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Record W2343866014 · doi:10.1177/0192513x16646146

Coresidential Union Entry and Changes in Commuting Times of Women and Men

2016· article· en· W2343866014 on OpenAlexaff
Philipp M. Lersch, Sibyl Kleiner

Bibliographic record

VenueJournal of Family Issues · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicWork-Family Balance Challenges
Canadian institutionsUniversity of Calgary
FundersEconomic and Social Research Council
KeywordsDemographic economicsPanel dataLabour economicsSurvey data collectionWork (physics)PsychologyEconomics

Abstract

fetched live from OpenAlex

Women, particularly those in coresidential unions, have previously been found to spend less time commuting to work than men. This gender gap among couples’ commuting has been linked to inferior labor market opportunities for women. How gender differences in commuting emerge on entering coresidence is underresearched, however. This study examines changes in commuting times at the transition from singlehood to coresidential unions using the British Household Panel Survey (1992-2008; N = 8,122 individuals). Results from fixed effects regression indicate that men increase their commuting time when entering coresidential unions. For childless women, entering coresidential unions is not associated with changes in commuting time. Mothers reduce their commuting time on entering coresidential unions. Changes in labor income and domestic housework responsibilities, previously suggested as likely explanations, are not found to contribute to observed changes in commuting among those entering coresidential unions in this study.

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)0.000
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 score0.020
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.025
GPT teacher head0.312
Teacher spread0.287 · 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

Citations7
Published2016
Admission routes1
Has abstractyes

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