DOI

https://doi.org/10.25772/TM7E-7630

Defense Date

2011

Document Type

Thesis

Degree Name

Master of Science

Department

Sociology

First Advisor

Jennifer Johnson

Abstract

This study examines a largely unexplored aspect of Sutherland’s (1974) model of differential association: the interplay of general and crime specific definitions favorable towards crime. Do individuals learn the specific techniques of a type of crime through interactions or do social interactions produce a general disposition towards all types of criminal behavior? Little prior research has been done on the influence of these definitions. Instead studies focus on only one or another, which leaves the details of general/specific definitions unexplored. With the aid of a mixed methodology of statistical and network analysis, this study explores general/specific definitions simultaneously by focusing on relationships between egos and alters. If alters commit similar crimes, it is likely that crime specific definitions are being learned; if crimes are dissimilar then general definitions are more likely. Using police data on a known criminal network located in an urban capital, I test the relationship between the criminal behaviors of egos and alters. The study also compares the centrality of the node to the commonality of crime they commit. This provides an understanding of how key nodes in the network affect the dissemination of criminal definitions. Overall, while variations exist for criminal types, the study finds that crime specific definitions dominate the network and, therefore, have greater influence over respondents’ criminal behavior. Conversely, I found no clear pattern which indicates that high centrality nodes commit more common crimes. This may indicate that high centrality nodes are responsible for disseminating general definitions of crime while most nodes communicate crime specific definition.

Rights

© The Author

Is Part Of

VCU University Archives

Is Part Of

VCU Theses and Dissertations

Date of Submission

June 2011

Included in

Sociology Commons

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