Suchergebnisse

This analysis of the diffusion of racial rioting in the United States applies recently developed extensions of event history analysis to the spread of rioting from 1964 to 1971. Contrary to early analyses of riot diffusion, the results demonstrate that diffusion is a critical force behind the pattern of rioting. The analysis identifies several types of diffusion in the riot cycle, demonstrating that contagious influence from riots decays over time, is mitigated by geographic distance, and is conditional on riot severity. Methodologically, the analysis produces extensions of prior event-history diffusion models that facilitate their use with collective violence and protest data. for comments on earlier drafts, Gregg Carter for providing his riot data, and Victoria Myers for assistance locating and retrieving original data.

This analysis of the diffusion of racial rioting in the United Slates applies recently developed extensions of event history analysis to the spread of rioting from 1964 to 1971. Contrary to early analyses of riot diffusion, the results demonstrate that diffusion is a critical force behind the pattern of rioting. The analysis identifies several types of diffusion in the riot cycle, demonstrating that contagious influence from riots decays over time, is mitigated by geographic distance, and is conditional on riot severity. Methodologically, the analysis produces extensions of prior event-history diffusion models that facilitate their use with collective violence and protest data. Adapted from the source document.

Movements develop in coevolution with regimes and other actors in their environments. Movement trajectories evolve through stochastic processes and are constrained, but not determined, by structures. Coevolution provides a theoretical structure for organizing existing understandings of social movements and sharpening future research. Stochastic thinking is essential for recognizing the both the volatility and path dependence of collective action and its underlying structural constraints. Formal models of diffusion, adaptive learning, mutual reinforcement, and inter-actor competition are developed and compared with empirical protest series. Responses to exogenous reinforcement, mutual adaptation in which failure is as important as success, and inter-actor competition are the most plausible mechanisms to account for empirical patterns. Trajectories of action depend upon the number of discrete random actors. Overall, the analysis suggests that movement dynamics are shaped more by interactions with other actors than by processes internal to a movement, and that empirical analysis must be sensitive to the level of aggregation of the data.

In recent years, there has been a surge in social movement theorizing known as the contentious politics approach to studying political protest activity. In 2002, a conference sponsored by the Collective Behavior and Social Movements Section of the American Sociological Association was held at the University of Notre Dame to consider, in part, this development in field. But the conference organizers also wanted to consider more broadly what we collectively consider to be social movement research and theorizing. In part, this means moving beyond a state-centered view of contentious politics and toward a more open definition of what might be fruitfully examined by social movement theories - and in turn what might inform those theories even as we use then in more traditional social movement arenas. This volume represents some of the fruits of that conference and includes four sections that defines social movement authorities challenges beyond state targets, expands our notions of what constitutes repression of social movement activity, examines challenges to cultural authorities and processes, and illustrates the broader notions of authority challenge in three case studies of corporate systems. With this volume, "Research in Social Movements, Conflict and Change" celebrates its 25th anniversary and a history of publishing important, leading edge research and theorizing in the areas pf protest, social conflict, and political change.

Movements develop in coevolution with regimes & other actors in their environments. Movement trajectories evolve through stochastic processes & are constrained, but not determined, by structures. Coevolution provides a theoretical structure for organizing existing understandings of social movements & sharpening future research. Stochastic thinking is essential for recognizing both the volatility & path dependence of collective action & its underlying structural constraints. Formal models of diffusion, adaptive learning, mutual reinforcement, & inter-actor competition are developed & compared with empirical protest series. Responses to exogenous reinforcement, mutual adaptation in which failure is as important as success, & inter-actor competition are the most plausible mechanisms to account for empirical patterns. Trajectories of action depend upon the number of discrete random actors. Overall, the analysis suggests that movement dynamics are shaped more by interactions with other actors than by processes internal to a movement, & that empirical analysis must be sensitive to the level of aggregation of the data. 10 Figures, 64 References. Adapted from the source document.