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Record W2153186863 · doi:10.1177/2156869313504931

Spouse’s Work-to-family Conflict, Family Stressors, and Mental Health among Dual-earner Mothers and Fathers

2013· article· en· W2153186863 on OpenAlexaffabout
Marisa Young, Scott Schieman, Melissa A. Milkie

Bibliographic record

VenueSociety and Mental Health · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicWork-Family Balance Challenges
Canadian institutionsUniversity of TorontoMcMaster University
Fundersnot available
KeywordsSpousePsychologyStressorMental healthRespondentWork–family conflictClinical psychologySocial psychologyPsychiatryWork (physics)

Abstract

fetched live from OpenAlex

We examine the association between perceptions of spouse’s work-to-family conflict, family stressors, and mental health outcomes using data from a sample of 1,348 dual-earning parents from a 2011 national survey of Canadian workers. Based on crossover stress theory and the stress process model, we hypothesize that perceptions of spouse’s work-to-family conflict are associated with family stressors, which mediate the association between perceptions of spouse’s work-to-family conflict and respondent’s mental health. Using ordinary least square regression techniques, we find that perceptions of spouse’s work-to-family conflict are associated with mental health outcomes as well as secondary family stressors. Furthermore, the family stressors resulting from perceptions of spouse’s work-to-family conflict facilitate family-to-work conflict among respondents, which further explains the association between perceptions of spouse’s work-to-family conflict and mental health outcomes. We discuss the implications of these findings for theories of crossover stress and the stress process model.

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)0.003
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 score0.213
Threshold uncertainty score0.423

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.025
GPT teacher head0.304
Teacher spread0.279 · 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

Citations80
Published2013
Admission routes2
Has abstractyes

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