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Local Norms, Political Partisanship, and Pandemic Response

Evidence from the United States

Bibliographic Data

ID7345369
AuthorsKeena Lipsitz (0000-0002-9192-836X, Princeton University), Grigore Pop-Eleches (0000-0003-3570-6233, Princeton University), Graeme B Robertson (0000-0003-1255-218X, Princeton University)
Year2023
Volume22
Issue1
Pages247-262
Publication date2023-11-21
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenuePerspectives on Politics (JOURNAL)
Journal identifiersISSN: 1537-5927 • E-ISSN: 1541-0986
PublisherCambridge University Press (CUP) (PUBLISHER)
DOI10.1017/s1537592723002864
OpenAlexW4388849000
LanguageEN
Citations received3
References cited61

A growing literature focuses on the role of political partisanship in shaping attitudes and behaviors during the COVID-19 pandemic in the United States. We provide a different perspective, by developing a theory of how partisanship interacts with another important factor that shapes how people think and behave in the context of the pandemic—local norms. Using a combination of survey data and a survey experiment, we demonstrate the importance of norms in shaping both support for social distancing and reported social-distancing behavior, particularly amongst independents and Republicans. We then confirm that perceptions of norms are indeed tied to what is actually happening around people—that their partisanship does not blind them to reality. Our analysis is the first to examine how partisanship and norms interact with each other and helps to explain why partisan differences matter more in some places than in others

Context (archaeology · Coronavirus disease 2019 (COVID-19 · Distancing · Economics · Geography · Happening · Pandemic · Perception · Perspective (graphical · Political economy · Political science · Politics · Positive economics · Social distance · Sociology · Survey data collection · Electoral Systems and Political Participation · Law · Psychology · Social and Intergroup Psychology · Social Media and Politics · Social Psychology

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Unique citing works3
Citations per year1
Citation span2023 - 2026 (4)
Citation velocitycurrent
Highly citedNo
Citation typesNeutral: 3

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