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Class, Ethnicity, and Cooperation Among Women: Evidence from a Public Goods Experiment in Lebanon

Published online by Cambridge University Press:  29 April 2020

Leslie Marshall*
Affiliation:
Department of Political Science, University of Pittsburgh, Pittsburgh, PA, USA Center for Sustainable Business, Joseph. M. Katz Graduate School of Business and College of Business Administration, University of Pittsburgh, Pittsburgh, PA, USA
Laura Paler
Affiliation:
Department of Political Science, University of Pittsburgh, Pittsburgh, USA
*
*Corresponding author. [email protected]

Abstract

While recent evidence suggests that women exhibit a high capacity to cooperate in all-women groups, existing research focuses on how women cooperate among themselves versus in mixed-gender situations. We still know little, however, about how social differences among women affect their collective action capacity. We examine this by implementing a public goods experiment in Lebanon in which 713 women and men were randomly assigned to play in same-gender groups that were either homogeneous or heterogeneous in their class and sectarian compositions. We show that women contribute significantly less in mixed-class groups while men contribute more, reinforcing that this pattern is unique to women. We also demonstrate that class differences can undermine women’s cooperation more than sectarian differences. These findings highlight how social differences – and class differences in particular – can impede women’s collective action capacity, revealing the potential barriers to building broad, gender-based coalitions to advance women’s rights and interests.

Type
Research Article
Copyright
© The Experimental Research Section of the American Political Science Association 2020

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Footnotes

We are especially indebted to Sami Atallah, Director of the Lebanese Center for Policy Studies (LCPS), for making this project possible. We are also grateful to Joanna Fayed, Zeina Hawa, and Zeina Helou for their tireless help with implementation and to Guy Grossman, Melanie Hughes, Kris Kanthak, and Lucy Martin for their thoughtful comments on earlier drafts. This project was made possible by funding that LCPS received from the Embassy of Norway. The authors are not aware of any conflicts of interest. This project is covered under University of Pittsburgh IRB PRO15060167. The data, code, and any additional materials required to replicate the analysis in this article are available at the Journal of Experimental Political Science Dataverse within the Harvard Dataverse Network, at doi: 10.7910/DVN/SWYQ26.

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