Spatial Optimization and Geographic Uncertainty: Implications for Sex Offender Management Strategies
Residence restrictions are increasingly popular policy-based tools for managing the spatial distribution of sex offenders in the USA.
Frequently implemented with limited study or practical guidance, it is likely that spatial uncertainty in many evaluative efforts creates interpretive and policy questions. For example, sex offender locations, prohibited areas, proximity evaluation, and travel uncertainties all have the potential to jeopardize analysis, policy development, and enforcement, but, more importantly, have the potential to raise legitimacy issues and obscure the interpretation of impacts. The purpose of this chapter is to examine the effects of spatial uncertainty in the context of sex offender analysis and management as well as review spatial optimization approaches to support this. This work enables a framework and direction for improving the quality of sex offender analysis and also provides the basis for quantifying certainty relative to data quality.
- American Civil Liberties Union [ACLU]. (2005). ACLU Ask U.S. Supreme Court to review Iowa’s sex offender residency restriction. http://www.aclu.org/racial-justice_prisoners-rights_drug-law-reform_immigrants-rights/aclu-asks-us-supreme-court-review- Last Accessed 07/31/11.
- American Civil Liberties Union [ACLU]. (2009). ACLU challenges Miami-Dade County’s 2,500-foot sex offender residency restriction. http://www.aclufl.org/news_events/?action=viewRelease&emailAlertID=3760 Last Accessed 07/31/11.
- Boyd, S. (2008). Allouez restrictions on sex offenders unchanged. Green Bay Press Gazette. http://www.greenbaypressgazette.com/article/20081222/GPG0101/812220535/1207/GPG01 Last Accessed 07/31/11.
- Cayo, M. R., & Talbot, T. O. (2003). Positional error in automated geocoding of residential addresses. International Journal of Health Geographics, 3, 5.Google Scholar
- Chaiken, J. M. (1998). Sex offenders and offending: Learning more from national data collection programs. National Conference on Sex Offender Registries. Washington, DC: Bureau of Justice Statistics.Google Scholar
- Curtis, K. (2003). California ‘Loses’ 33,000 sex offenders. Associated Press. http://www.cbsnews.com/stories/2003/01/08/national/main535654.shtml Last Accessed 07/31/11.
- Curtin, K.M. & R.L. Church. (2006). A Family of Multiple-Type Discrete Dispersion Models. Geographical Analysis, 38(3), 248–270.Google Scholar
- Dangermond, J. (1988). A review of digital data commonly available and some of the practical problems of entering them into a GIS. In W. J. Ripple (Ed.), Fundamentals of geographic information systems: a compendium (pp. 41–58). Bethesda, MD: American Congress on Surveying and Mapping.Google Scholar
- Eakins, P. (2008). Long beach neighbourhood fights to move sex offenders. Press-Telegram. http://www.presstelegram.com/news/ci_8291281 Last Accessed 01/31/11.
- Environmental Systems Research Institute [ESRI]. (2010). Euclidean distance algorithm. http://webhelp.esri.com/arcgisdesktop/9.3/index.cfm?TopicName=Euclidean_Distance_algorithm Last Accessed 07/31/11.
- Freeman, N.H., & Sandler, J.C. (2010). The Adam Walsh Act: a false sense of security or an effective public policy?. Criminal Justice Policy Review, 21(1), 31–49.Google Scholar
- Goodchild, M. F., & Gopal, S. (1989). Accuracy of spatial databases. London: Taylor and Francis.Google Scholar
- Grubesic, T.H., & Murray, A.T. (2004). Assessing the locational uncertainties of geocoded data. Proceedings from the 24th Urban Data Management Symposium. Chioggia, Italy.Google Scholar
- Jones, C. B. (1997). Geographical information systems and computer cartography. Harlow: Longman.Google Scholar
- Longley, P. A., Goodchild, M. F., Maguire, D. J., & Rhind, D. W. (2005). Geographic information systems and science (2nd ed.). New York: Wiley.Google Scholar
- Love, R. F., Morris, J. G., & Wesolowsky, G. O. (1988). Facility location: models and methods. New York: North-Holland.Google Scholar
- Matson, S. (1999). Sex offender registration: policy overview and comprehensive practices. http://www.csom.org/pubs/sexreg.html Last Accessed 07/31/11.
- Mazza, S. (2008). Gardena gets tougher on sex offenders. Daily Breeze. http://www.dailybreeze.com/ci_9834634 Last Accessed 01/31/11.
- National Center for Missing and Exploited Children [NCMEC]. (2010). Map of registered sex offenders in the United States. http://www.missingkids.com/en_US/documents/sex-offender-map.pdf Last Accessed 07/31/11.
- Openshaw, S., & Taylor, P. (1981). The modifiable areal unit problem. In N. Wrigley & R. Bennett (Eds.), Quantitative geography: a British view (pp. 60–69). London: Routledge and Kegan Paul.Google Scholar
- Robinson, A. H., Morrison, J. L., Muehrcke, P. C., Kimerling, A. J., & Guptill, S. C. (1995). Elements of cartography (6th ed.). New York: Wiley.Google Scholar
- United States Census Bureau [Census]. (2001). Scale, generalization, and limitations of the cartographic boundary files. http://www.census.gov/geo/www/cob/scale.html Last Accessed 07/31/11.
- Verigin, H. (1999). Data quality parameters. In P. A. Longley, M. F. Goodchild, D. J. Maguire, & D. W. Rhind (Eds.), Geographical information systems: principles and technical issues. New York: Wiley.Google Scholar
- Winston, W. L. (2004). Operations research: applications and algorithms (4th ed.). New York: Wadsworth.Google Scholar