MétaCan
Menu
Back to cohort
Record W4362719796 · doi:10.1016/j.fmre.2023.02.027

Spillover and crossover from work overload to spouse-rated work-to-family conflict: The moderating role of cross-role trait consistency

2023· article· en· W4362719796 on OpenAlexaff
Yunhui Huang, Yina Mao, Yujie Zhan

Bibliographic record

VenueFundamental Research · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicWork-Family Balance Challenges
Canadian institutionsWilfrid Laurier University
FundersNational Natural Science Foundation of China
KeywordsPsychologySocial psychologyTraitConsistency (knowledge bases)Work–family conflictJob satisfactionPersonalityContext (archaeology)BurnoutSpillover effectSpouseBig Five personality traitsPerceptionWork (physics)Clinical psychologyPolitical science

Abstract

fetched live from OpenAlex

While most previous research in social psychology shows benefits of individuals' consistency in personality across different social roles, the current study brings the concept of cross-role trait consistency to the context of management and examines its dark side. Data from 197 couples showed that an employee's work overload was positively associated with his/her spouse's perception of how much the employee's work interfered with family life. This relationship was mediated by the employee's job burnout. More importantly, this mediating relationship was moderated by the employee's cross-role trait consistency. These findings indicate that work overload may affect spouses' perception of employees' work-to-family conflict through job burnout, with the transmission of burnout on work-to-family conflict stronger among employees high in cross-role trait consistency. Thus, cross-role trait consistency appears to strengthen negative spillover and crossover from work to family. Theoretical and practical implications are discussed.

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)0.003
metaresearch head score (Gemma)0.012
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 score0.003
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.116
GPT teacher head0.415
Teacher spread0.299 · 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

Citations9
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueFundamental ResearchSame topicWork-Family Balance ChallengesFrench-language works237,207