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Cited by 513

The DOI matches its Crossref record; 53 of the 53 references it cites were found in a registry or an index.

The Individual–Institutional Nexus of Protest Behaviour

Dalton, Russell, Van Sickle, Alix, Weldon, Steven·2010·British Journal of Political Science

Abstract

Political protest is seemingly a ubiquitous aspect of politics in advanced industrial societies, and its use may be spreading to less developed nations as well. Our research tests several rival theories of protest activity for citizens across an exceptionally wide range of polities. With data from the 1999–2002 wave of the World Values Survey, we demonstrate that the macro-level context – levels of economic and political development – significantly influences the amount of popular protest. Furthermore, a multi-level model examines how national context interacts with the micro-level predictors of protest activity. The findings indicate that contemporary protest is expanding not because of increasing dissatisfaction with government, but because economic and political development provide the resources for those who have political demands.

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Crossref · 10.1017/s000712340999038x

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Metadata

Authors
Dalton, R., Van Sickle, A., & Weldon, S.
Venue
British Journal of Political Science
Published
2009-12-08
Volume
40
Issue
1
Pages
51-73
ISSN
  • 0007-1234 (ISSN-L)
  • 1469-2112
OpenAlex
W2145473407
Cited by
513
References
53
FWCI
33.65
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: The Individual–Institutional Nexus of Protest Behaviour. https://app.cochat.ai/papers/10.1017/s000712340999038x
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Dalton, R., Van Sickle, A., & Weldon, S. (2010). The Individual–Institutional Nexus of Protest Behaviour. British Journal of Political Science. https://doi.org/10.1017/s000712340999038x

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.