Community Structure and Crime: Testing Social-Disorganization Theory

Authors: Robert J. Sampson (University of Illinois at Urbana-Champaign), W. Byron Groves (University of Wisconsin-Green Bay)
Publication: American Journal of Sociology, Vol. 94, No. 4 (1989), pp. 774-802
Published by: The University of Chicago Press
Stable URL: JSTOR
Accessed on: 18-10-2025 01:31 UTC

Shaw and McKay's theory of community social disorganization has not been directly tested before this study.
General Hypothesis: Low economic status, ethnic heterogeneity, residential mobility, and family disruption contribute to community social disorganization, which in turn increases crime and delinquency rates.
Measure of Social Organization: Assessed through local friendship networks, control of street-corner teenage peer groups, and prevalence of organizational participation.

The model was first tested using data from 238 localities in Great Britain from a 1982 national survey of 10,905 residents.
A replication was conducted with an independent national sample consisting of 11,030 residents across 300 British localities in 1984.
Results consistently supported the theory, showing that variations in social disorganization account for differences in criminal victimization and offending rates across communities.

Shaw and McKay's model, particularly prominent in the study of juvenile delinquency, identifies three structural factors:
- Low Economic Status
- Ethnic Heterogeneity
- Residential Mobility
Findings from Previous Researchers: Bursik (1984), Morris (1970), Short (1969) emphasized the relevance of these factors to variations in crime and delinquency.

Data Collection Issues: Limitations arose due to a lack of relevant data to empirically analyze community social control phenomena purported by Shaw and McKay.
Ecological Studies: Focused more on socioeconomic status rather than directly testing mediating variables in social-disorganization theory.
Challenges with Official Data: Official crime rates may reflect biases leading to an inaccurate portrayal of community dynamics in relation to crime rates.
Need for New Data: Suggested that survey methodologies gathering self-reported delinquency and victimization data could provide better insights.

Definition of Social Disorganization: Defined as the community's inability to achieve common values and maintain social controls (Kornhauser 1978).
Systemic Model: Local communities viewed as complex networks comprising friendship and kinship bonds, as well as formal and informal associations (Kasarda and Janowitz 1974).
Hypothesis on Teenage Peer Groups: Communities unable to control teenage peer dynamics will likely face higher delinquency rates (ref. Thrasher 1963; Shaw and McKay 1969).

Supervision of Teenage Peer Groups: Essential for controlling delinquent behaviors.
- Evidence of gangs originating from unsupervised youth activities (e.g., Thrasher 1963).
- Cohesive communities better govern teenage behavior.
Informal Local Friendship Networks: Networks enhance community control and awareness against criminal behavior.
- High network density signifies better control over delinquent actions (Krohn 1986).
Formal Organizational Participation: Strong participation in community organizations strengthens social cohesion and control.
- Weak community ties lessen local control capacities (Kornhauser 1978).

Socioeconomic Status (SES): Communities with lower SES have weaker organizational bases and higher crime rates.
Residential Mobility: Frequent movement disrupts social relations, hindering community integration (Kasarda and Janowitz 1974).
Ethnic Heterogeneity: Diversity can dampen the community's ability to reach consensus and maintain social order (Suttles 1968).
Family Disruption: Marital instability leads to decreased social supervision and community control (Sampson 1987).
Urbanization: Urban areas typically show diminished local social control compared to suburban or rural locales (e.g., Fischer 1982).

Data Source: British Crime Survey (BCS), providing macro-level community analysis through comprehensive sampling.
Community Measures: Constructs developed based explicitly on respondents' locality, including organized participation, friendship networks, and teenage peer supervision averages.
Statistical Analysis: Included a range of community structural characteristics to measure their effects on crime and delinquency rates.

Large discrepancies in community characteristics, including SES, ethnic diversity, and residential stability.

Strong support for the proposed model linking community structure to crime, mediated by social disorganization measures.
Diversions in crime rates corresponded to levels of social organization, emphasizing the mediating role of unsupervised peer groups, friendship networks, and organizational participation in determining crime rates.
Notable correlations between community-level characteristics and both victimization and self-reported offending rates showed direct negative and positive effects, respectively.

Multiple tests confirmed the validity of the regression models used, revealing no significant issues with multicollinearity or influential cases.
Adjustments for neighborhood fear ensured the independence of results from external deterrent factors.

The findings underscore the relevance of social-disorganization theory in explaining macro-level crime rate variations in a different cultural backdrop (England and Wales).
The study illuminates the theoretical implications of community organizational dynamics, providing renewals of interest in the systemic models posited by Shaw and McKay.
They highlight the necessity for future research to improve metric precision for assessing community disorganization dimensions and potential impacts on crime rates.

A comprehensive list of references ranging from foundational texts such as Shaw and McKay's works to supportive contemporary analyses of social-networking theories, providing foundational depth for the community crime analysis attempted in the study.
Measured variables were suitably adjusted for macro-level constructs to enhance data reliability throughout the community analyses.