NDLI: Shooting on the Street: Measuring the Spatial Influence of Physical Features on Gun Violence in a Bounded Street Network

Content Provider	Springer Nature Link
Author	Xu, Jie Griffiths, Elizabeth
Copyright Year	2016
Abstract	Accurately estimate the strength and extent (distance) of the spatial influence of physical features on gun violence using a street network measurement strategy.Treating disaggregated point locations as the unit-of-analysis, the spatial influence of various physical features of place on all 2012 incidents of gun violence in Newark, NJ is estimated along a street network plane rather than a planar plane, and using a continuous operationalization of street network distances as opposed to Euclidean or Grid distances. Network-based computation methods clarify the path distances over which physical features of place, or shooting attractors, exert a significant spatial influence on gun violence. Segmented regression models estimate feature-specific distance decay patterns by demarcating the exact network distances at which the strength of attraction weakens or dissipates entirely.Findings show that liquor stores, grocery stores, bus stops, and residential foreclosures are shooting attractors in Newark, NJ. The magnitude of spatial influence is strongest in the immediate vicinity of each physical feature, and declines precipitously thereafter; yet the nature and strength of the decay varies by feature. A comparison of results analyzed on a street network plane to those based on an unbounded plane illustrates the potential biases in traditional approaches.Determining whether and how strongly physical features operate as crime attractors requires constraining the analyses to the street network plane and accurately measuring continuous distances along the street network. The methodology articulated in this study can be used to more precisely estimate the spatial influence and distance decay of various physical features of place on crime density.
Starting Page	237
Ending Page	253
Page Count	17
File Format	PDF
ISSN	07484518
Journal	Journal of Quantitative Criminology
Volume Number	33
Issue Number	2
e-ISSN	15737799
Language	English
Publisher	Springer US
Publisher Date	2016-03-30
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Spatial influence Physical features of place Street network Network Cross K Function Gun violence Criminology and Criminal Justice Sociology Methodology of the Social Sciences Statistics
Content Type	Text
Resource Type	Article
Subject	Law Pathology and Forensic Medicine

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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