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Record W1917632159 · doi:10.1111/jomf.12026

Core Self‐Evaluations, Work–Family Conflict, and Burnout

2013· article· en· W1917632159 on OpenAlexaff
Victor Y. Haines, Steve Harvey, Pierre Durand, Alain Marchand

Bibliographic record

VenueJournal of Marriage and the Family · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicWork-Family Balance Challenges
Canadian institutionsCollège de MaisonneuveConcordia UniversityUniversité de Montréal
Fundersnot available
KeywordsWork–family conflictBurnoutPsychologyCore self-evaluationsSocial psychologyWork (physics)Scale (ratio)Empirical researchJob satisfactionClinical psychologyJob designJob performance

Abstract

fetched live from OpenAlex

This study investigated how core self‐evaluations relate to work–family (and family–work) conflict and burnout. Drawing from a sample of 289 police officers and civilian staff who were either married or living in a union as common‐law partners, this study advances an empirical integration of work–family and core self‐evaluations research. The results suggested that even when work, nonwork, and demographic variables are controlled for, positive core self‐evaluations (i.e., composite scale, self‐esteem, locus of control, emotional stability) are related to less work–family (and family–work) conflict. The associations between core self‐evaluations and burnout are partially mediated by work–family (and family–work) conflict. Finally, core self‐evaluations moderated the association between work–family conflict and burnout, but not the one between family–work conflict and burnout.

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)0.007
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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
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 head0.052
GPT teacher head0.316
Teacher spread0.264 · 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

Citations42
Published2013
Admission routes1
Has abstractyes

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