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Record W3200814777 · doi:10.1177/08982643211042159

Couple Religiosity and Well-Being Among Older Adults in the United States

2021· article· en· W3200814777 on OpenAlexaff
Laura Upenieks, Jeremy E. Uecker, Markus H. Schafer

Bibliographic record

VenueJournal of Aging and Health · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicReligion, Spirituality, and Psychology
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsReligiosityPsychologyLatent class modelMental healthTraitSimilarity (geometry)GerontologyMarital statusDemographySocial psychologyMedicineSociologyPopulationPsychiatry

Abstract

fetched live from OpenAlex

Objectives: This article evaluates whether couples’ religious similarity is consequential for the health of older married men and women. Alternatively, we examine whether women’s religiosity alone is health-protective to their husbands . Methods: Using dyadic data from the US National Social Life, Health, and Aging Project, a representative sample of 913 individuals ages 62–91 plus their marital partners, we perform latent-class analysis to separate older couples into classes based on religious characteristics. Ordered logistic regression models are then used to assess whether different combinations of religious (dis)similarity are associated with married men and women’s well-being. Results: We find that older women in highly religious, homogamous marriages report better mental and physical health relative to women in heterogamous and secular (non-religious) marriages. No significant associations were observed for men. Discussion: Our results emphasize that religiosity is not only an individual trait—dis/similarities within a couple have important implications for older women’s 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 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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.173
Threshold uncertainty score0.977

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.026
GPT teacher head0.367
Teacher spread0.341 · 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.

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

Citations9
Published2021
Admission routes1
Has abstractyes

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