Factors Influencing Crime and Instability in Urban Housing Developments - Report of the Second Phase (A Methodological Review) (From Link Between Crime and the Built Environment, Volume 2, PC104-C132, 1980, by Tetsuro Motoyama et al - See NCJ-79544)

• NCJ Number: 79553
• Author(s): C Murray; H Rubenstein; L Langbein; T Motoyama; P Hartjens
• Date Published: 1980
• Length: 29 pages
• Corporate Author: American Institutes for Research
• Sale Source: National Institute of Justice/
• Language: English
• Country: United States of America
• Note: Available on microfiche from NCJRS as NCJ-79544.

Annotation

This review assesses the Newman and Franck study of the interrelationships between crime rates and turnover in moderate- and low-income housing developments.

Abstract

Specifically, the study sought to determine the factors that contribute most to high crime rates, vandalism, and fear of crime in residential developments and also whether housing management policies help to reduce crime rates, instability, and abandonment. Data were collected and analyzed from 63 low- and moderate-income housing sites in three cities; the study design was based on a 'defensible space' causal model. The research involved analysis of household surveys, archival and observational data on physical attributes of the housing development, data on the socioeconomic characteristics of the residents, data on friendship and neighboring patterns, and housing management policies. Among its conclusions, the study determined that two physical design variables--building size and accessibility--and two social variables--low income and teen-adult ratio--are the major determinants of crime, fear, and instability. The study offers very weak evidence that the built environment is a major factor in encouraging or deterring crime; however, it reveals evidence supporting some of the key relationships among the built environment and use of space, control of space, social interaction, and turnover, which defensible space theory indicates are related to crime. Obstacles to determining more from the data were the early conversion of the individual data points into composites that have no interpretable metrics and reliance on the path model, which produced unstable results and offered only a remote possibility that a replication would reveal coefficients of similar magnitude. For further information on the study, see NCJ 71093 and 71094.