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Responding to the COVID-19 pandemic has created unprecedented social and political challenges. Mitigation strategies often disrupt the daily lives of citizens and constrain rights and privileges. Policies intended to contain disease spread have provoked resentment, resistance, and backlash. We examine the extent to which specific COVID-19 policy responses influence the frequency of civil unrest. Combining insights from both grievance and opportunity models of dissent, we contend that pandemic response policies are most likely to lead to unrest when the grievances and opportunities created by disease mitigation strategies reinforce each other. We test our arguments with nuanced information on specific pandemic mitigation policies, combined with geo-located events data on COVID-19-related social unrest activities. We find that policies such as workplace and school closures, which induce intense grievances and reduce the opportunity cost of engaging in collective mobilization, are associated with increases in dissent activities. Policies that restrict opportunities for mobilization, such as restrictions on public transportation, reduce the number of dissent activities. Notably, economic support policies attenuate the effects of workplace closures on dissent. Our results illustrate the varying effects of pandemic mitigation policies on unrest depending on how the grievances they inspire relate to the opportunity they create.

Field survey experiments often measure amorphous concepts in discretely ordered categories, with postsurvey analytics that fail to account for the discrete attributes of the data. This article demonstrates the use of discrete distribution tests, specifically the chi-square test and the discrete Kolmogorov—Smirnov (KS) test, as simple devices for comparing and analyzing ordered responses typically found in surveys. In Monte Carlo simulations, we find the discrete KS test to have more power than the chi-square test when distributions are right or left skewed, regardless of the sample size or the number of alternatives. The discrete KS test has at least as much power as the chi-square, and sometimes more so, when distributions are bi-modal or approximately uniform and samples are small. After deriving rules of usage for the two tests, we implement them in two cases typical of survey analysis. Using our own data collected after Hurricanes Katrina and Rita, we employ our rules to both validate and assess treatment effects in a natural experimental setting.

Responding to the COVID-19 pandemic has created unprecedented social and political challenges. Mitigation strategies often disrupt the daily lives of citizens and constrain rights and privileges. Policies intended to contain disease spread have provoked resentment, resistance, and backlash. We examine the extent to which specific COVID-19 policy responses influence the frequency of civil unrest. Combining insights from both grievance and opportunity models of dissent, we contend that pandemic-response policies are most likely to lead to unrest when the grievances and opportunities created by disease-mitigation strategies reinforce each other. We test our arguments with nuanced information on specific pandemic-mitigation policies, combined with geolocated events data on COVID-19-related social unrest activities. We find that policies such as workplace and school closures, which induce intense grievances and reduce the opportunity cost of engaging in collective mobilization, are associated with increases in dissent activities. Policies that restrict opportunities for mobilization, such as restrictions on public transportation, reduce the number of dissent activities. Notably, economic support policies attenuate the effects of workplace closures on dissent. Our results illustrate the varying effects of pandemic-mitigation policies on unrest depending on how the grievances they inspire relate to the opportunity they create.