MétaCan
Menu
Back to cohort
Record W2038867149 · doi:10.1037/a0020788

Spousal interrelations in happiness in the Seattle Longitudinal Study: Considerable similarities in levels and change over time.

2010· article· en· W2038867149 on OpenAlexaff
Christiane A. Hoppmann, Denis Gerstorf, Sherry L. Willis, K. Warner Schaie

Bibliographic record

VenueDevelopmental Psychology · 2010
Typearticle
Languageen
FieldPsychology
TopicAging and Gerontology Research
Canadian institutionsUniversity of British ColumbiaUniversity of British Columbia Hospital
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute on Aging
KeywordsHappinessPsychologySpouseLatent growth modelingDevelopmental psychologyLongitudinal studyAdult developmentLongitudinal samplePerspective (graphical)Social psychologySociology

Abstract

fetched live from OpenAlex

Development does not take place in isolation and is often interrelated with close others such as marital partners. To examine interrelations in spousal happiness across midlife and old age, we used 35-year longitudinal data from both members of 178 married couples in the Seattle Longitudinal Study. Latent growth curve models revealed sizeable spousal similarities not only in levels of happiness but also in how happiness changed over time. These spousal interrelations were considerably larger in size than those found among random pairs of women and men from the same sample. Results are in line with life-span theories emphasizing an interactive minds perspective by showing that adult happiness waxes and wanes in close association with the respective spouse. Our findings also complement previous individual-level work on age-related changes in well-being by pointing to the importance of using the couple as the unit of analysis.

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)0.002
metaresearch head score (Gemma)0.005
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 score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
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)0.0010.000

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 head0.196
GPT teacher head0.448
Teacher spread0.253 · 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

Citations68
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueDevelopmental PsychologySame topicAging and Gerontology ResearchFrench-language works237,207