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Record W1951167450 · doi:10.1111/apps.12004

The Link between National Paid Leave Policy and Work–Family Conflict among Married Working Parents

2013· article· en· W1951167450 on OpenAlexaff
Tammy D. Allen, Laurent Lapierre, Paul E. Spector, Steven Poelmans, Michael P. O’Driscoll, Juan I. Sánchez, Cary L. Cooper, Ashley G. Walvoord, Αλέξανδρος-Σταμάτιος Αντωνίου, Paula Brough, Sabine A. E. Geurts, Ulla Kinnunen, Milan Pagon, Satoru Shima, Jong‐Min Woo

Bibliographic record

VenueApplied Psychology · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicWork-Family Balance Challenges
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsSick leaveWork–family conflictWork (physics)Family LeavePerceptionPsychologyParental leavePaid workFamily conflictDemographic economicsSocial psychologyPolitical science

Abstract

fetched live from OpenAlex

We investigated relationships between four dimensions of work–family conflict (time‐ and strain‐based work interference with family, time‐ and strain‐based family interference with work) and three key national paid leave policies (paid parental leave, paid sick leave, paid annual leave) among a sample of 643 working married parents with children under the age of 5 across 12 industrialised nations. Results provided some evidence that paid sick leave has a small but significant negative relationship with work–family conflict. Little evidence was revealed of a link between paid parental leave or of a link between paid annual leave and work–family conflict. Family‐supportive organisational perceptions and family‐supportive supervision were tested as moderators with some evidence to suggest that paid leave policies are most beneficial when employees' perceptions of support are higher than when they are lower. Family‐supportive organisational perceptions and family‐supportive supervision were both associated with less work–family conflict, providing evidence of their potential benefit across national contexts.

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 score0.019
Threshold uncertainty score0.037

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 studies0.0010.000
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 head0.065
GPT teacher head0.352
Teacher spread0.288 · 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

Citations87
Published2013
Admission routes1
Has abstractyes

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