#  Stone Inequality & Social Policy Seminar: Jonathan Mummolo 

 



    ![Mummolo](/sites/g/files/omnuum5566/files/styles/hwp_5_4__480x385/public/2026-01/Mummolo%20J.jpg?h=15f35778&itok=KHqs96TB) 

 



 

####  calendar\_today Date and Time 

 **March 9, 2026** 

 12:00PM - 01:15PM EDT 

####  pin\_drop Location 

 **Malkin Penthouse**  

Harvard Kennedy School

 

 

 



 

### The Promises and Pitfalls of Police Body-Worn Camera Data in the Study of Police Use of Force

**Jonathan Mummolo**, *Associate Professor of Politics and Public Affairs, Princeton University*

**Abstract:** Analyses of police behavior have relied on self-reported officer accounts which may contain omissions, errors, or falsehoods. Body-worn camera (BWC) footage promised a more objective record, but resource and technological constraints leave most BWC footage unseen. In this paper, we draw on more than 700,000 BWC videos (~800 TB), and associated police administrative records from a large police department, to assess the accuracy and completeness of traditional use-of-force reports. Using an original computational classifier in concert with human annotators, we first estimate the prevalence of "missing" uses of force (events caught on video that are not reported by officers). Reporting rates vary sharply by force type—weapon uses are well documented in traditional administrative files; most undocumented force involves tackling and/or manually restraining civilians. Using a modified "capture-recapture" statistical technique common in ecology, we then bound, for the first time, the share of force incidents which are fully "hidden"—events not captured in either paper or video records. We also show that BWC footage remains difficult to analyze computationally even with leading vision analysis techniques. To facilitate progress, we discuss possible policy changes and technological advances that would improve the usefulness of these data in the near term. We also provide the first ever human-annotated testbed of public BWC footage against which other researchers and industry leaders can objectively evaluate vision model performance.

**Jonathan Mummolo** is an Associate Professor of Politics and Public Affairs at Princeton University. He studies bureaucratic politics and political behavior, and devotes particular focus to law enforcement agencies and police-civilian interactions. His work explores several facets of policing, including how controversial tactics are deployed in time and space, how rules and procedures affect the nature and volume of police-civilian interactions, the role of race in police behavior, and how police tactics affect perceptions of law enforcement and crime. He also conducts methodological research on issues relevant to his substantive work, including causal inference, statistical modeling and experimental design. His work exploits a range of research designs and data sources including field, natural, and survey experiments, qualitative interviews and administrative records obtained through public information requests to government agencies. His research has appeared in *Science, Proceedings of the National Academy of Sciences, Journal of the American Statistical Association, American Political Science Review*, *American Journal of Political Science*, and *The Journal of Politics*, among other peer-reviewed journals. Mummolo received a B.A. from New York University and a Ph.D. from Stanford University. Before beginning his doctoral studies he was a staff writer at *The Washington Post* where he covered crime and politics in the Washington, D.C. region.



 

**Due to building access restrictions, if you do not have a Harvard ID and wish to attend, you must email** [**inequality@hks.harvard.edu**](mailto:inequality@hks.harvard.edu) **to receive permission at least three days in advance of the seminar.**



 

 

 



 

 

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