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Cited by 653

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Lipstick and Logarithms: Gender, Institutional Context, and Representative Bureaucracy

KEISER, LAEL R., WILKINS, VICKY M., MEIER, KENNETH J., HOLLAND, CATHERINE A.·2002·American Political Science Review

Abstract

According to the theory of representative bureaucracy, passive representation among public employees will lead to active representation in bureaucratic outputs. Existing research demonstrates that the link between passive and active representation exists for race but not for sex. Past research on this topic has not, however, taken into account the contextual environment that affects whether sex will translate into gender and lead to active representation in the bureaucracy. In this paper, we create a framework that specifies the conditions that affect whether passive representation results in active representation for sex and then test this framework using the case of education. We find that passive representation of women in education leads to active representation and that the institutional context affects the extent to which this link between passive and active representation occurs.

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Metadata

Authors
KEISER, L. R., WILKINS, V. M., MEIER, K. J., & HOLLAND, C. A.
Venue
American Political Science Review
Published
2002-09
Volume
96
Issue
3
Pages
553-564
ISSN
  • 0003-0554 (ISSN-L)
  • 1537-5943
OpenAlex
W2027785757
Cited by
653
References
2
FWCI
15.61
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Lipstick and Logarithms: Gender, Institutional Context, and Representative Bureaucracy. https://app.cochat.ai/papers/10.1017/s0003055402000321
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KEISER, L. R., WILKINS, V. M., MEIER, K. J., & HOLLAND, C. A. (2002). Lipstick and Logarithms: Gender, Institutional Context, and Representative Bureaucracy. American Political Science Review. https://doi.org/10.1017/s0003055402000321

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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.