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Improving Police and Criminal Court Data Transparency in the United States: A Case Study

Author(s)
Elbashir, Ahmed
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Advisor
Williams, Sarah
Terms of use
In Copyright - Educational Use Permitted Copyright MIT http://rightsstatements.org/page/InC-EDU/1.0/
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Abstract
Effective reform of criminal justice in the United States, including how to understand and fight inequity and structural racism embedded in the system, is hampered by the complexity and opaqueness of America’s criminal justice system. While extensive data is generated and recorded on individual police encounters, arrests, charges, court cases, sentences, and more, most of it is inaccessible to the public, or to researchers who could study this data and produce actionable insights. In the past decade, government officials in many major American municipalities have signaled an intent to collect and publish more data online to promote transparency and improve community relations. However, these efforts have been hindered by bureaucratic difficulties, the eclectic nature of the authorities who generate critical policing and criminal justice data, and the publication of online data in incomplete or non-useful formats. This paper will review the published criminal justice data in Philadelphia, New York City, and Chicago, describe the state of their criminal justice open data publications, and make recommendations for those and other municipalities on how to record and publish data. For data producers, these recommendations emphasize the importance of developing coherent tabular datasets for different criminal justice data topics, releasing visualizations which allow the general public to interface with the data, and publishing downloadable tabular datasets with as much detail as possible without infringing on individual privacy. For government organizations, this paper recommends that legislators pass laws requiring police departments, district attorneys, and courts to collect and publish data, and provide those organizations with the necessary funding to do so.
Date issued
2022-05
URI
https://hdl.handle.net/1721.1/144954
Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Publisher
Massachusetts Institute of Technology

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