Despite the growing body of research examining the collateral consequences of legislation governing sex offenders, a complete understanding of their residential choices post release remains elusive. This paper develops a predictive-analytical framework that helps determine which demo-graphic and socioeconomic factors best forecast the residential choices of convicted sex offenders. Specifically, a derived index of social disorganization (ISDOR) is implemented in both statistical and nonlinear data mining approaches to predict the presence of sex offenders in a community. The results of the analysis are encouraging, predicting nearly 75% of registered offender locations correctly. The utility of this framework as a tool for public policy and law enforcement is discussed.
ASJC Scopus subject areas
- Geography, Planning and Development
- Environmental Science (miscellaneous)