Abstract

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<jats:title content-type="abstract-subheading">Purpose</jats:title>
<jats:p>The purpose of this paper is to evaluate the violence-reduction effects following an FBI-led gang takedown in South Central Los Angeles.</jats:p>
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<jats:title content-type="abstract-subheading">Design/methodology/approach</jats:title>
<jats:p>The time series impact of the intervention was estimated using a Bayesian diffusion-regression state-space model designed to infer a causal effect of an intervention using data from a similar (non-targeted) gang area as a control.</jats:p>
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<jats:title content-type="abstract-subheading">Findings</jats:title>
<jats:p>A statistically significant 22 percent reduction in violent crime was observed, a reduction that lasted at least nine months after the interdiction.</jats:p>
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<jats:title content-type="abstract-subheading">Research limitations/implications</jats:title>
<jats:p>The research method does make assumptions about the equivalency of the control area, though statistical checks are employed to confirm the control area crime rate trended similarly to the target area prior to the intervention.</jats:p>
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<jats:title content-type="abstract-subheading">Practical implications</jats:title>
<jats:p>The paper demonstrates a minimum nine-month benefit to a gang takedown in the target area, suggesting that relatively long-term benefits from focused law enforcement activity are possible.</jats:p>
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<jats:title content-type="abstract-subheading">Social implications</jats:title>
<jats:p>Longer-term crime reduction beyond just the day of the intervention can aid communities struggling with high crime and rampant gang activity.</jats:p>
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<jats:title content-type="abstract-subheading">Originality/value</jats:title>
<jats:p>Few FBI-led gang task force interventions have been studied for their crime reduction benefit at the neighborhood level. This study adds to that limited literature. It also introduces a methodology that can incorporate crime rates from a control area into the analysis, and overcome some limitations imposed by ARIMA modeling.</jats:p>
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