Citation

Leeper GE. N. Y. Univ. Law Rev. 2017; 92: 2051-2093.

Copyright

(Copyright © 2017, New York University School of Law)

DOI

unavailable

PMID

unavailable

Abstract

When it wants to be, the federal government is good at counting things. It tracks average daily caffeine intake (300 milligrams per adult older than twenty-two in 2008), weekly instances of the flu (875 reported by public health laboratories in the week ending January 14, 2017), monthly production of hens' eggs (8.97 billion in December 2016), and annual bicycle thefts (204,984 in 2015). But it currently cannot provide a comprehensive count of how often police officers use lethal force against its citizens. The deaths of Michael Brown, Walter Scott, Tamir Rice, Laquan McDonald--all unarmed, black, and shot by police officers--and far too many others have forced the issue of lethal police use of force into the national consciousness. But while many recent reports have focused on the unreliability of current data, there has been relatively little consideration of how, exactly, the federal government might go about getting it. This Note seeks to fill this gap by laying out the contours within which the federal government can act to incentivize states to collect more and better data. After highlighting the need for robust data collected at the federal level and describing various issues with the current state of federal collection of law enforcement data, this Note outlines the legal landscape legislators considering such a policy must grapple with: the combination of federalism concerns that are particularly acute in the sphere of state and local law enforcement, and the Supreme Court's somewhat ambiguous conditional spending jurisprudence. Finally, it explains how the federal government might incentivize data collection without running afoul of the law, proposing a legislative scheme for federal collection of law enforcement data that combines national guidelines, conditional spending requirements, and competitive grant funding.

Language: en