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NCJ Number: 241504 
Title: Assessing Macro-Level Predictors and Theories of Crime: A Meta-Analysis (From Crime and Justice: A Review of Research, Volume 32, P 373-450, 2005, Michael Tonry, ed. – See NCJ-241498)
Author(s): Travis C. Pratt; Francis T. Cullen
Date Published: 2005
Page Count: 78
Sponsoring Agency: University of Chicago Press
Chicago, IL 60637
Sale Source: University of Chicago Press
1427 East 60th Street
Chicago, IL 60637
United States of America
Publisher: http://www.press.uchicago.edu 
Type: Research (Theoretical)
Format: Book Chapter
Language: English
Country: United States of America
Annotation: This essay presents the results of a meta-analysis of research that assessed macro-level predictors and theories of crime.
Abstract: The macro-level approach reemerged as a salient criminological paradigm in the late 1970s and early 1980s. Prompted by new theories and reformulations of existing ones, over 200 empirical studies explored ecological correlates of crime. Few efforts have been made, however, to “make sense” of this literature. A “meta-analysis” was undertaken to determine the relative effects of macro-level predictors of crime. Indicators of “concentrated disadvantage” (e.g., racial heterogeneity, poverty, and family disruption) are among the strongest and most stable predictors. Except for incarceration, variables indicating increased use of the criminal justice system (e.g., policing and get-tough policy effects) are among the weakest. Across all studies, social disorganization and resource/economic deprivation theories receive strong empirical support, anomie/strain, social support/social altruism, and routine activity theories receive moderate support; and deterrence/rational choice and subcultural theories receive weak support. (Published Abstract)
Main Term(s): Crime causes theory
Index Term(s): Crime prediction; Criminality prediction; Poverty and crime; Prediction; Strain theory
To cite this abstract, use the following link:
http://www.ncjrs.gov/App/publications/abstract.aspx?ID=263594

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