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Cited by 264

The DOI matches its Crossref record; 48 of the 48 references it cites were found in a registry or an index.

Testing the Stability of Crime Patterns: Implications for Theory and Policy

Andresen, Martin A., Malleson, Nicolas·2011·Journal of Research in Crime and Delinquency

Abstract

Recent research in the ‘‘crime at places’’ literature is concerned with smaller units of analysis than conventional spatial criminology. An important issue is whether the spatial patterns observed in conventional spatial criminology focused on neighborhoods remain when the analysis shifts to street segments. In this article, the authors use a new spatial point pattern test that identifies the similarity in spatial point patterns. This test is local in nature such that the output can be mapped showing where differences are present. Using this test, the authors investigate the stability of crime patterns moving from census tracts to dissemination areas to street segments. The authors find that general crime patterns are somewhat similar at all spatial scales, but finer scales of analysis reveal significant variations within larger units. This result demonstrates the importance of analyzing crime patterns at small scales and has important implications for further theoretical development and policy implementation.

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Metadata

Authors
Andresen, M. A., & Malleson, N.
Venue
Journal of Research in Crime and Delinquency
Published
2010-12-05
Volume
48
Issue
1
Pages
58-82
ISSN
  • 0022-4278 (ISSN-L)
  • 1552-731X
OpenAlex
W2160677803
Cited by
264
References
48
FWCI
25.04
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Testing the Stability of Crime Patterns: Implications for Theory and Policy. https://app.cochat.ai/papers/10.1177/0022427810384136
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Andresen, M. A., & Malleson, N. (2011). Testing the Stability of Crime Patterns: Implications for Theory and Policy. Journal of Research in Crime and Delinquency. https://doi.org/10.1177/0022427810384136

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.