Co-Constitution of Protest Repertoires and Performances through Protest Cycles

Monday, 11 July 2016: 09:12
Location: Hörsaal 21 (Main Building)
Oral Presentation
Charles KIRSCHBAUM, Insper/ CEM-Cebrap, Brazil
Angela ALONSO, USP /CEBRAP, Brazil
Extant literature on social movements and protests has stressed the need for incorporating relational mechanisms in order to explore how actors, practices and repertoires co-evolve as protests unfold (Tilly, 2007). This paper establishes a dialogue with the current literature by proposing a methodological approach to tackle the relational dynamics among actors and repertoire. Rather than assuming relationships as ex-ante and given to the protest cycles, or conceiving the protest repertoire as given and bounded in a ‘tool box’ (Swilder, 1986), we suggest that relationships among actors and mobilized repertoire co-evolve. Social actors might engage in specific performances not only to promote their protest, but also to distinguish them from other counterparts. Conversely, joint events that involve a wide range of social actors might lead the former to silence specific performances that could put in jeopardy the contingent coalition. Further, the emergence of not-predicted forms might set social actors against each other. In order to explore these dynamics, we explore the protest cycles that took place in Brazil, during the month of June of 2013. We built a unique database of protest events, comprising around 800 events collected from newspapers (i.e. Malinicka, Tindall & Diani, 2013). Each event was codified and includes (inter alia) actors involved, form of action, form of repression, action target (Franzosi, 2004). The relationship between actors and forms of action constitute a longitudinal affiliation network. The evolution of performance network is formalized, yielding ‘protest grammars’ (Mohr & Rawlings, 2010), while the network among actors provide a glance at the evolution of coalitions (McAdam & Fligstein, 2012). Actor-based modeling (i.e. Siena) is applied in order to model the co-evolution of this network’s two modes.