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Record W2552670066 · doi:10.3138/jcfs.41.1.167

Midlife Marital Happiness and Ethnic Culture: A Life Course Perspective

2010· article· en· W2552670066 on OpenAlexaffvenueabout
Barbara Mitchell

Bibliographic record

VenueJournal of Comparative Family Studies · 2010
Typearticle
Languageen
FieldPsychology
TopicPsychological Well-being and Life Satisfaction
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsHappinessEthnic groupLife course approachImmigrationPsychologySocial psychologyStressorReligiosityDemographyGender studiesSociologyGeographyClinical psychology

Abstract

fetched live from OpenAlex

It is well established that marital relationships remain integral to individual and family well -being and that some marriages are happier than others. It is also well documented that continuing high rates of immigration contribute 10 increasingly diverse marital patterns in Canadian society. Drawing from life course theory, the purpose of this paper is to further explore cultural, socio-demographic, and relationship factors and their association with midlife happiness. Data are drawn from in-depth interviews with a sample of 390 middle-generation married parents living in Metro Vancouver, British Columbia. Canada from four cultural groups: British, Chinese, lndo/East Indian, and Southern-European. Both quantitative and qualitative results reveal similarities in midlife marital happiness across these four cultural groups although perceived marital stressors underlying unhappy marriages vary across groups. Moreover, immigration status and religiosity are associated with greater marital happiness. Yet, relationship dynamic factors (i.e., intimacy satisfaction, doing activities together) surface as the most significant predictors of marital happiness. Implications for aging parental marital relations are also highlighted, with emphasis on those parents who are at greater risk for relationship stress, strain, or crisis.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.786
Threshold uncertainty score0.670

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 studies0.0000.001
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 head0.134
GPT teacher head0.458
Teacher spread0.325 · 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
Published2010
Admission routes3
Has abstractyes

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