Journal article
Need drugs, will travel?: The distances to crime of illegal drug buyers
Journal of criminal justice, v 41(3)
01 May 2013
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Purpose: This study examines distances to crime among illegal drug buyers while controlling for buyer, drug, and destination characteristics.
Methods: Geocoded arrests for drug buyers in an urban municipality, over a three year period, spatially identify major drug markets. Negative binomial regression is used to model compositional characteristics of drug arrestees and contextual effects of markets on distance to arrest (n=4,082).
Results: Trip distance to drug purchase arrest varies by drug market. Being white, and having prior contact with the criminal justice system correlated with longer trip distances. Additional compositional effects vary by drug type.
Conclusions: In line with prior journey to crime research and crime pattern theory, illicit drug buyers are arrested in close proximity of their homes. Future research should consider the extent to which short aggregate market distances reflect policing differentials and close social ties. (C) 2013 Elsevier Ltd. All rights reserved.
Metrics
Details
- Title
- Need drugs, will travel?: The distances to crime of illegal drug buyers
- Creators
- Lallen T. Johnson - Drexel UniversityRalph B. Taylor - Department of Geography and Urban Studies (courtesy appointment), Temple University, Philadelphia, PA, USAJerry H. Ratcliffe - Temple UniversityMichelle J Dolinski - Physics
- Publication Details
- Journal of criminal justice, v 41(3)
- Publisher
- Elsevier
- Number of pages
- 10
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Physics
- Web of Science ID
- WOS:000318059100005
- Scopus ID
- 2-s2.0-84874511596
- Other Identifier
- 991019186805504721
UN Sustainable Development Goals (SDGs)
This publication has contributed to the advancement of the following goals:
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Criminology & Penology