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Record W2582477890 · doi:10.1037/fam0000297

Better late than early: Marital timing and subjective well-being in midlife.

2017· article· en· W2582477890 on OpenAlexafffundabout
Matthew D. Johnson, Harvey Krahn, Nancy L. Galambos

Bibliographic record

VenueJournal of Family Psychology · 2017
Typearticle
Languageen
FieldPsychology
TopicPsychological Well-being and Life Satisfaction
Canadian institutionsUniversity of Alberta
FundersSocial Sciences and Humanities Research Council of CanadaUniversity of Alberta
KeywordsPsychologyPsycINFOHappinessDevelopmental psychologyPath analysis (statistics)Marital statusSubjective well-beingSocial supportNorm (philosophy)Social psychologyDemographyPopulationMEDLINE

Abstract

fetched live from OpenAlex

Drawing on data from 405 Canadian adults surveyed as high school seniors (Age 18) and again in midlife (Age 43), the present study examined whether marital timing, a variable rooted in the age norm hypothesis (whether marriage was early, on time, or late in relation to peers), might contribute additional insight into the well-documented association between marital status and subjective well-being (SWB; happiness, symptoms of depression, and self-esteem). The analysis also considered 3 alternative explanations of the marriage-SWB link: the social selection hypothesis, social role theory, and the adaptation perspective. Path analysis results demonstrated marrying on time or late compared with marrying early predicted fewer symptoms of depression in midlife, offering some support for the age norm hypothesis. Little support was found for the social selection hypothesis, but getting married and divorcing were consistently linked with future SWB, in accordance with social role theory. Marrying at an older age predicted higher self-esteem in midlife for men, implying potential adaptation. (PsycINFO Database Record

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)0.001
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 score0.179
Threshold uncertainty score0.922

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.047
GPT teacher head0.365
Teacher spread0.318 · 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

Citations14
Published2017
Admission routes3
Has abstractyes

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