The deadliest local police departments kill 6.91 times more frequently than the least deadly departments, net of risk, in the United States.
Josh Leung-GagnéPublished in: PNAS nexus (2024)
I use data linking counts of homicides by police to police department (PD) and jurisdiction characteristics to estimate benchmarked (i.e. risk-adjusted) police homicide rates in 2008-2017 among the 711 local PDs serving 50,000 or more residents, a sample with demographics resembling all mid-to-large Census places. The benchmarked rate estimates capture PD deadliness by comparing PDs to peers whose officers face similar risks while adjusting for access to trauma care centers to account for differential mortality from deadly force. Compared to existing estimates, differences in benchmarked estimates are more plausibly attributable to policing differences, speaking to whether the force currently used is necessary to maintain safety and public order. I find that the deadliest PDs kill at 6.91 times the benchmarked rate of the least deadly PDs. If the PDs with above-average deadliness instead killed at average rates for a PD facing similar risks, police homicides would decrease by 34.44%. Reducing deadliness to the lowest observed levels would decrease them by 70.04%. These estimates also indicate the percentage of excess police homicides-those unnecessary for maintaining safety-if the baseline agency is assumed to be optimally deadly. Moreover, PD deadliness has a strong, robust association with White/Black segregation and Western regions. Additionally, Black, Hispanic, foreign-born, lower income, and less educated people are disproportionately exposed to deadlier PDs due to the jurisdictions they reside in. Police violence is an important public health concern that is distributed unevenly across US places, contributing to social disparities that disproportionately harm already marginalized communities.
Keyphrases
- public health
- healthcare
- mental health
- palliative care
- physical activity
- emergency department
- human health
- cardiovascular events
- cardiovascular disease
- south africa
- machine learning
- electronic health record
- risk factors
- big data
- affordable care act
- gestational age
- peripheral blood
- preterm birth
- low birth weight
- health insurance
- pain management
- neural network