Mitigating the Harm of Public Mass Shootings through Situational Crime Prevention

The proposed dissertation seeks to study the situational and environmental factors leading to fatal public mass shooting incidents (PMSI). The project will add 28 situational crime prevention constructs to the open-source Mass Shooting and Media Database of 321 mass shootings between 1966-2018, funded by NIJ and DHS. It will also code all 2019 mass shooting incidents. The applicant will use Latent Class Analysis (LCA) and Structural Equation Modelling (SEM) to develop topologies of factors that enhance lethality during PMSI. The applicant will also select 8 separate classes identified by the LCA to perform an inductive, in-depth case study on environmental and situational factors that contributed to lethality. The external peer review noted the strengths of the proposal: the cross validation of its findings and its mixed-methods approach. "Note: This project contains a research and/or development component, as defined in applicable law," and complies with Part 200 Uniform Requirements - 2 CFR 200.210(a)(14). CA/NCF