Lauren Krivo and Ruth Peterson

Project

Understanding Crime and Community: A National Neighborhood Crime Study

Investigators

Lauren J. Krivo (Department of Sociology, Rutgers & CJRC)
Ruth D. Peterson (Sociology Emeritus & CJRC)

Sponsor

National Science Foundation

Abstract

The NNCS assembled crime data for neighborhoods in 91 cities with populations over 100,000. These crime data are combined with sociodemographic data for cities/metropolitan areas and tracts from census and other published sources to construct a contextual data set of neighborhood characteristics with city/metropolitan variables appended to each neighborhood unit. These data permit researchers to conduct multi-level analyses evaluating: (1) the direct and indirect effects (through neighborhood conditions) of city/metropolitan structure on neighborhood crime; (2) whether and how city/metropolitan contextual factors condition the influence of neighborhood social disorganization, structural disadvantage, and socioeconomic inequality on crime; and (3) the extent to which neighborhood conditions (particularly economic status) have similar influences on crime in predominantly Black, White, and Latino neighborhoods. Such analyses are central to determining (1) the merits of claims by William Julius Wilson and others that the decline in stable manufacturing employment, growth of the low wage service sector, bifurcation of the labor market into high and low wage sectors, growing inequality, and decentralization of employment have had dramatic consequences for crime and other urban social problems; and (2) how racial/ethnic composition, as distinct from economic composition, influences community crime levels.

Products

National Neighborhood Crime Study Data Set
This unique data set combines important crime and sociodemographic information for 9,593 neighborhoods (census tracts) and the 91 cities and 64 metropolitan areas in which they are located. The national sample of places in which the neighborhoods are located differ in size, population composition, and labor market structure.

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