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Multilevel Analysis of Protest

Application for Small N Designs

Bibliographic Data

ID3758019
AuthorsKateřina Vráblíková (0000-0002-5676-5091, University of Bath, Bath, UK, corresponding author)
Year2022
Volume66
Issue5
Pages648-668
Publication date2022-05-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueAmerican Behavioral Scientist (JOURNAL)
Journal identifiersISSN: 0002-7642 • E-ISSN: 1552-3381
PublisherSAGE Publications Inc (PUBLISHER)
DOI10.1177/00027642211021628
OpenAlexW3172853445
LanguageEN
References cited27

Protest is the result of complex multilevel processes. It is triggered by contextual factors such as political opportunities or events, it depends on organizations' mobilizing capacity as well as on the type of people who protest, and it is shaped by the characteristics of the populations they come from. To effectively study the antecedents that operate at various levels, social movement research needs to integrate data from multiple analytical levels and systematically examine the relationships across the various levels. While large N statistical techniques of multilevel modelling are well understood, less is known about applying multilevel analysis research examining small number of cases. The article develops conceptual and methodological tools for multilevel analysis of protests in studies with a small number of cases. First, it demonstrates the empirical requirements associated with analyzing three types of multilevel effects: contextual effects, composition effects, and cross-level interactions. Next, specific multilevel small N designs that can be used to examine the three multilevel effects are presented. The last section uses the multilevel approach to examine the demobilization of anti-Iraq War protests in the United States

Demobilization · Multilevel model · Multilevel modelling · Political science · Politics · Computer Science · Electoral Systems and Political Participation · Political Conflict and Governance · Psychology · Qualitative Comparative Analysis Research

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Citation velocityhistorical
Highly citedNo
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