skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Explore Research Products in the PAR
It may take a few hours for recently added research products to appear in PAR search results.


Title: Laundering Militarization: Preparedness, Professionalism, and Police Common Sense
US police militarization is commonly understood as military violence abroad flowing to domestic policing, where it does not belong. Despite years of reform efforts, attempts to demilitarize local police have thus far failed to effect substantive change. This essay builds on the history of US policing, as well as sixteen months of ethnographic research with police in Maryland, to suggest that the ideological labor of policing contributes to these failures. Specifically, I examine two elements of what I call police common sense: preparedness as moral practice and violence as professional technique. In so doing, I demonstrate how policing metabolizes militarization as an apolitical technical craft that counterintuitively reduces violence, and that allows officers to fulfill their primary ethical role as stewards of public crises. Demilitarization reforms function in tandem with the political work of preparedness and professionalism to consecrate “good” militarization as commonsensical and legitimate. These reforms thus inadvertently lend power to the notion of police as the “thin blue line” between extreme violence and innocent (white) society.  more » « less
Award ID(s):
2204269
PAR ID:
10524218
Author(s) / Creator(s):
Publisher / Repository:
Johns Hopkins University Press
Date Published:
Journal Name:
American Quarterly
Volume:
75
Issue:
4
ISSN:
1080-6490
Page Range / eLocation ID:
799 to 820
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. ; ; ; ; ; (, Journal of Experimental Political Science)
    Abstract Does providing information about police shootings influence policing reform preferences? We conducted an online survey experiment in 2021 among approximately 2,600 residents of 10 large US cities. It incorporated original data we collected on police shootings of civilians. After respondents estimated the number of police shootings in their cities in 2020, we randomized subjects into three treatment groups and a control group. Treatments included some form of factual information about the police shootings in respondents’ cities (e.g., the actual total number). Afterward, respondents were asked their opinions about five policing reform proposals. Police shooting statistics did not move policing reform preferences. Support for policing reforms is primarily associated with partisanship and ideology, coupled with race. Our findings illuminate key sources of policing reform preferences among the public and reveal potential limits of information-driven, numeric-based initiatives to influence policing in the US. 
    more » « less
  2. ; ; ; (, Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency)
    Large-scale policing data is vital for detecting inequity in police behavior and policing algorithms. However, one important type of policing data remains largely unavailable within the United States: aggregated police deployment data capturing which neighborhoods have the heaviest police presences. Here we show that disparities in police deployment levels can be quantified by detecting police vehicles in dashcam images of public street scenes. Using a dataset of 24,803,854 dashcam images from rideshare drivers in New York City, we find that police vehicles can be detected with high accuracy (average precision 0.82, AUC 0.99) and identify 233,596 images which contain police vehicles. There is substantial inequality across neighborhoods in police vehicle deployment levels. The neighborhood with the highest deployment levels has almost 20 times higher levels than the neighborhood with the lowest. Two strikingly different types of areas experience high police vehicle deployments — 1) dense, higher-income, commercial areas and 2) lower-income neighborhoods with higher proportions of Black and Hispanic residents. We discuss the implications of these disparities for policing equity and for algorithms trained on policing data. 
    more » « less
  3. ; ; (, Applied Sciences)
    Integrating artificial intelligence (AI) technologies into law enforcement has become a concern of contemporary politics and public discourse. In this paper, we qualitatively examine the perspectives of AI technologies based on 20 semi-structured interviews of law enforcement professionals in North Carolina. We investigate how integrating AI technologies, such as predictive policing and autonomous vehicle (AV) technology, impacts the relationships between communities and police jurisdictions. The evidence suggests that police officers maintain that AI plays a limited role in policing but believe the technologies will continue to expand, improving public safety and increasing policing capability. Conversely, police officers believe that AI will not necessarily increase trust between police and the community, citing ethical concerns and the potential to infringe on civil rights. It is thus argued that the trends toward integrating AI technologies into law enforcement are not without risk. Policymaking guided by public consensus and collaborative discussion with law enforcement professionals must aim to promote accountability through the application of responsible design of AI in policing with an end state of providing societal benefits and mitigating harm to the populace. Society has a moral obligation to mitigate the detrimental consequences of fully integrating AI technologies into law enforcement. 
    more » « less
  4. ; ; (, PLOS ONE)
    Jackson, Jonathan (Ed.)
    Explanations for police misconduct often center on a narrow notion of “problem officers,” the proverbial “bad apples.” Such an individualistic approach not only ignores the larger systemic problems of policing but also takes for granted the group-based nature of police work. Nearly all of police work is group-based and officers’ formal and informal networks can impact behavior, including misconduct. In extreme cases, groups of officers (what we refer to as, “crews”) have even been observed to coordinate their abusive and even criminal behaviors. This study adopts a social network and machine learning approach to empirically investigate the presence and impact of officer crews engaging in alleged misconduct in a major U.S. city: Chicago, IL. Using data on Chicago police officers between 1971 and 2018, we identify potential crews and analyze their impact on alleged misconduct and violence. Results detected approximately 160 possible crews, comprised of less than 4% of all Chicago police officers. Officers in these crews were involved in an outsized amount of alleged and actual misconduct, accounting for approximately 25% of all use of force complaints, city payouts for civil and criminal litigations, and police-involved shootings. The detected crews also contributed to racial disparities in arrests and civilian complaints, generating nearly 18% of all complaints filed by Black Chicagoans and 14% of complaints filed by Hispanic Chicagoans. 
    more » « less
  5. (, Journal of the American Philosophical Association)
    Predictive policing, the practice of using of algorithmic systems to forecast crime, is heralded by police departments as the new frontier of crime analysis. At the same time, it is opposed by civil rights groups, academics, and media outlets for being ‘biased’ and therefore discriminatory against communities of color. This paper argues that the prevailing focus on racial bias has overshadowed two normative factors that are essential to a full assessment of the moral permissibility of predictive policing: fairness in the social distribution of the benefits and burdens of policing as well as the distinctive role of consent in determining fair distribution. When these normative factors are given their due attention, several requirements emerge for the fair implementation of predictive policing. Among these requirements are that police departments inform and solicit buy-in from affected communities about strategic decision-making and that departments favor non-enforcement-oriented interventions. 
    more » « less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Save / Share this Record
  • Send to Email