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Record W3176194940 · doi:10.3138/jcfs-52-2-005

Couples’ Relative Education and the Division of Domestic Work in France, Spain, and the United States

2021· article· en· W3176194940 on OpenAlexvenueno aff
Joan García Román

Bibliographic record

VenueJournal of Comparative Family Studies · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Labor, and Family Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsDivision of labourEarningsNormativeUnpaid workNegotiationInequalityDemographic economicsSociologySocioeconomic statusEconomicsWork (physics)Gender studiesPolitical sciencePopulationDemographySocial science

Abstract

fetched live from OpenAlex

The reversal of the gender gap in education and the emergence of couples in which the woman has a better economic or education status than her partner have been key shifts in family dynamics in recent decades. One of the consequences of this phenomenon is a more egalitarian division of tasks within couples, which is derived from the stronger resources of more educated women to negotiate roles. In this paper, I explored the division of unpaid domestic work in couples in France, Spain, and the United States (US), taking into account the level of education and the income of both members of the couple. The results show that hypogamous couples by education are more egalitarian than other types of couples, but the reversal of the gender gap in education has a relative effect on the division of housework. In that sense, better status in terms of earnings supposes more equality within the couple. However, gender inequalities persist even when the woman makes more money than her partner. A higher level of income is not sufficient to obtain more equality within the household, and other normative changes must be implemented in societies.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.287
Threshold uncertainty score0.699

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
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 head0.042
GPT teacher head0.357
Teacher spread0.315 · 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 designQualitative
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

Citations16
Published2021
Admission routes1
Has abstractyes

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