Action repertoires in contentious episodes: What determines governments’ and challengers’ action strategies? A cross-national analysis
Corresponding Author
ABEL BOJAR
European University Institute, Italy
Address for correspondence: Abel Bojar, Department of Political & Social Sciences, European University Institute, Via della Badia dei Roccettini, 9, 50014 Fiesole, Italy. Email: [email protected]
Search for more papers by this authorCorresponding Author
ABEL BOJAR
European University Institute, Italy
Address for correspondence: Abel Bojar, Department of Political & Social Sciences, European University Institute, Via della Badia dei Roccettini, 9, 50014 Fiesole, Italy. Email: [email protected]
Search for more papers by this authorAbstract
This paper studies the interactions between governments, challengers and third party actors in the context of 60 contentious policy episodes in 12 European countries during the Great Recession. More specifically, we focus on the endogenous dynamics that develop in the course of these episodes. Based on the combination of a new event dataset, which allows for the construction of action sequences, and a novel method (contentious episode analysis) to study the impact of actor-specific actions on subsequent actions within a sequence, we test a set of hypotheses on the determinants of actors’ overall action repertoires within specific contexts. Overall, our results are more supportive of the interdependence of cooperation than of the interdependence of conflict: the repression-radical mobilisation-external legitimation of conflictive behaviour nexus is weaker than the concession-cooperation-mediation nexus. While the literature tends to focus on conflict dynamics, we find that there is a more systematic dynamics of cooperation in the course of contentious episodes.
Supporting Information
Filename | Description |
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ejpr12386-sup-0003-ONLINEAPPENDIX.docx198.5 KB | Figure 1-A: predicted probabilities from the path dependence models in high contentiousness episodes Figure 2-A: predicted probabilities from the government/challenger-threat models in high contentiousness episodes Figure 3-A: predicted probabilities from the third party models in high contentiousness episodes Figure 4-A: predicted probabilities from the path-dependence models excluding short sequences Figure 5-A: predicted probabilities from the government/challenger threat models excluding short sequences Figure 6-A: predicted probabilities from the third-party models excluding short sequences Figure 7-A: Path dependence models for at least second-order lags (predicted probabilities with 95% confidence intervals) Figure 8-A: Path dependence models for lags longer than a week (predicted probabilities with 95% confidence intervals) Table 1-B: Frequency distribution of action forms by actor types Table 2-B: Frequency distribution of institutional and stylized actor types Table 1-C: Government path-dependence models Table 2-C: Challenger path-dependence models Table 3-C: Government threat models Table 4-C: Challenger threat models Table 5-C: Government-third party models Table 6-C: Challenger-third party models Table 1-D: Government selflags (% of column total) Table 2-D: Challenger selfags (% of column total) Table 3-D: Challenger-specific lags of government actions (% of column total) Table 4-D: Government-specific lags of challenger actions (% of column total) Table 5-D: Third-party specific lags of government actions (% of column total) Table 6-D: Third-party specific lags of challenger actions (% of column total) Figure 1-E: predicted probabilities of government actions as a function of past challenger actions and government self-lags Figure 2-E: predicted probabilities of challenger actions as a function of past government actions and challenger self-lags Figure 3-E: predicted probabilities of government actions as a function of past third party actions and government self-lags Figure 4-E: predicted probabilities of challenger actions as a function of past third party actions and challenger self-lags |
ejpr12386-sup-0001-DataS1.dta86.6 MB | Supplementary Material |
ejpr12386-sup-0002-DataS2.do27.3 KB | Supplementary Material |
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