This article explores those factors that shape a political organization’s choice of tactics in political mobilization with a particular focus on the influence of gender ideology on the choice of different type of contentious action. To understand why political organizations engaging in contentious politics choose to employ violent tactics, nonviolent tactics, or a mixture of both, current scholarship has tended to focus on factors such as relationship with the government, external support, and religious or leftist ideology. Far less attention has been given to the role of an organization’s ideology relating to gender when predicting its behavior. In addition, much of the analysis of contentious activity has analyzed the use of violence or protest separately and rarely examines the choice of a mixed strategy. We employ a time-series multinomial logistic regression analysis to examine the Middle East Minorities at Risk Organizational Behavior dataset (MAROB), including data over 24 years on 104 ethno-political organizations that have used a range of tactics including protest, violence, and/or a mix of the two, to investigate organizational and state-level variables that lead organizations to choose different strategies. We find that a number of variables can influence a movement’s choice to engage in one strategy over another. Gender-inclusive ideology makes an organization more likely to engage in protest and less likely to choose a violent or mixed strategy.

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Researchers have recently been cautioned regarding error in the Uniform Crime Reports’ (UCR) “Crime by County” cross-sectional time-series data. These data were the basis for analyses of the effects of laws regarding shall-issue concealed carry weapons (CCW) permits on UCR crime rates in the controversial book More Guns, Less Crime (MGLC). The authors conduct a critical analysis of the state-level data used in that study, compare it to readily available state-level UCR data, and discuss issues that may unduly influence the MGLC parameter estimates. Using alternative data, they reestimate the MGLC models, finding that the majority of the MGLC state-level findings are mere artifacts of reporting error and data anomalies resulting from the use of aggregated UCR “Crime by County” data. The authors conclude that any inferences regarding the effects of concealed carry weapons laws on crime rates drawn from analyses of the MGLC state-level data are seriously flawed.

The use of surveys