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Non-verbal cues as a test of gender and race bias in politics: the Italian case

Published online by Cambridge University Press:  01 July 2015

Shanto Iyengar  and
Mauro Barisione
Shanto Iyengar*
Affiliation:
Department of Communication and Political Science, Stanford University, Stanford, CA 94305, USA
Mauro Barisione
Affiliation:
Department of Social and Political Sciences, Università degli Studi di Milano, Milan, Italy
*
*E-mail: siyengar@stanford.edu
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Abstract

Gender and race biases persist in western democracies, with male and white candidates still being the norm. Voters may be more inclined to express sexist and racist attitudes in countries with a traditionally male-dominated political system and a majority-white population. As sexism and racism are notoriously difficult to document, and because many people are unaware of their biases toward social groups, we bypass conventional survey measurement and observe voters’ willingness to support candidates whose physical features have been manipulated to make them appear more prototypically feminine or non-white. We implemented this approach in the context of the 2013 Italian election, by presenting a national sample of Italian voters with pictures of male and female parliamentary candidates – both unknown and well known. Overall, we found no main effects of gender or race bias in political judgment. For Italian voters, party cues are by far the most powerful indicators of out-group status, and therefore the strongest predictors of candidate perception and support. This result may be of particular interest to other political contexts characterized by strong partisan polarization.

Keywords

survey experimentcandidate imagespublic opinionsocial prejudiceinteraction models
Type
Research Article
Information
Italian Political Science Review / Rivista Italiana di Scienza Politica , Volume 45 , Issue 2 , July 2015 , pp. 131 - 157
Copyright
© Societá Italiana di Scienza Politica 2015 

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Supplementary material: Link

Iyengar and Barisione Dataset

Dataset

http://dx.doi.org/10.7910/DVN/ZMZDHG
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