Use of a “Microecologic Technique” to Study Crime Around Substance Abuse Treatment Centers

Use of a “Microecologic Technique” to Study Crime Around Substance Abuse Treatment Centers Whether substance abuse treatment centers affect neighborhood crime is hotly debated. Empirical evidence on this issue is lacking because of the difficulty of distinguishing the crime effect of treatment centers in high-crime areas, the inability to make before-and-after comparisons for clinics founded before computerized crime data, and the need for appropriate control sites. The authors present an innovative method (without an actual data analysis) to overcome these challenges. Clinic addresses and crime data are geocoded by street address. Crimes are counted within concentric-circular, 25-meter “buffers” around the clinics. Regression analyses are used to calculate the “crime slope” (β) among the buffers. A negative β indicates more crimes closer to the site. A similar process is used to evaluate crimes around control sites: convenience stores, hospitals, and residential points. This innovative technique provides valid empirical evidence on crime around substance abuse treatment centers. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Social Science Computer Review SAGE

Use of a “Microecologic Technique” to Study Crime Around Substance Abuse Treatment Centers

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Publisher
SAGE
Copyright
Copyright © by SAGE Publications
ISSN
0894-4393
eISSN
1552-8286
D.O.I.
10.1177/0894439307298928
Publisher site
See Article on Publisher Site

Abstract

Whether substance abuse treatment centers affect neighborhood crime is hotly debated. Empirical evidence on this issue is lacking because of the difficulty of distinguishing the crime effect of treatment centers in high-crime areas, the inability to make before-and-after comparisons for clinics founded before computerized crime data, and the need for appropriate control sites. The authors present an innovative method (without an actual data analysis) to overcome these challenges. Clinic addresses and crime data are geocoded by street address. Crimes are counted within concentric-circular, 25-meter “buffers” around the clinics. Regression analyses are used to calculate the “crime slope” (β) among the buffers. A negative β indicates more crimes closer to the site. A similar process is used to evaluate crimes around control sites: convenience stores, hospitals, and residential points. This innovative technique provides valid empirical evidence on crime around substance abuse treatment centers.

Journal

Social Science Computer ReviewSAGE

Published: May 1, 2007

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