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Record W4385449660 · doi:10.3138/jcfs.54.1.060

How Do Wives and Husbands in Dual-Earner Couples in Korea Coordinate Work Hours and Childcare?

2023· article· en· W4385449660 on OpenAlexvenueno aff
Yun‐Suk Lee, Yoo-Jean Song

Bibliographic record

VenueJournal of Comparative Family Studies · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicWork-Family Balance Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsPaid workPsychologyWork (physics)Child careTime-use surveyWorking hoursWork hoursDevelopmental psychologyWork scheduleDual (grammatical number)Full-timeDemographic economicsSocial psychologyLabour economicsMedicineEconomicsNursingEconomic growth

Abstract

fetched live from OpenAlex

This study examined how dual-earner couples in Korea coordinate their work time to cope with childcare responsibilities and whether they employ tag-team parenting. Using the 2019 Korean Time Use Survey data, we assessed time spent in childcare and paid work among dual-earner couples with young children. OLS regression analysis was conducted separately for mothers’ and fathers’ childcare time, focusing on time spent on paid work and differences in work schedules. Mothers tend to leave for work later and head home earlier compared to fathers, presumably to take care of children. Couples worked longer separately than concurrently, and paid work time was strongly associated with one’s own and spousal time spent on childcare, supporting the desynchronization of work hours at the couple-level. Although the mother’s major responsibilities for childcare are still prevalent in Korea, couples tend to desynchronize working time with spouses so that one parent can be present with the children.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.162
Threshold uncertainty score0.652

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.094
GPT teacher head0.367
Teacher spread0.273 · 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 teacher head, 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

Citations1
Published2023
Admission routes1
Has abstractyes

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