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Record W4399319836 · doi:10.1080/13639080.2024.2362630

Education, employment, and care work over adulthood: gendered life course trajectories in Canada and Germany

2024· article· en· W4399319836 on OpenAlexafffundabout
Janine Jongbloed, Johanna Turgetto, Lesley Andres, Wolfgang Lauterbach

Bibliographic record

VenueJournal of Education and Work · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Policy and Reform Studies
Canadian institutionsUniversity of British Columbia
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsLife course approachContext (archaeology)Welfare stateEducational attainmentWelfareGermanUnpaid workDemographic economicsSociologyWork–life balanceFamily lifeGender studiesWork (physics)PsychologyEconomic growthPolitical scienceEconomicsDevelopmental psychology

Abstract

fetched live from OpenAlex

This article compares the education, employment, and care work biographical sequences of Canadian and German women and men from late adolescence into mid-adulthood. Through the lenses of comparative gendered life course theory and welfare regime theory, sequence and cluster analyses are used to determine the adult life course sequences of women and men in each country and to assess the extent to which they differ across contexts. The analyses reveal clear gender differences in work–family balance in labour market participation and unpaid care work. Groups also differ strongly on educational attainment, income, and family composition. Comparatively, gender differences are less marked in the Canadian context. These results suggest that differing gendered trajectories result in diverse outcomes depending on the national context, shaping different outcomes for women cross-nationally. Our findings highlight how historical and contemporary country-specific welfare state policies support or hinder women as active and productive members of society.

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)0.002
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 score0.031
Threshold uncertainty score0.224

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.005
Science and technology studies0.0050.001
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.017
GPT teacher head0.333
Teacher spread0.316 · 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

Citations4
Published2024
Admission routes3
Has abstractyes

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