G2TT
来源类型Research Report
规范类型报告
Catalyzing Policing Reform with Data
其他题名Policing Typology for Los Angeles Neighborhoods
Ashlin Oglesby-Neal; Alena Stern; Kathryn L.S. Pettit
发表日期2020-05-12
出版年2020
语种英语
概述Strong community-police relationships are essential to public safety, and these relationships influence how communities engage with the police. We created a typology based on multiple aspects of policing that reveals a relationship between resident-initiated and police-initiated activity, and explores how that relationship varies across neighborhoods. We found that resident calls for service and police stops and
摘要

Strong community-police relationships are essential to public safety, and these relationships influence how communities engage with the police. We created a typology based on multiple aspects of policing that reveals a relationship between resident-initiated and police-initiated activity, and explores how that relationship varies across neighborhoods. We found that resident calls for service and police stops and arrests generally increase together, and neighborhoods with high amounts of activity tend to have a greater proportion of violent crime and serious calls for service. The neighborhoods with high activity also tend to have wider racial disparities in stops and arrests, and more economic hardship. This neighborhood-policing typology can inform conversations about police reform in Los Angeles and also serve as an example of how open data can be a powerful tool for local movements for a more equitable criminal justice system in other cities. Read the blog post on Urban Wire for highlights from the report.

Explore the Data and Methods

To visualize the levels of resident and police-initiated activity and explore patterns across Los Angeles neighborhoods, see the interactive tool that accompanies this report.

The open data come from the Los Angeles Open Data Portal, the American Community Survey, and the US Department of Housing and Urban Development. A companion Technical Appendix describes the data sources and methods, and the code for processing and analyzing the data is on GitHub.

About the Project

The analysis was conducted in collaboration with the Microsoft Criminal Justice Reform team, the Microsoft Data Science and Analytics team, and the University of Southern California’s Sol Price Center for Social Innovation.

This neighborhood-policing typology is part of a larger criminal justice project of the National Neighborhood Indicators Partnership (NNIP), which is a learning network coordinated by the Urban Institute that connects independent partner organizations in 30 cities. NNIP’s mission is to ensure all communities can access data and have the skills to use information to advance equity and well-being across neighborhoods. A previous brief highlights how local organizations across the US are using data to explore criminal justice issues in their communities.

主题Crime and Justice ; Neighborhoods, Cities, and Metros
URLhttps://www.urban.org/research/publication/catalyzing-policing-reform-data
来源智库Urban Institute (United States)
资源类型智库出版物
条目标识符http://119.78.100.153/handle/2XGU8XDN/480998
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Ashlin Oglesby-Neal,Alena Stern,Kathryn L.S. Pettit. Catalyzing Policing Reform with Data. 2020.
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