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Record W2110698467 · doi:10.1177/0956797614533968

The Second Shift Reflected in the Second Generation

2014· article· en· W2110698467 on OpenAlexaff
Alyssa Croft, Toni Schmader, Katharina Block, Andrew Scott Baron

Bibliographic record

VenuePsychological Science · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicWork-Family Balance Challenges
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsVisionPsychologyWorkforceInequalityDivision of labourGender inequalityDevelopmental psychologySocial psychologyGender equalityGender studiesSociologyPolitical science

Abstract

fetched live from OpenAlex

Gender inequality at home continues to constrain gender equality at work. How do the gender disparities in domestic labor that children observe between their parents predict those children's visions for their future roles? The present research examined how parents' behaviors and implicit associations concerning domestic roles, over and above their explicit beliefs, predict their children's future aspirations. Data from 326 children aged 7 to 13 years revealed that mothers' explicit beliefs about domestic gender roles predicted the beliefs held by their children. In addition, when fathers enacted or espoused a more egalitarian distribution of household labor, their daughters in particular expressed a greater interest in working outside the home and having a less stereotypical occupation. Fathers' implicit gender-role associations also uniquely predicted daughters' (but not sons') occupational preferences. These findings suggest that a more balanced division of household labor between parents might promote greater workforce equality in future generations.

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)0.001
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 score0.011
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.001

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 head0.073
GPT teacher head0.389
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

Citations154
Published2014
Admission routes1
Has abstractyes

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