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Tightening The Ooda Loop: Police Militarization, Race, And Algorithmic Surveillance, Jeffrey L. Vagle
Tightening The Ooda Loop: Police Militarization, Race, And Algorithmic Surveillance, Jeffrey L. Vagle
Michigan Journal of Race and Law
This Article examines how military automated surveillance and intelligence systems and techniques, when used by civilian police departments to enhance predictive policing programs, have reinforced racial bias in policing. I will focus on two facets of this problem. First, I investigate the role played by advanced military technologies and methods within civilian police departments. These approaches have enabled a new focus on deterrence and crime prevention by creating a system of structural surveillance where decision support relies increasingly upon algorithms and automated data analysis tools and automates de facto penalization and containment based on race. Second, I will explore these …
Uncovering "Nondiscernible" Differences: Empirical Research And The Jury-Size Cases, Richard O. Lempert
Uncovering "Nondiscernible" Differences: Empirical Research And The Jury-Size Cases, Richard O. Lempert
Michigan Law Review
My point is not that verdict differences associated with jury size cannot be revealed through careful empirical investigation. Indeed, at several places in this article I will suggest research strategies likely to reveal such differences. Rather, it is that typical strategies of legal-impact research, such as those utilized in the Colgrove real-world studies, are unlikely to uncover differences associated with jury size however well they control for those plausible rival hypotheses that form the usual threats to the validity of impact research. The reason lies in the unamenability of the jury-size problem to the usual techniques of aggregate data analysis.