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Record W2141878657 · doi:10.1177/0192513x13508403

Gender Differences in Perceived Domestic Task Equity

2013· article· en· W2141878657 on OpenAlexaff
Marisa Young, Jean E. Wallace, Alicia J. Polachek

Bibliographic record

VenueJournal of Family Issues · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicWork-Family Balance Challenges
Canadian institutionsUniversity of CalgaryMcMaster University
Fundersnot available
KeywordsSpousePsychologyEquity (law)Social psychologyPerceptionInequalityWork–family conflictDemographic economicsWork (physics)EconomicsSociologyPolitical science

Abstract

fetched live from OpenAlex

Despite inequalities in domestic work, a majority of couples perceive this arrangement as fair. Our study addresses this paradox by examining whether and why married lawyers perceive domestic work arrangements as unfair to themselves or their spouse. Our results reveal that predictors of perceived equity to self and spouse differ substantially and that the antecedents of perceptions of unfairness vary by gender. That is, women working longer hours are more likely than men to perceive the distribution of tasks as unfair to their spouse. Furthermore, the association between spouse’s time-based conflict and perceived task equity is greater for men than women at lower levels of spouse’s time-based conflict, though the effects converge for men and women at higher levels of time-based conflict. Our findings highlight the value in taking a more nuanced approach to studying perceived inequity in the distribution of domestic tasks among men and women.

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)0.006
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 score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.095
GPT teacher head0.376
Teacher spread0.280 · 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

Citations33
Published2013
Admission routes1
Has abstractyes

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