Printer Friendly

Where are they? A spatial inquiry of sex offenders in Brazos County.

INTRODUCTION

Several studies in the past decade have analyzed sexual abuse on males and females under the age of 18 in the United States (Tjaden and Thoennes 1998, Greenfield 1997). Finkelhor (1994) informed that one in five females and one in seven males are sexually abused by the age of 18. The fear, both personal and altruistic, of becoming a victim of sexual abuse consciously or semiconsciously exists in the community. This fear has been rekindled even more with the recent unfortunate events of sex-related crimes throughout the nation.

In an attempt to redeem neighborhoods of these mishaps, law-enforcement agencies have regulated various sex offender restriction statutes that can help manage the risk posed by sex offenders. While numerous statutes have been in place for about four decades now, the Jacob Wetterling Crimes Against Children and Sexually Violent Offenders Registration Program (1) (42 U.S.C. 14071 et seq.) of 1994 reshaped the way law enforcers managed Registered Sex Offenders (RSOs) in the United States. This law required convicted sex offenders to register and notify their law administrators of their movement. Information about offenders such as each offender's name, age, gender, height, weight, race, and details of the offense are provided to the state authorities such as the State Department of Public Safety.

After the death of Megan Kanka at the hands of a convicted sex offender living across the street in New Jersey, President Clinton signed an amendment to this law, requiring all states to make the information about pedophiles and rapists available to the general public (Beck and Travis 2004, Engeler 2005). When this law was signed in May of 1996, the local citizenry was and continues to be informed of the whereabouts of sex offenders in their community. This notification system exists in all the states, and makes it mandatory for the offenders to inform the respective state authorities about their movements anywhere in the United States. This information then is made public to notify the communities of the offenders' details. The Jacob Wetterling act sets minimum standards by federal administration for states. Individual states, on the other hand, can impose more stringent requirements on the offenders. In Texas, the Code of Criminal Procedure, SB1054, Article 42.12, Section 13B (Texas Legislature Online, 78th Legislature) mandates the Child Safety Zone (CSZ) for the state of Texas to be "within 1,000 feet of premises such as school, day-care facility, playground, public or private youth center, public swimming pool, or video arcade facility, places where children generally gather." Currently, the state of Texas stipulates anywhere from 200 feet to 1,000 feet for this zone, which follows the drug-free zone restrictions used in the state. This study investigates the locations of sex offenders' residences with respect to the CSZ using a standard 1,000-foot buffer (as mandated by the Texas legislature and currently under discussion in the legislature (2)) around the child facilities on proximity to an RSO, area of risk owing to the RSO presence, and how such information can be communicated to the general public.

The movement of RSOs within and between different states with varying restriction laws makes it difficult for the offenders and the supervising authorities to exactly determine the distance between the residences of the offenders and the CSZ. However, current trends in modern technology such as using a geographic information system (GIS) have made it feasible to closely supervise the mobility restrictions of the registered sex offenders. GIS provides a powerful tool to map these locations, efficiently update the data, and frequently check for violators residing in the CSZ. This study uses the current restriction laws stipulated by the Texas legislature to inquire: (1) How many sex offenders reside within the Child Safety Zone (1,000-foot buffer)? (2) how to identify the known offenders in closest proximity to where a victim is reported missing? and (3) how can this digital mapping system help notify and bring awareness to the local community?

BACKGROUND

Felson and Clark (1998), in their analysis, reported that all crimes are a result of available opportunities. The laws that have been enacted to reduce sex crimes attempt to reduce these opportunities as much as possible. Cohen and Felson (1979) stated that the increase in opportunities of crime is because of the presence of three elements: (1) a suitable target, (2) absence of a guardian, and (3) a motivated offender. This is defined as the Routine Activity Theory (RAT). Therefore, occurrence of sex crimes can be reduced or checked when a guardian is aware of the presence of a motivated offender who may attack a suitable victim. Megan's Law, in a sense, performs a similar task for society. The law-enforcement agencies inform the respective communities of the presence of a sex offender through the notification system to increase the awareness of individuals living in close proximity to the offender. As a result, these acts help to avoid or reduce the chances of a motivated offender meeting a suitable target in space and time. Extensive literature that analyzes proximity and sex crime are reported in Walker, Golden, and VanHouten (2001).

Similarly, to monitor the adjudicated offenders, agencies such as the Parole Board and the Board of Pardon have developed restrictions that control the mobility of the offenders in the community. These restrictions have received wide attention recently.

Robertson (2000, 109) suggested that:
 ... an understanding of geographic trends of registered sex
 offenders, especially as they relate to schools and daycare
 facilities, may help police narrow their suspect lists in open
 cases, to those individuals contained within their registration
 database, living within a close proximity to the victim
 procurement site, who pose a high risk of recidivism.


Although RAT indicates that there is a relationship between proximity and repeated sex crimes, Levenson and Cotter (2005) reported that there is lack of empirical research in this area. Canter and Larkin (1993) proposed the commuter and marauder hypothesis based on the components of proximity and crime. They proposed that commuters travel to commit crimes in other areas beyond their homes and the marauder criminals use the areas around their homes to commit crimes. Crime and proximity in relation to Child Safety Zone (commuters) has been investigated spatially by Walker et al. (2001). Their study analyzed the proximity of sex offenders and the potential victims using GIS. They used the Arkansas Code of 1,000-foot buffer and identified the offenders who lived within this distance. They also investigated the number of offenders who resided within 1,000 feet from such premises as schools, parks, and day-care centers. In several cases, sex offenders were found to be living in close proximity to the premises where children congregate. Also, just about half of the offenders (47 percent) were reported to be living within the 1,000-foot restriction area.

Although the impact of Megan's Law, though spatial in nature, has not been investigated spatially in relation to proximity and crime (marauder), its effect has been reviewed for its mode of notification by Thomas (2003). His study reported that the methods of disseminating the community notification (Megan's Law) was through leaflets or flyers, community notification meetings, and other means such as the media, "need-to-know" basis, and marked-car licenses in various communities across the United States. While the exact distance traveled by an offender to commit a sex crime remains to be investigated, Megan's Law is based on the premise that an individual in immediate and close proximity to a sex offender is at risk of victimization and thus needs to be notified about sex offender presence in the community. In Texas, this act requires notification (3) (Texas Criminal Procedures Code Annotated Section 62.201(a)) by mail to households within the zone of influence, defined in two levels depending on the location of the urban or rural setting of an RSO's dwelling: immediate risk--within three city blocks (or approximately 0.33 miles) in urban or subdivided settings, and lateral risk--within one mile in rural settings (areas outside subdivisions).

Conversely, Terry Thomas (2001) reported that the Sex Offender Act of 1997 in the United Kingdom had unforeseen consequences. The implication of this law required setting up a mechanism of registration to help the police decide the risk caused by a dangerous sex offender. This idea of registration of sex offenders was based on three arguments: (1) to help the police identify the suspects after a crime, (2) to prevent crime, and (3) to act as a deterrent (Home Office, 107). The registration laws in United States serve the same purpose. However, residential restrictions for the sex offenders vary from state to state. In Illinois, the least restrictive distance is 500 feet, while California restricts the dwelling of sex offenders within a quarter mile of schools (Levenson and Cotter 2005). Texas law allows these restrictions to vary for each offender, depending on the type of offense committed. Presently, the parole board assigns this distance based on the individual's offense. This distance can be anywhere up to 1,000 feet. This makes it difficult for the law-enforcement officials to keep a check on the movement of these offenders. To alleviate these difficulties, the Texas legislature has been forwarded a petition to make the restrictive distance of 1,000 feet uniform throughout the state of Texas.

Nonetheless, the undisputed fact remains that the primary aim of the notification system is to increase the vigilantism of communities. One of the more recent methods of increasing vigilantism against crime is through Web-based technologies. Spatial technology, in addition to being used as a mapping tool (e.g., Walker et al. 2001, Foote and Crum 1995), can be effectively used as a communication tool using Web GIS. While Web GIS has been used as a communication tool for some time now (e.g., Ramasubramanian 1995), its application to communicate sex crimes has been increasingly advocated (e.g., Albrecht and Pingel 2005, Shyy, Stimson, Western, Murray, and Mazerolle 2005). It is important to communicate information regarding sex crimes because, as suggested by Sampson, Raudenbush, and Earls (1997), it increases the "collective efficacy" of the community. They state that an increase in collective efficacy of a community results in lower expected levels of crime.

Therefore, this study provides a methodological approach to identify and notify individuals about the sex offenders in their community using GIS. Deriving from the RAT, sex crime, as a result of proximity, can occur in two ways. In the absence of a guardian by (1) proximity to probable or suitable victims and (2) proximity to motivated offenders. While a detailed literature review by Walker et al. (2001) assesses the issues of proximity to suitable victims using GIS, proximity to motivated offenders has been neglected as a cause of sex crime. The following investigation will help (1) identify the percentage of offenders who violate the residential restrictions if and when 1,000-foot restriction is approved; (2) identify the areas of probable crime in close vicinity to the offenders' homes; and (3) measure the effectiveness of developing a Web-based GIS notification system that maps the offenders and the restriction zones.

METHODOLOGY

Study Area

The area under study, Brazos County, Texas, has a population of about 152,000 (U.S. Census 2000), comprised of the cities of Bryan, College Station, and Wellborn. About 88 percent of the population of Brazos County resides in the twin cities of Bryan and College Station. The Texas Department of Public Safety (TXDPS) lists 164 registered sex offenders in the zip codes of Brazos County. Also included on this list are the name of each offender (including alias names), date of birth, gender, race, current residential address, information pertinent to the offense, and latest photograph with other information. Without a geographical system in place to track registered sex offenders, the cities of College Station and Bryan have not been able to check the violators who reside within the Child Safety Zones for a long time. Thus, it was necessary to provide the law-enforcement authorities with tools to help them locate such violators residing in the neighborhoods within child safety zones.

Spatial Inquiry into the Location of Sex Offenders

The spatial information for Brazos County was provided by the city of Bryan Information Technology (IT) Department. The two main themes created for this analysis were (1) the Child Safety Zone and (2) the location of residence of each offender.

[FIGURE 1 OMITTED]

This study required the geocoding of day-care facilities in Brazos County obtained from the Department of Family and Protective Services, and schools and parks in Brazos County. Schools, parks, and day-care centers in Brazos County were geocoded using parcel-level data. These are the locations where children generally gather and were used as basic themes to develop the CSZ. The address information of the RSOs was obtained from the Texas Department of Public Safety's Sex Offender Database. The spatial data of Brazos County parcels was used to geocode (single-field (file)) the "USaddress" field with the address database files of the day-care centers and the registered sex offenders in Brazos County.

Matching interactively, the unmatched addresses of the offenders were searched and selected. About 12 of the 164 addresses of the sex offenders were either located out of the Brazos County or could not be located in the Brazos parcels file and thus were not used for further analysis. The layers with information on parks and schools in Brazos County were buffered for a distance of 1,000 feet. These layers were appended and merged together to form the new dissolved layer of all the buffers that formed the Child Safety Zone. Playgrounds, public or private youth centers, and public swimming pools are a part of the schools in Bryan and College Station. Once the sex offender locations were geocoded, spatial query was made to locate the offenders residing in the CSZ (see Figure 1).

Locating Known Offenders

Risk-assessment tools to predict risk have been investigated for some time now (Hanson and Thornton 2000, Thornton et al. 2003). The Static 99 risk-assessment tool generates four categories of risk: low, low-medium, medium-high, and high, and has been validated by Beech, Friendship, Erikson, and Hanson (2002) and Thornton (2002). By using the Texas Case Classification and Risk-Assessment tool, community supervision officers have established three different levels of risks associated with each registered sex offender. The risk levels based on the nature of the crime are high, medium, and low (Texas Department of Criminal Justice Website). These risk levels are assigned by the Department of Corrections, the Department of Social and Health Service, and the Sentence Review Board. For high-risk offenders, the TXDPS is required to send postcards to residents in the one-mile radius of a nonsubdivided area and a three-block radius of a subdivided neighborhood within seven days of release and ten days of move of a sex offender to their neighborhood. This is because high-risk offenders are considered the most probable convicts to reoffend. Even though only the moving in of a high-risk offender requires notification to the community, every offender induces a certain level of perception of risk in the community where he or she lives. Therefore, the Critical Risk Zones (CRZs) are classified based on the risk level of an offender as high, moderate, and low and by proximity as immediate and lateral risk.

Currently, law-enforcement agencies buffer the location where a victim is reported missing and identify the offenders within the buffer to check the possible reoffenders of the reported crime (e.g., Hubbs 2003). This method, however productive, does not allow the law-enforcement officials to identify the closest offender with the highest level of risk. Including the dimension of proximity and the level of risk in this search can help the officials search for the suspect beginning with the closest high-risk offender to the farthest low-risk offender, possibly minimizing the time to find the suspects most probable of committing the reported crime.

This study utilized the standards required by Megan's Law as the baseline to geographically analyze the victim procurement site. The Critical Risk Zone of each sex offender was based on the distances specified in Megan's Law. Two zones: immediate risk zone, a three-block distance from the residence of the offender, and lateral risk zone, a one-mile distance from the residence of the registered sex offender, were created as the "area of influence" for each offender. These were termed the "Critical Risk Zones."

Community Notification

The spatial mapping technique to locate sex offenders can be a useful community notification tool. Therefore, a Web-based GIS interface was developed and launched at the city of Bryan police department Website. This Website can aid the individuals of the community to access the spatial georeferenced information regarding registered sex offenders and child safety zones. Public access to this service was monitored for number of hits to assess if individuals of the Brazos County used this service, resulting in improved collective efficacy of the community.

RESULT

The descriptive analysis of the registered sex offenders residing in Brazos County, Texas, showed that 73 percent of the offenders were white. More than 10 percent of offenders have committed a crime at least two or more times; about 5 percent of the offenders were females; and more than 10 percent of the offenders were high-risk offenders. About 44.2 percent of the offenders were 15 to 30 years old when the crime was committed, and 35 percent of them were 30 to 45 years old. More than 50 percent of the victims were 15 to 25 years old, and more than 80 percent (131) of the victims were females.

[FIGURE 2 OMITTED]

Spatial Inquiry into Location of Sex Offenders

The offenders in the CSZ (77 of 164) were categorized based on their risk levels (see Figure 2). Thirty-eight were identified as low-risk offenders, 27 as moderate-risk offenders, and 12 as high-risk offenders. An investigation, similar to that conducted by Walker et al. (2001), revealed that six (50 percent) of these high-risk offenders were within a 1,000-foot proximity of at least one day care, four were near schools, and 11 were in close proximity to parks in the cities of Bryan and College Station. Four offenders were identified within 1,000 feet of at least one day care and one park in Bryan. One high-risk offender, who had been charged with indecency with females age 12 and 14 in 1982 and females age 13 in 1990, resides within 1,000 feet of one day care, one park, and one school in Bryan.

The spatial query showed that an alarmingly high percentage (55.41 percent) of offenders resided within the CSZ. The proximity, as shown in Figure 2, of the offenders to the schools, parks, and day-care centers in Bryan/College Station was not in adherence with the state restriction of 1,000 feet in Texas. Although this percentage may vary with continuous moving in or out of the offenders in Brazos County, the findings at this snapshot of time reveal that a high percentage of these offenders reside within the CSZ.

[FIGURE 3 OMITTED]

Locating Known Offenders

The zones were classified based on the risk level and proximity, according to the following six divisions: (i) Low Immediate Risk Zones, (ii) Low Lateral Risk Zones, (iii) Moderate Immediate Risk Zones, (iv) Moderate Lateral Risk Zones, (v) High Immediate Risk Zones, and (vi) High Lateral Risk Zones (see Figure 3). These zones may or may not overlap for two or more offenders based on the distance between each other. Using GIS, the location where the child was reported missing can be georeferenced. Upon identifying that location, a list of registered sex offenders who lie within the immediate risk zone and lateral risk zone can be generated for the purpose of investigation.

This risk-level analysis provides a platform from where the authorities can identify the registered offender residing in the closest proximity of a reported victim, or provide some indication as to where to direct the investigations after a victim is reported missing.

Community Notification

The press release of the new Web-based GIS service was announced on May 5, 2005. Access to this Website was monitored and automatically recorded to measure the number and sources of hits (see Figure 4). The hits on the city of Bryan RSO Website shared about 50 percent of all the hits on the city of Bryan Website immediately after the press release of the new Web-based tool. Also, May of 2005 reported three times the total hits (67,777) compared to all other months except the holiday month of December 2004. Although the large increase in access to this Website can be attributed to the press release, the monitoring and assessment of total number of hits on the Website in future can show if the individuals of the community accessed the Website to constantly update themselves. Such assessment can indicate increased communication of sex crime-related information through the Web-based GIS service. Except for December 2004 (holiday season), there was an increase in access to the Bryan County Website in May of 2005 when the Web-based service was launched.

DISCUSSION

Sex-crime analysis, like any other crime analysis, is associated with the notion of place with a geographical location. Occurrence of crime has a spatial dimension that has been explored since the 1970s (Chainey and Ratcliffe 2005). Using GIS to analyze the sex-crime occurrence now is advocated more than ever (Grubesic, Mack, and Murray 2007). Thus, it is important to use spatial technology efficiently to analyze the occurrence of crime and as a communication tool to disseminate sex crime-related information. This study used GIS to analyze the location of sex offenders within the CSZ. Enforcement of a 1,000-foot buffer for CSZ would result in a high percentage of offenders being in violation of the law and require relocation by the authorities to avoid having them in close proximity to children. However, irrespective of where the offenders reside, they bring some amount of risk to the community. GIS can help map that risk using existing law as a framework to help locate potential offenders in proximity to the location where a sex crime was committed. Advancement in spatial technology allows dissemination of sex crime-related information to individuals of the community to increase their awareness about existing offenders in the neighborhood.

The high percentage (more than 55 percent) of violators living in the CSZ can be a concern for the local community. It has to be noted that this high percentage was due to the fact that these offenders currently reside based on the restrictions that do not follow the 1,000-foot distance. Cross-verification of the ethnicity of offenders with their current photos on the Website revealed that a high percentage of "White" offenders were reported because the general classification was categorized as Black or White. Hispanic-looking individuals were classified as White as well. Nevertheless, at the discretion of the authorities, the violators can be notified to relocate and also suggested to locate outside the CSZ, yet still be accessible to their jobs.

The CRZ can help law-enforcement officers identify the registered offenders in the closest proximity to a victim reported missing or at the location of crime. This spatial service can be made available to the law-enforcement agencies to investigate a reported crime. The categories of risk used here are not empirically evolved, but have been used commonly by several states in the United States.

The Web-based GIS service was available for local community members to increase awareness among the community about registered sex offenders' residence locations in reference to their homes, workplaces, as well as places they visit on a regular basis. The Website provides a sense of geographical reference to law enforcers and to the local community. Increased access to the Website indicates increased public awareness and interest in using Web-based mapping services as a communication tool. This Web-based service helps individuals relate the location of sex offenders with their residences and the paths their children take to commute to school.

CONCLUSION

This study investigated the use of spatial technology to map and communicate sex crime-related information. GIS was used to map the locations of places where children congregate, such as parks, schools, and day-care centers, and the residences of registered sex offenders in Brazos County, Texas. Based on the locations where children congregate, more than half of the offenders were found to be in violation of the restriction distance mandated by the Texas legislature. Also, offenders were mapped for the risk they are perceived to bring to the community. This area under risk for each offender was mapped based on the notification system and level of risk, allowing law enforcers to identify the offenders with greatest risk and closest proximity to a reported sex crime. While spatial technology can be used to map a sex crime, it also can help communicate this information visually to the individuals of the community. This is evident from the analysis in this study when the Web-based sex-offender service was monitored for the number of hits after its induction. The methodology proposed in this article also can be an effective tool and more importantly cost-effective and time-effective in managing risk. With the availability of GIS, geocoding of offenders' residences, and the availability of themes such as parks and schools, sex crimes related to children can be efficiently managed. Therefore, the present study hopes to encourage the use of GIS technology in investigating crime-management strategies, especially related to sex crimes.

One primary limitation of this study is the use of a common 1,000-foot buffer to create the CSZ. The restriction distance varies between each state. In Brazos County, the restriction distance varies with the individual offender. The significance of the distance is more perceived than empirically tested. Therefore, a future scope of this study would include empirical examination of the influence of restriction distance on the risk to the community using GIS. Nonetheless, this study demonstrated the use of GIS to efficiently map and communicate the information related to sex crimes to the residents of the community and assist law enforcers to regulate sex crimes in their jurisdictions.

[ILLUSTRATION OMITTED]

References

Albrecht, J., and J. Pingel. 2005. GIS as a communication process: Experiences from the Milwaukee COMPASS project. In F. Wang, ed., Geographic information systems and crime analysis. Hershey, PA: Idea Group Publishing, 1-23.

Beck, V. S., and L. F. Travis III. 2004. Sex offender notification and fear of victimization. Journal of Criminal Justice 32: 455-63.

Beech, A., C. Friendship, M. Erikson, and R. Hanson. 2002. The relationship between static and dynamic risk factors and reconviction in a sample of UK child abusers. Sexual Abuse: A Journal of Research and Treatment 14: 155-67.

Canter, D. V., and P. Larkin. 1993. The environmental range of serial rapists. Journal of Environmental Psychology 13: 63-69.

Chainey, S., and J. Ratcliffe. 2005. GIS and crime mapping. Chichester: John Wiley and Sons.

Cohen, L. E., and M. Felson. 1979. Social change and crime rate trends: A routine activity approach. American Sociological Review 44: 588-608.

Engeler, A. 2005. Is your child a target? The sex offender next door. Good Housekeeping 240, no. 5: 192-97.

Finkelhor, D. 1994. Current information on the scope and nature of child sexual abuse. Child Abuse and Neglect 4: 31-53.

Felson, M., and R. V. Clarke. 1998. Opportunity makes the thief: Practical theory for crime prevention. Police Research Series, Paper 98. Home Office, Policing and Reducing Crime Unit. Great Britain: Research, Development and Statistics Directorate.

Foote, K., and S. Crum. 1995. Cartographic communication (November 17, 2007), http://www.colorado.edu/geography/ gcraft/notes/cartocom/cartocom_f.html.

Greenfeld, L. 1997. Sex offenses and offenders: An analysis of data on rape and sexual assault. Washington D.C.: U.S. Department of Justice, Bureau of Justice Statistics.

Grubesic, T. H., E. Mack, and A. T. Murray. 2007. Geographic exclusion: Spatial analysis for evaluating the implications of Megan's Law. Social Science Computer Review 25, no. 2: 143-62.

Hanson, R., and D. Thornton. 2000. Improving risk assessments for sex offenders: A comparison of three actuarial scales. Law and Human Behavior 24: 119-36.

Hubbs, R. 2003. Mapping crime and community problems in Knoxville, Tennessee. In M. R. Leipnik and D. R. Albert, eds., GIS in law enforcement: Implementation issues and case studies. London: Taylor & Francis.

Levenson, J. S., and L. P. Cotter. 2005. The impact of sex offender residence restrictions: 1000 feet from danger or one step from absurd? International Journal of Offender Therapy and Comparative Criminology 49, no. 2: 168-78.

Ramasubramanian, L. 1995. Building communities: GIS and participatory decision making. Journal of Urban Technology 3, no. 3: 67-79.

Robertson, L. S. 2000. Assessment of the proximity of registered sex offenders to schools and day cares: St. Louis City, Missouri, 1998. MO: Department of Administration of Justice.

Sampson, R., S. Raudenbush, and F. Earls. 1997. Neighborhoods and violent crime: A multilevel study of collective efficacy. Science 277: 918-24.

Shyy, T-K., R. J. Stimson, J. Western, A. T. Murray, and L. Mazerolle. 2005. WebGIS for mapping community crime rates: Approaches and challenges. In F. Wang, ed., Geographic information systems and crime analysis. Hershey, PA: Idea Group Publishing, 14, 236-53.

Texas Department of Family and Protective Services, Child Care Licensing Division (November 20, 2004), http://www. tdprs.state.tx.us/Child_Care/About_Child_Care_Licensing/ default.asp.

Texas Department of Criminal Justice Website (January 10, 2005), http://www.tdcj.state.tx.us/cjad/cjad-who-sa-tool. htm.

Texas Department of Public Safety (November 20, 2004), http:// www.txdps.state.tx.us/.

Texas Legislature Online, 78th Legislature (November 20, 2004), http://www.tdh.state.tx.us/hcqs/plc/csotlaws. htm#legislation.

Tjaden, P., and N. Thoennes. 1998. Prevalence, incidence, and consequences of violence against women: Findings from the national violence against women survey. Washington, D.C.: U.S. Department of Justice, National Institute of Justice.

Thomas, T. 2003. Sex offender community notification: experiences from America. The Howard Journal 42, no. 3: 217-28.

Thomas, T. 2001. Sex offenders, the home office, and the Sunday papers. Journal of Social Welfare and Family Law 23, no. 1: 103-8.

Thornton, D., R. Mann, S. Webster, L. Blud, R. Travers, C., Friendship, and M. Erickson. 2003. Distinguishing and combining risks for sexual and violent recidivism. Annals of the New York Academy of Sciences 989: 225-35.

Thornton, D. 2002. Constructing and testing a framework for dynamic risk assessment. Sexual Abuse: A Journal of Research and Treatment 14: 139-53.

U.S. Census Bureau, http://www.census.gov.

Walker, J. T., J. W. Golden, and A. C. VanHouten. 2001. The geographical link between sex offenders and potential victims: A routine activities approach. Justice Research and Policy 3, no. 22: 15-33.

(1.) Details of the Jacob Wetterling Crimes Against Children and Sexually Violent Offenders Registration Program can be obtained at the Cornell University Law School U.S. Code collection at http://www.law.cornell.edu/uscode/html/uscode42/ usc_sec_42_00014071--000-.html.

(2.) The existing Texas legislature requires a distance of 1,000 feet. However, the Board of Pardon and the judiciary system can decide this distance case by case. However, Martha Wong, Texas state representative, has moved for an amendment that mandates that all offenders be subjected to a 1,000-foot distance throughout the state of Texas. Details regarding the House Bill 1828 can be found on the Texas legislature Website at http://www.capitol.state.tx.us/.

(3.) Details regarding the notification system in Texas are available at http://tlo2.tlc.state.tx.us/statutes/cr.toc.htm, titled "Article 62.201. Additional public notice for individuals subject to civil commitment."

Dr. Praveen Maghelal is an assistant professor in the Department of Urban and Regional Planning at Florida Atlantic University and has educational background in civil engineering, architecture, and planning. His research interest includes spatial planning, physical activity and built environment, and transportation planning.

Corresponding Address:

111 East Las Olas Boulevard

Department of Urban and Regional Planning

Florida Atlantic University

Fort Lauderdale, Florida 33301

Phone: (954) 726-5030

Fax: (954) 762-5673

pmaghela@fau.edu

Miriam Olivares is a Ph.D. candidate in Urban and Regional Science at Texas A&M University, from where she earned a master's degree in land development. She holds a bachelor's degree in architecture with emphasis on planning from Monterrey Tech, Mexico. Her research interest is in sustainable development. Currently, she is working on her dissertation regarding sustainable communities and sex-crime management.

Dr. Douglas Wunneburger is a senior lecturer in the Department of Landscape Architecture and Urban Planning at Texas A&M University. His primary research interests include the integration of spatial and information technology for studies in landscape ecology-based planning and management.

Gustavo Roman is the Director of Information Technology for the City of Bryan, Texas. He holds master's and bachelor's degrees from Texas A&M University and has more than 12 years of municipal government experience, including seven-plus years in the implementation and management of GIS systems.
Figure 4. Chart and table of total number of hits to access the
sex offender Web service

Summary by Month

 Daily Average Monthly
 Totals

Month Hits Files Pages Visits Sites

May 2005 67777 47263 15354 459 4939
Apr 2005 24242 15410 5354 213 3219
Mar 2005 23776 14236 6270 226 3495
Feb 2005 22161 13352 5563 262 3456
Jan 2005 21700 13195 5621 356 4625
Dec 2004 58305 23736 27928 957 16659
Nov 2004 15938 10612 3633 146 1814
Oct 2004 16401 11292 3709 144 2001
Sep 2004 15797 11035 3564 127 2062
Aug 2004 15989 10820 3642 127 1926
Jul 2004 15598 10979 3533 135 1866
Jun 2004 14743 10325 3455 120 1845

Summary by Month

 Monthly Totals

Month KBytes Visits Pages Files Hits

May 2005 14997006 8739 291740 898001 1287773
Apr 2005 11878090 6410 160623 462325 727261
Mar 2005 9754452 7033 194376 441340 737066
Feb 2005 10149913 7362 155774 373879 620522
Jan 2005 9163086 11064 174271 409075 672723
Dec 2004 18585619 29684 865796 735838 1807461
Nov 2004 6621826 4399 109006 318375 478166
Oct 2004 6963752 4478 114988 350074 508444
Sep 2004 7617430 3816 106937 331051 473912
Aug 2004 42513587 3942 112922 335437 495687
Jul 2004 7155400 4209 109529 340363 483545
Jun 2004 6884369 3623 103675 309772 442290

Totals 152284530 94759 2499637 5305530 8734850
COPYRIGHT 2008 Urban and Regional Information Systems Association (URISA)
No portion of this article can be reproduced without the express written permission from the copyright holder.
Copyright 2008 Gale, Cengage Learning. All rights reserved.

 
Article Details
Printer friendly Cite/link Email Feedback
Author:Maghelal, Praveen; Olivares, Miriam; Wunneburger, Douglas; Roman, Gustavo
Publication:URISA Journal
Date:Jan 1, 2008
Words:5680
Previous Article:Robust principal component analysis and geographically weighted regression: urbanization in the Twin Cities Metropolitan Area of Minnesota.
Next Article:Tools and methods for a transportation household survey.
Topics:

Terms of use | Privacy policy | Copyright © 2018 Farlex, Inc. | Feedback | For webmasters