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Logarithmic versus Linear Visualizations of COVID-19 Cases Do Not Affect Citizens’ Support for Confinement

The SARS-CoV-2 virus was first identified in Wuhan, China, in late December 2019, and it quickly spread to many countries. By March 2020, the virus had triggered a global pandemic (World Health Organization, 2020). In response to this crisis, governments have implemented unprecedented public health...

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Autores principales: Sevi, Semra, Aviña, Marco Mendoza, Péloquin-Skulski, Gabrielle, Heisbourg, Emmanuel, Vegas, Paola, Coulombe, Maxime, Arel-Bundock, Vincent, Loewen, Peter John, Blais, André
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cambridge University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7200843/
http://dx.doi.org/10.1017/S000842392000030X
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author Sevi, Semra
Aviña, Marco Mendoza
Péloquin-Skulski, Gabrielle
Heisbourg, Emmanuel
Vegas, Paola
Coulombe, Maxime
Arel-Bundock, Vincent
Loewen, Peter John
Blais, André
author_facet Sevi, Semra
Aviña, Marco Mendoza
Péloquin-Skulski, Gabrielle
Heisbourg, Emmanuel
Vegas, Paola
Coulombe, Maxime
Arel-Bundock, Vincent
Loewen, Peter John
Blais, André
author_sort Sevi, Semra
collection PubMed
description The SARS-CoV-2 virus was first identified in Wuhan, China, in late December 2019, and it quickly spread to many countries. By March 2020, the virus had triggered a global pandemic (World Health Organization, 2020). In response to this crisis, governments have implemented unprecedented public health measures. The success of these policies will largely depend on the public's willingness to comply with new rules. A key factor in citizens’ willingness to comply is their understanding of the data that motivate government action. In this study, we examine how different ways of presenting these data visually can affect citizen's perceptions, attitudes and support for public policy.
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spelling pubmed-72008432020-05-06 Logarithmic versus Linear Visualizations of COVID-19 Cases Do Not Affect Citizens’ Support for Confinement Sevi, Semra Aviña, Marco Mendoza Péloquin-Skulski, Gabrielle Heisbourg, Emmanuel Vegas, Paola Coulombe, Maxime Arel-Bundock, Vincent Loewen, Peter John Blais, André Can J Polit Sci Research Note/Notes de recherche The SARS-CoV-2 virus was first identified in Wuhan, China, in late December 2019, and it quickly spread to many countries. By March 2020, the virus had triggered a global pandemic (World Health Organization, 2020). In response to this crisis, governments have implemented unprecedented public health measures. The success of these policies will largely depend on the public's willingness to comply with new rules. A key factor in citizens’ willingness to comply is their understanding of the data that motivate government action. In this study, we examine how different ways of presenting these data visually can affect citizen's perceptions, attitudes and support for public policy. Cambridge University Press 2020-04-14 /pmc/articles/PMC7200843/ http://dx.doi.org/10.1017/S000842392000030X Text en © Canadian Political Science Association (l'Association canadienne de science politique) and/et la Société québécoise de science politique 2020 http://creativecommons.org/licenses/by/4.0/ http://creativecommons.org/licenses/by/4.0/This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Note/Notes de recherche
Sevi, Semra
Aviña, Marco Mendoza
Péloquin-Skulski, Gabrielle
Heisbourg, Emmanuel
Vegas, Paola
Coulombe, Maxime
Arel-Bundock, Vincent
Loewen, Peter John
Blais, André
Logarithmic versus Linear Visualizations of COVID-19 Cases Do Not Affect Citizens’ Support for Confinement
title Logarithmic versus Linear Visualizations of COVID-19 Cases Do Not Affect Citizens’ Support for Confinement
title_full Logarithmic versus Linear Visualizations of COVID-19 Cases Do Not Affect Citizens’ Support for Confinement
title_fullStr Logarithmic versus Linear Visualizations of COVID-19 Cases Do Not Affect Citizens’ Support for Confinement
title_full_unstemmed Logarithmic versus Linear Visualizations of COVID-19 Cases Do Not Affect Citizens’ Support for Confinement
title_short Logarithmic versus Linear Visualizations of COVID-19 Cases Do Not Affect Citizens’ Support for Confinement
title_sort logarithmic versus linear visualizations of covid-19 cases do not affect citizens’ support for confinement
topic Research Note/Notes de recherche
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7200843/
http://dx.doi.org/10.1017/S000842392000030X
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