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Record W2121732903 · doi:10.1177/0192513x14522240

It’s About Time! Gender, Parenthood, and Household Divisions of Labor Under Different Welfare Regimes

2014· article· en· W2121732903 on OpenAlexaboutno aff
Jeff Neilson, Maria Stanfors

Bibliographic record

VenueJournal of Family Issues · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicWork-Family Balance Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsWelfareWelfare stateDemographic economicsTime-use surveyConvergence (economics)Ordinary least squaresMultinational corporationBalance (ability)EconomicsParental leaveWork (physics)SociologyLabour economicsPolitical sciencePsychologyEconomic growthPolitics

Abstract

fetched live from OpenAlex

Having young children generally intensifies gendered patterns of time use. During the 1990s, this pattern changed in several Nordic countries, where welfare state arrangements support gender equality and work–family balance more comprehensively than elsewhere. We investigate the impact of parenthood on men’s and women’s time use across welfare state regimes, performing ordinary least squares regressions using data from the Multinational Time Use Study for Germany, Italy, and Canada ( N = 57,367 weekdays/53,292 weekends). We find convergence of men’s and women’s time use over the 1990s but uncover no strong evidence of the Nordic pattern emerging elsewhere. Instead, in countries with less comprehensive family policies and less support for gender equality, parenthood continued to reinforce traditional patterns of behavior on weekdays. There is evidence of change on weekends in Germany and Canada, where fathers became more involved domestically, but not in Italy, suggesting certain welfare state regimes may preserve gendered behavior more than others.

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 score0.050
Threshold uncertainty score0.099

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 studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.054
GPT teacher head0.325
Teacher spread0.271 · 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

Citations125
Published2014
Admission routes1
Has abstractyes

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