Student or educator? Sign up with your school email and get 6 months of Pro free.
CoChat
Sign Up
Cited by 451

The DOI matches its Crossref record; 525 of the 525 references it cites were found in a registry or an index.

Disentangling the relationship between gender and work–family conflict: An integration of theoretical perspectives using meta-analytic methods.

Shockley, Kristen M., Shen, Winny, DeNunzio, Michael M., Arvan, Maryana L., Knudsen, Eric A.·2017·Journal of Applied Psychology
DOI 10.1037/apl0000246
Open this paper in CoChat — free account

Abstract

Implicit in many discussions of work-family issues is the idea that managing the work-family interface is more challenging for women than men. We address whether this intuition is supported by the empirical data via a meta-analysis of gender differences in work-family conflict (WFC) based on more than 350 independent samples (N > 250,000 workers). Challenging lay perceptions, our results demonstrate that men and women generally do not differ on their reports of WFC, though there were some modest moderating effects of dual-earner status, parental status, type of WFC (i.e., time-, strain-, vs. behavior-based), and when limiting samples to men and women who held the same job. To better understand the relationship between gender and WFC, we engaged in theory-testing of mediating mechanisms based on commonly invoked theoretical perspectives. We found evidence in support of the rational view, no support for the sensitization and male segmentation perspectives, and partial support for the asymmetrical domain permeability model. Finally, we build theory by seeking to identify omitted mediators that explain the relationship between gender and work-interference-with-family, given evidence that existing theoretically specified mechanisms are insufficient to explain this relationship. Overall, we find more evidence for similarity rather than difference in the degree of WFC experienced by men and women. (PsycINFO Database Record

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1037/apl0000246

Cites

525 of 525 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Items 401–525 of 525

Cited by

See all 451

Metadata

Authors
Shockley, K. M., Shen, W., DeNunzio, M. M., Arvan, M. L., & Knudsen, E. A.
Venue
Journal of Applied Psychology
Publisher
American Psychological Association (APA)
Published
2017-12
Volume
102
Issue
12
Pages
1601-1635
ISSN
  • 0021-9010 (ISSN-L)
  • 1939-1854
DOI
10.1037/apl0000246
OpenAlex
W2739824782
Cited by
451
References
525
FWCI
92.25
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.