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Record W2989732031 · doi:10.1177/0192513x19888769

When Family Calls: How Gender, Money, and Care Shape the Relationship between Family Contact and Family-to-Work Conflict

2019· article· en· W2989732031 on OpenAlexafffundabout
Philip J. Badawy, Scott Schieman

Bibliographic record

VenueJournal of Family Issues · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicWork-Family Balance Challenges
Canadian institutionsUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsWork–family conflictWork (physics)Association (psychology)PsychologyFamily lifeSocial psychologyRole conflictSalientDevelopmental psychologySociologyPolitical scienceGender studies

Abstract

fetched live from OpenAlex

The fluid boundaries between work and family life and the dynamic ways these domains are shaped by communication technology represent an important area in work-family research. However, surprisingly little is known about how family contact at work affects functioning in the work role—especially how these dynamics may change and unfold over time. Drawing on longitudinal data from the Canadian Work, Stress, and Health Study (2011–2017), the present study examines the association between family contact and family-to-work conflict. We find that increases in family contact over time are positively associated with more family-to-work conflict, but gender and three salient family-related conditions—financial strain, providing care for family members, and difficulties with children—are key moderators of this focal relationship. We discover that the focal association is significantly stronger for women and for those with elevated levels of financial strain, caregiving responsibilities, and difficulties with children over time. We discuss these results by integrating border theory with stress amplification and the cost of caring.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.142
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.117
GPT teacher head0.344
Teacher spread0.227 · 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.

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

Citations17
Published2019
Admission routes3
Has abstractyes

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