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Cited by 320

The DOI matches its Crossref record; 37 of the 37 references it cites were found in a registry or an index.

TO VEIL OR NOT TO VEIL?: A Case Study of Identity Negotiation among Muslim Women in Austin, Texas

READ, JEN'NAN GHAZAL, BARTKOWSKI, JOHN P.·2000·Gender & Society

Abstract

The increasingly pervasive practice of veiling among Muslim women has stimulated a great deal of scholarly investigation and debate. This study brings empirical evidence to bear on current debates about the meaning of the veil in Islam. This article first examines the conflicting meanings of the veil among Muslim religious elites and Islamic feminists. Although the dominant gender discourse among Muslim elites strongly favors this cultural practice, an antiveiling discourse promulgated by Islamic feminists has gained ground within recent years. This study then examines how these discursive disputes affect gender identity negotiation among veiled and unveiled Muslim women living in Austin, Texas. Interviews with these women highlight how their gender identities reproduce and reformulate existing Muslim gender discourses. Special attention is paid to the subjective disparities and points of congruence between both groups of respondents. This study concludes by suggesting avenues for future research on the intersection of gender, religion, and cultural difference.

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Metadata

Authors
READ, J. G., & BARTKOWSKI, J. P.
Venue
Gender & Society
Published
2000-06
Volume
14
Issue
3
Pages
395-417
ISSN
  • 0891-2432 (ISSN-L)
  • 1552-3977
OpenAlex
W2114821019
Cited by
320
References
37
FWCI
98.43
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: TO VEIL OR NOT TO VEIL?: A Case Study of Identity Negotiation among Muslim Women in Austin, Texas. https://app.cochat.ai/papers/10.1177/089124300014003003
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READ, J. G., & BARTKOWSKI, J. P. (2000). TO VEIL OR NOT TO VEIL?: A Case Study of Identity Negotiation among Muslim Women in Austin, Texas. Gender & Society. https://doi.org/10.1177/089124300014003003

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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.