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Cited by 487

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Gender, Leisure, and Constraint: Towards a Framework for the Analysis of Women's Leisure

Shaw, Susan M.·1994·Journal of Leisure Research

Abstract

This paper examines three approaches to the analysis of women's leisure, and discusses ways in which the ideas and concepts from these different approaches can be integrated. The first and dominant approach to understanding women's leisure is analysis of how leisure is constrained. From this perspective leisure is conceptualized as a desirable experience, and constraints to leisure participation are seen to arise out of structured gender relations. The second approach focuses on how leisure activities themselves, especially stereotypical activities, can be constraining through the reinforcement of traditional gender relations. A third, emerging approach examines ways in which women's leisure can be seen to have the potential for resistance to societally imposed constraints. Some guiding principles are suggested for the integration of these three approaches into a broader conceptual framework. Such a framework allows for both the diversity of women's experiences, and the contradictions inherent in women's leisure, to be taken into account.

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Metadata

Authors
Shaw, S. M.
Venue
Journal of Leisure Research
Published
1994-01
Volume
26
Issue
1
Pages
8-22
ISSN
  • 0022-2216 (ISSN-L)
  • 2159-6417
OpenAlex
W1549915682
Cited by
487
References
0
FWCI
16.08
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Gender, Leisure, and Constraint: Towards a Framework for the Analysis of Women's Leisure. https://app.cochat.ai/papers/10.1080/00222216.1994.11969941
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Shaw, S. M. (1994). Gender, Leisure, and Constraint: Towards a Framework for the Analysis of Women's Leisure. Journal of Leisure Research. https://doi.org/10.1080/00222216.1994.11969941

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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.