Research

Research Agenda

My research agenda on policing focuses on three interrelated areas: 1) market-based approaches to social control that municipalities use to manage risks and increase the accountability of state actors, specifically the role of insurance to reform policing and regulate police behavior; 2) “monetary sanctions” stemming from police misconduct and the contemporary fiscal justice movement fighting these sanctions; and 3) the social, political, racial, and ethical dimensions of using artificial intelligence, machine learning, and big data-informed algorithmic risk techniques in modern police accountability mechanisms (e.g., insurance, early intervention systems, body-worn cameras) and its implications for justice and equity in policing.

The Role of Insurance Models to Reform Policing & Increase Accountability

Despite many police accountability efforts underway in the contemporary United States, financial immunization of officers continues to enable police impunity. Legal scholars have examined this social problem from the vantage points of law and how governments pay for misconduct; they have also mapped the police liability insurance terrain. Yet little is known about how police accountability activists and municipal actors—e.g., public officials, police leaders, risk managers—approach and perceive the overlapping issues of insurance, risk management, police accountability, and police misconduct settlements. Further, despite pioneering research in this area by legal scholars, few in-depth municipal case studies currently exist, especially from a sociological and sociolegal perspective. My dissertation, Police Misconduct, Monetary Sanctions, and Insurance Models in the Modern Police Accountability Era, examines the role that insurance models play—or could potentially play—in regulating police departments and individual officers. Through a qualitative case study of municipalities in Minnesota operating with and without market-based insurance, my project adds to the existing sociological and related interdisciplinary literatures, while shedding light on the salience of this accountability mechanism, by: 1) Elucidating key stakeholders’ approaches to and perceptions of existing and potential insurance models for regulating police behavior. 2) Uncovering and/or further elucidating municipal, non-profit, and/or private sector insurance and risk management practices that either perpetuate or reduce police impunity and police violence. 3) Informing scholarly and policy discussions on reforming police via insurance.
 

In one empirical chapter, I analyze the innovative but ultimately unsuccessful 2016 ballot campaign of the Committee for Professional Policing (CfPP), a police accountability group in Minneapolis, Minnesota, which attempted to make Minneapolis the first city nationwide to require police to carry professional liability insurance. I reinterpret Feeley and Simon’s (1992) classic “new penology” paradigm through a social movement lens. They argue that a late-twentieth-century penal shift occurred away from rehabilitation toward managing aggregates of dangerous criminal categories (e.g., violent offenders) using risk management approaches. I extend their thesis by examining how police accountability groups are implicitly inverting the new penology onto police in an effort to manage aggregates of dangerous police categories (e.g., violent officers) using risk management approaches. In doing so, my research has created a new subarea in the sociology of punishment by opening up empirical avenues for investigating how criminal justice reformers may be applying the logic of the new penology to manage high-risk personnel in other criminal justice occupations too.

My sole-authored article on CfPP’s insurance campaign was recently published in Law & Social Inquiry (LSI) (official journal of the American Bar Foundation) and received multiple national paper awards. A related paper, “‘Entrepreneurs of Punishment’: Police Misconduct Insurance, Grassroots Activism, and the Limits of Linguistic Capital,” uses a Bourdieusian analysis to examine Minneapolis’ efforts to obstruct CfPP’s campaign and also received a national paper award. Currently, I am preparing this paper for journal submission. In addition to these two articles, I plan to revise my dissertation into a book manuscript and pursue a book contract with a leading academic press. 

In future research, I will apply for a National Science Foundation Law and Social Sciences grant to trace the diffusion processes and implementation efforts of this accountability mechanism across the US. External funding will enable me to hire student RAs to help collect and analyze data, affording them mentoring and publication opportunities. 

Monetary Sanctions & Fiscal Justice Activism 

Monetary Sanctions of Police Misconduct & Other Carceral State Institutions

Another major contribution of my dissertation is that I extend the sociology of punishment literature on “monetary sanctions.” Existing research focuses on all the costs imposed by the criminal legal system on traditional offenders accused and/or convicted of a crime. Instead of focusing on how cities (like Ferguson, Missouri) budget for revenue generated from monetary sanctions and the micro-level predatory effects these sanctions have on traditional offenders, my project illuminates: 1) how police misconduct payouts contribute to tax revenue shortfalls, which can trap cities in long-term debt cycles; and 2) how financially immunizing officers and departments has meso-level predatory effects on cities by diverting tax revenue from the public sector to cover payouts.

The Fiscal Justice Movement in the Contemporary Police Accountability Era

In my dissertation, I argue that CfPP’s insurance campaign can be situated within a wider fiscal justice movement that has emerged in the Black Lives Matter and modern police accountability era. This submovement has been spearheaded by public policy and grassroots-focused research organizations seeking to hold police accountable along with the municipalities and financial institutions that financially immunize them. For example, the Washington D.C.-based firm, Activest, was established in 2015 in the wake of the police-perpetrated killing of Michael Brown in Ferguson, Missouri. It seeks to factor in police misconduct payouts and inequity when determining the valuation of cities’ bonds, which conventional credit assessment institutions have generally overlooked. My future research will examine how fiscal justice organizations nationwide are seeking to advance racial, social, and economic justice by transforming municipal finance. 

Artificial Intelligence, Machine Learning, Big Data & Police Accountability Mechanisms

In my dissertation, I trace the discursive development of “problem officers,” which, in the policing literature, are defined as officers who disproportionately and repeatedly commit misconduct. From the mid-1970s to the present, the notion of “problem officers” evolved along with the accountability mechanism of early intervention systems (EISs) for identifying and correcting behavior of violent officers. Currently, EISs are an integral tool of the risk management process within police agencies, and, in recent years, data scientists and police managers have partnered to develop a new EIS to predict future misconduct. The data scientists aim to diffuse this innovative accountability mechanism to police departments nationwide and make it a model for preventing future misconduct. This new predictive EIS employs machine-learning algorithms, which are computer algorithms that detect patterns by processing historical data sources, and relies on big data-informed algorithmic techniques. Machine-learning techniques produce risk scores that departments can use to rank officers in terms of risk levels and distribute resources more efficiently. In the wake of George Floyd’s murder, some police departments are also starting to employ the new predictive EIS developed by the company Truleo, which uses artificial intelligence to identify problem behaviors and prevent misconduct. While I have begun to examine the social, political, racial, and ethical dimensions of insurance models, in my future research I will examine these dimensions as they pertain to predictive EISs and body-worn cameras and their implications for justice and equity in policing.