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Record W7005698542

The role of chronic stress in the association between depressive symptoms and marital satisfaction

2009· dissertation· en· W7005698542 on OpenAlexfundno aff

Bibliographic record

VenueSummit (Simon Fraser University) · 2009
Typedissertation
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCell Image Analysis Techniques
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaSimon Fraser University
KeywordsDepressive symptomsAssociation (psychology)Context (archaeology)Chronic stressDepression (economics)Stress (linguistics)Marital status
DOInot available

Abstract

fetched live from OpenAlex

In an 18-month longitudinal study of 200 newlywed couples, growth curve analyses indicated that marital satisfaction and chronic stress interact to predict depressive symptoms. When chronic stress decreased over time, the association between changes in marital satisfaction and depressive symptoms was relatively weak, but when chronic stress increased, the association between marital satisfaction and depressive symptoms was stronger and more negative. Cross-spouse analyses generally indicated that when spouses experienced increases in chronic stress or higher average chronic stress across time points, the bidirectional association between wives’ depressive symptoms and husbands’ marital satisfaction became weaker and less negative. In sum, increases in chronic stress over the first year of marriage strengthened the within-spouse association between marital satisfaction and depressive symptoms but weakened the bidirectional cross-spouse association between husbands’ marital satisfaction and wives’ depressive symptoms. This highlights how the broader social context may put maritally distressed spouses at greater risk for depression.

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)0.004
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 score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.003
GPT teacher head0.207
Teacher spread0.204 · 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

Citations0
Published2009
Admission routes1
Has abstractyes

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