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Measuring attitudes as a complex system

Structured thinking and support for the Canadian carbon tax

Published online by Cambridge University Press:  10 November 2021

Jordan Mansell ,
Steven Mock ,
Carter Rhea ,
Adrienne Tecza  and
Jinelle Piereder
Jordan Mansell*
Affiliation:
Western University, Network for Economic and Social Trends
Steven Mock
Affiliation:
University of Waterloo, Balsillie School of International Affairs
Carter Rhea
Affiliation:
Université de Montréal
Adrienne Tecza
Affiliation:
Colorado Center for Civic Learning and Engagement
Jinelle Piereder
Affiliation:
University of Waterloo
*
Correspondence: Jordan Mansell, Western University, Network for Economic and Social Trends, London, Ontario, Canada Email: jmansel3@uwo.ca
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Abstract

We test a method for applying a network-based approach to the study of political attitudes. We use cognitive-affective mapping, an approach that visually represents attitudes as networks of concepts that an individual associates with a given issue. Using a software tool called Valence, we asked a sample of Canadians (n = 111) to draw a cognitive-affective map (CAM) of their views on the carbon tax. We treat these networks as a series of undirected graphs and examine the extent to which support for the tax can be predicted based on each graph’s emotional and structural properties. We find evidence that the emotional but not the structural properties significantly predict individuals’ attitudes toward the carbon tax. We also find associations between CAMs’ structural properties (density and centrality) and several measures of political interest. Our results provide preliminary evidence for the efficacy of CAMs as a tool for studying political attitudes. The study data are available at https://osf.io/qwpvd/?view_only=6834a1c442224e72bf45e7641880a17f

Keywords

political attitudespolitical ideologynetwork analysislatent propertiescognitive-affective mappingcarbon tax
Type
Special Issue: Psychophysiology, Cognition, and Political Differences
Information
Politics and the Life Sciences , Volume 40 , Issue 2: SPECIAL ISSUE: PSYCHOPHYSIOLOGY, COGNITION, AND POLITICAL DIFFERENCES , Fall 2021 , pp. 179 - 201
Copyright
© The Author(s), 2021. Published by Cambridge University Press on behalf of the Association for Politics and the Life Sciences

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