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Cited by 355

The DOI matches its OpenAlex record; 15 of the 15 references it cites were found in a registry or an index.

Gender Ideology and Perceptions of the Fairness of the Division of Household Labor: Effects on Marital Quality

Theodore N. Greenstein·1996·Social Forces

Abstract

Under what circumstances will married women perceive inequalities in the division of household labor as unfair? This research develops and tests a model based on relative deprivation theory that suggests that gender ideology functions as a moderator variable in a process through which inequalities in the division of household labor come to be seen as inequities. Using data from the National Survey of Families and Households, three empirical tests of the model provide evidence that inequalities in the division of household labor are more strongly related to perceptions of inequity for egalitarian than for traditional wives, and that perceptions of inequity are more strongly related to perceived quality of the marital relationship for egalitarian than for traditional wives. The findings suggest that researchers studying the division of household labor need to shift their focus away from analyses of objective inequalities and toward the study of perceived inequity.

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OpenAlex · 10.1093/sf/74.3.1029

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Metadata

Authors
Greenstein, T. N.
Venue
Social Forces
Publisher
Oxford University Press
Published
1996-03-01
Volume
74
Issue
3
Pages
1029-1029
ISSN
0037-7732 (ISSN-L)
OpenAlex
W2161345470
Cited by
355
References
15
FWCI
25.20
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Gender Ideology and Perceptions of the Fairness of the Division of Household Labor: Effects on Marital Quality. https://app.cochat.ai/papers/10.1093/sf/74.3.1029
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Greenstein, T. N. (1996). Gender Ideology and Perceptions of the Fairness of the Division of Household Labor: Effects on Marital Quality. Social Forces. https://doi.org/10.1093/sf/74.3.1029

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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.