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Configurational Comparative Methods

Social Movement Mobilization The operationalization of the social movement condition defines our unit of analysis. In order to operationalize it, we use yearly counts per movement as used in Giugni (2004) and produce distribution graphs.13 Based on these graphs, we select our cases based on the presence of ebbs and flows in protest activities, with an average of four peaks and nonpeaks by movement and by country. Peaks are phases of strong mobilization during which the num-ber of protest events is clearly above average for that movement in that country. Nonpeaks are phases of weak mobilization during which the number of events is clearly below average for that movement in that country. The peaks (periods of strong mobilization) were coded 1 and the non-peaks (periods of weak mobilization) were coded 0. Since the aim of our analysis is to measure the impact of social movements, these peak and nonpeak periods define our cases. For example, the ecology movement experienced a peak of activity between 1984 and 1988 in Italy. This defines one case and also sets the coding of the condition “protest” for this case. Since phases of strong and weak mobilization define the cases, some periods are excluded from the analysis. One might legitimately ask what would happen had these periods of “gray” mobilization been included. This would make sense if the aim was to assess the degree of impact of one variable—here the level of mobilization—on policy change, net of the effect of all other variables, as is usually done in statistical analysis. However, QCA, and crisp-set QCA in particular, aims at identifying patterns among several categorical or nominal variables that are associated with policy change. Although, multivalue QCA or fuzzy-set QCA, where conditions can take more than two values, could have been used, both variants are better suited to analyze medium-large datasets, and our dataset is rather small once divided by country and issue. Public Opinion