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Record W2141936378 · doi:10.1177/0020715214543541

Part-time work, women’s work–life conflict, and job satisfaction: A cross-national comparison of Australia, the Netherlands, Germany, Sweden, and the United Kingdom

2014· article· en· W2141936378 on OpenAlexvenueno aff
Anne Roeters, Lyn Craig

Bibliographic record

VenueInternational Journal of Comparative Sociology · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicWork-Family Balance Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsResidenceWork (physics)Job satisfactionTime-use surveyWorking timeLife satisfactionDemographic economicsWork–family conflictWork timePart-time employmentPolitical sciencePsychologySocial psychologyEconomics

Abstract

fetched live from OpenAlex

This study uses the International Social Survey Programme (ISSP) 2013 ‘Family and Changing Gender Roles’ module ( N = 1773) to examine cross-country differences in the relationship between women’s part-time work and work–life conflict and job satisfaction. We hypothesize that part-time work will lead to less favorable outcomes in countries with employment policies that are less protective of part-time employees because the effects of occupational downgrading counteract the benefits of increased time availability. Our comparison focuses on the Netherlands and Australia while using Germany, the United Kingdom, and Sweden as benchmarks. Part-time employment is prevalent in all five countries, but has the most support and protection in the Dutch labor market. We find little evidence that country of residence conditions the effects of part-time work. Overall, the results suggest that part-time work reduces work–life conflict to a similar extent in all countries except Sweden. The effects on job satisfaction are negligible. We discuss the implications for social policies meant to stimulate female labor force participation.

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 score0.030
Threshold uncertainty score0.059

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 communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
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 head0.131
GPT teacher head0.426
Teacher spread0.295 · 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

Citations57
Published2014
Admission routes1
Has abstractyes

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