the U.S. over 60 years old in 2006, this study analyzed the relationship between retirement and three subjective measures of well-being: depressive symptoms, financial worries, and health. Drawing on the life course perspective and the heterogeneity of women's labor force experiences, this study contrasted the well-being of recent retirees with those who self-identified as homemakers (n = 1695) and long-term retirees with homemakers (n = 2012). Findings indicated that being a recent retiree was associated with more favorable reports of health and that being a long-term retiree was more favorably associated with accounts of all three outcome measures relative to homemakers. Thus, despite the major role change they experienced, findings support the notion that participating in the paid labor force may have been a protective factor with regard to self-assessed well-being.

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 score0.006
Threshold uncertainty score0.013

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.076
GPT teacher head0.375
Teacher spread0.298 · 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

Citations15
Published2010
Admission routes1
Has abstractyes

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