This four article journal-based dissertation builds on Gene Sharp's framework of nonviolent direct action, along with Hess and Martin's repression backfire, in order to deepen our understanding of how state repression impacts protest mobilization and historical processes of social change. After initially problematizing Gene Sharp’s notions of power and consent with aid of political discourse theory, and two case studies of the 1905 Russian Bloody Sunday Massacre and the South African 1976 Soweto Massacre, the dissertation moves onto specifically explain the conditions under which protest mobilization is likely to continue after severe state repression. A causal process model underpins the logic of the dissertation. It identifies generalizable antecedent factors and conditions under which repression backfire is most likely to occur. Numerous mechanisms are also introduced that help explain the operation of this process across different historical eras and political systems. After applying this process model and its mechanisms to the 2013 Turkish Gezi protests, a fuzzy-set qualitative comparative analysis of 44 different historical massacres is presented in which repression backfired and increased protest in some cases, but not others. Repression backfire is a highly asymmetrical and nonlinear causal phenomenon. I conclude that nonviolent protest strategy has been a salient factor in historical cases of repression backfire and is also vital for the ability of protests to withstand state repression. However, the role of nonviolence is partial and to some degree inadequate in explaining repression backfire if it is not linked to other general factors which include protest diversity, protest threat level, and geographic terrain.
Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:688095 |
Date | January 2016 |
Creators | Anisin, Alexei |
Publisher | University of Essex |
Source Sets | Ethos UK |
Detected Language | English |
Type | Electronic Thesis or Dissertation |
Source | http://repository.essex.ac.uk/17165/ |
Page generated in 0.0016 seconds