Measuring attitudes as a complex system: Structured thinking and support for the Canadian carbon tax.

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...

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Publicado en:Politics & the Life Sciences Vol. 40; no. 2; pp. 179 - 202
Autores principales: Mansell, Jordan, Mock, Steven, Rhea, Carter, Tecza, Adrienne, Piereder, Jinelle
Formato: Artículo
Publicado: Cambridge University Press Sep2021
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Sep2021
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      pub: Cambridge University Press
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        10.1017/pls.2021.16
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        atl: Measuring attitudes as a complex system: Structured thinking and support for the Canadian carbon tax.
      aug:
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          Mansell, Jordan
          Mock, Steven
          Rhea, Carter
          Tecza, Adrienne
          Piereder, Jinelle
        affil:
          Western University, Network for Economic and Social Trends
          University of Waterloo, Balsillie School of International Affairs
          Université de Montréal
          Colorado Center for Civic Learning and Engagement
          University of Waterloo
      su:
        Systems theory
        Political attitudes
        Carbon taxes
        Undirected graphs
        Software development tools
        Concept mapping
      sug:
        subj:
          Systems theory
          Political attitudes
          Custom Computer Programming Services
          Computer systems design and related services (except video game design and development)
          Marketing Research and Public Opinion Polling
          Carbon taxes
          Undirected graphs
          Software development tools
          Concept mapping
      keyword:
        carbon tax
        cognitive-affective mapping
        latent properties
        network analysis
        political attitudes
        political ideology
        carbon tax
        cognitive-affective mapping
        latent properties
        network analysis
        political attitudes
        political ideology
      ab: 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
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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