A Multi-Method Analysis of Civil Resistance Outcomes

• In Event: Non-Violent Resistance and Protests

Abstract

Popular uprisings start as an attempt to bring about change in politically stagnant situations. This mission becomes particularly challenging when it involves mobilization against repressive central authority. Following the framework introduced by Schock (2013), I conduct a multi-method analysis of civil resistance outcomes by utilizing measures for mobilization, resilience, leverage, backfire, strategic choices, and strategy shift. I apply data analytics, logistic regression, and machine learning on the Nonviolent and Violent Campaign Outcomes Dataset (NAVCO 2.1), which documents major civil resistance campaigns around the globe from 1946-2013. I verify the findings with a comparative case study of the 2011 Tunisian and Syrian popular uprisings. I then apply Geographic Information Systems to examine the effect of proximity between countries that experience popular uprisings within the same year on civil resistance outcomes. My results demonstrate that civil resistance outcomes are shaped by both internal and external variables. Efficient mobilization, unity among opposition groups, and the capacity to withstand regime repression are crucial factors that determine campaign success. Furthermore, stripping the regime from its sources of power through security defections, state defections, and withdrawal of international support also increases the likelihood of campaign success. My results are consistent with Chenoweth and Lewis (2013) and provide evidence to support the theoretical proposition that non-violent campaigns have higher chances of success than violent insurgencies. This leads to the important conclusion that sticking to non-violent methods of civil resistance is the ideal course of action. The results also demonstrate the importance of proximity as one of the top variables that explain civil resistance campaign outcomes. They provide supporting evidence to concepts such as the domino effect and waves of democratization and highlight the importance of the spatial dimension in explaining and predicting popular uprisings.

Author

• Soha Hammam, Claremont Graduate University