PREDICTING VIOLENT CRIME USING URBAN AND SUBURBAN DENSITIES

Topics: Crime, Suburb, Population Pages: 25 (4614 words) Published: October 25, 2013
Behavior and Social Issues, 14, 113-127 (2005). © Brian Christens & Paul W. Speer. Readers of this article may copy it without the copyright owner’s permission, if the author and publisher are acknowledged in the copy and the copy is used for educational, not-for-profit purposes.

PREDICTING VIOLENT CRIME USING URBAN AND SUBURBAN
DENSITIES
Brian Christens1 & Paul W. Speer
Vanderbilt University

ABSTRACT: Violent crime is often studied with individual level variables, using population characteristics as predictors. This study attempts to predict an additional amount of the variability in violent crime using an environmental variable—population density—in a single U.S. city. Data aggregated to the census block group level are used to test a model that compares the urban center of the city with the entire county and the non-urban parts of the county. Drawing on Jane Jacobs’ (1961) theories of urbanism and the occurrence of crime, it was hypothesized that population density at the census block level would negatively predict violent crime in the urban areas. Based on evidence of a non-linear relationship between crime and density (Regoeczi, 2002), it was conversely hypothesized that density would have a positive predictive effect on violent crime in the suburban areas, due to differences in urban and suburban/rural crime. The analyses support the hypotheses for the urban areas, but fail to support the hypotheses for the suburban areas, providing insight into an elusive relationship—and the effects of environments on behavior patterns. KEYWORDS: urban theory, geographic information systems, violent crime, population density

Understanding where crime happens can be a key to understanding why it happens (Roncek, 1993). Models that predict the occurrence of violent crime by geographical area often use data on the characteristics of the inhabitants (e.g. income, race, home ownership, family structure) of that area (Jencks, 1992). Additionally, there have been studies of psychological (e.g. ,territoriality) and physical-environmental predictors (e.g., block size, landscape) of crime (Kuo & Sullivan, 2001; Perkins, Wandersman, Rich & Taylor, 1993).

Population density has also received considerable attention as it relates to crime. Jane Jacobs (1961) contradicted the popular wisdom of city planners with her claim that crowded city streets and sidewalks could be effective deterrents to criminal behavior. A number of national studies tested the relationships between density and crime, with differing results. Some studies, such as those by Schuessler (1962) or Galle, Gove, and McPherson (1972), found positively correlated relationships between crime and density. Meanwhile, Kvalseth (1977) and others found the opposite types of relationships. Still others (e.g., Freedman, 1975) found non-significant relationships between the two variables.

Complicating factors in understanding studies like these are the differing ways that density is defined or measured, the level of data aggregation, and the different ways that crime data are gathered and analyzed (see Regoeczi, 2003). For instance, Shichor, Deker, and O’Brien (1980) found positive relationships between property crimes with contact 1

The authors can be reached by email at B.Christens@Vanderbilt.edu.

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and density, but negative relationships between non-property assaultive crimes and density, measured across 26 cities. The article attributed the first finding to the fact that many crimes in high-density areas would involve contact by necessity (Repetto, 1974), and the second to the idea of circulation on streets at all times acting as a deterrent (Jacobs, 1961). Alternatively, Sampson (1983) hypothesized that structural density, the degree to which an area is crowded with buildings, would be positively related to crime due to its ability to impede those same social controls.

Studies that hypothesized positive correlations between density and...

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