* Reducing Housing Options for Convicted |
|
Sex Offenders: Investigating the Impact of |
|
Residency Restriction Laws Using GIS |
|
Paul A. Zandbergen
Department of Geography
University of South Florida
Timothy C. Hart
Department of Criminal Justice
University of Nevada, Las Vegas
* Abstract
Sex offender registries have been established throughout the United States. To date, 16 states have adopted additional residency restriction policies, precluding registered sex offenders from living within a certain distance of places where children gather. This study quantifies the impact of residency restrictions on housing options for registered sex offenders using Orange County, Florida, as a case study. A Geographic Information System (GIS) is employed to identify all occupied residential properties using
JUSTICE RESEARCH AND POLICY, Vol. 8, No. 2, 2006 © 2006 Justice Research and Statistics Association
2 • Justice Research and Policy
* Introduction
In an effort to protect the
Several recent studies have demonstrated that sex offender registration and notification laws may produce unintended outcomes,1 including an in- creased likelihood of reoffending (Edwards & Hensley, 2001; Elbogen, Patry, & Scalora, 2003; Hanson & Harris, 1998; Tewksbury, 2005), public anxiety, retaliation, harassment, stigmatization, and retribution (Edwards & Hensley, 2001; Levenson & Cotter, 2005a; Schram & Milloy, 1995; Tewksbury, 2004; Tewksbury & Lees, 2006; Younglove & Vitello, 2003; Zevitz, Crim, & Farkas, 2000),problemsassociatedwithoffenderdisplacementandreentry(Blair,2004; Edwards & Hensley, 2001; Elbogen et al., 2003; Levenson & Cotter, 2005a; Tewksbury, 2005; Zevitz et al., 2000), obtaining and maintaining employment (Tewksbury, 2004; Tewksbury & Lees, 2006), difficulties in personal and so- cial relationships (Tewksbury, 2004; Tewksbury & Lees, 2006), and limiting housing options (Mustaine, Tewksbury, & Stengel, 2006a; 2006b; Tewksbury, 2004; Zevitz & Farkas, 2000). In short, contemporary sex offender registration and notification laws may do more harm than good.2 Though the consequences
1 See Welchans (2005) for a review of empirical evaluations of sex offender registra- tion and community notification policies.
2 Although none of the aforementioned studies measure the degree to which reof- fending occurs, each provides insight into the adverse effects that notification and resi- dency restriction policies have on sex offenders and which may subsequently result in an increased likelihood of reoffending.
Housing Options for Sex Offenders • 3
of these laws are becoming increasingly apparent, less is known about polices designed to place limits on where sex offenders can live.
Recently both the Colorado Department of Public Safety and the Minnesota Department of Corrections investigated the relationship between reoffending and the geographic proximity of sex offenders to places where children gather. Results of the two studies challenge some of the underlying assumptions of residency restriction laws. The study in Colorado, for example, revealed that child molesters who reoffended do not live closer to schools or daycare cen- ters than
3 Although the Colorado (2004) study used mapping software to produce maps that displayed the proximal relationships between sex offenders and schools and sex offenders and childcare centers, the software was not used to generate “exact measurements of resi- dences’ proximity to schools and childcare centers.” Rather, findings from the Colorado study were based on “an illustration of the sex offender residences…and their proximity to schools and childcare centers,” which showed no apparent relationship (p. 30).
4 • Justice Research and Policy
tailored to serve a compelling interest” – public safety. The ruling marked the first time that a federal appeals court heard a case involving sex offender resi- dency restrictions. While the ruling is binding only in the court’s
One unintended outcome of residency restriction laws may be that they in- crease rather than decrease the likelihood of reoffending. Levenson and Cotter (2005b) recently conducted a survey of registered sex offenders in Florida and found that residency restrictions have forced them to move out of their homes and apartments, prevented them from living with supportive family members, and kept them from acquiring affordable housing. In other words, limits on housing options are forcing some sex offenders to become more isolated, fi- nancially and emotionally stressed, and less
To date, 16 states have adopted residency restrictions: Alabama, Arkan- sas, California, Florida, Georgia, Illinois, Indiana, Iowa, Kentucky, Louisiana, Michigan, Ohio, Oklahoma, Oregon, Tennessee and Texas. Restrictions vary with respect to the type of offender to which they apply (i.e., all sex offend- ers or only those under active supervision), as well as the type of location for which they apply and the size of the buffer or restrictive zone. For example, Iowa currently has a
A bill filed recently in the Florida House of Representatives would have increased the residency restriction that the state imposes on sex offenders from a buffer distance of 1,000 feet to 2,500 feet (Florida House Bill 91CS, 2006).
Housing Options for Sex Offenders • 5
Although the bill failed to pass, other states (e.g., California and Texas) are considering similar
The current study employs Geographic Information Systems (GIS) to quantify the impact of a 1,000- and
* Data and Methods
The methodology employed in this study relies on using the parcel database of Orange County, Florida, to identify locations of all the “places where children congregate,”5 as well as locations of all residential properties that fall inside 1,000- and
4 This study employs buffer distances of 1,000 and 2,500 feet. Even though the bill to increase the distance to 2,500 feet did not pass in the Florida House of Representa- tives, the distance of 2,500 feet is in effect in many local jurisdictions in Florida and is being considered by other states.
5 Florida’s Criminal Procedure and Corrections code states that if certain crime vic- tims are under the age of 18, then the courts must impose upon the convicted offender a prohibition on living within 1,000 feet of a school, daycare center, park, playground, bus stop, or other “places where children regularly congregate.” In the original statute, only schools, daycare facilities, parks, and playgrounds were specifically mentioned; but in 2004, public school bus stops were added to the law. Restrictions only apply to those convicted after October 1, 1997.
6 • Justice Research and Policy
Parcels
The 2004 parcel database for Orange County was obtained from the Or- ange County Property Appraisers Office. This database contains the boundaries of all legal properties, and includes information on the physical address of the property, the owner(s), tax assessment information, and zoning. The database was obtained in a
Attractions
A list of attractions of interest to children was obtained from Orange County. Addresses for the 22 records were exported to a DBF file and parcel geocoded6 using the Orange County parcel database. All 22 records were ac- curately matched and found to correspond to 22 unique properties in the parcel database. In addition, due to the unique nature of Orange County, all of the properties owned and operated by the Disney Corporation were identified in the parcel database and added to the set of attractions. The Disney Corporation runs a large number of different attractions, which were not captured sufficiently in the list of attractions for the entire county. The amount of land owned by Disney is quite large and makes the situation in Orange County a bit different. It should be noted, however, that most of these properties are not near residential areas, and therefore do not influence the analysis of residency restrictions very strongly.
Bus Stops
Locations of all public school bus stops in 2004 were obtained from the Or- ange County School Board. Individual datasets for elementary schools, middle schools, high schools, and special education schools were combined into a single dataset of 17,613 unique locations. The School Board made these data available in a
Daycare Facilities
Locations of Florida daycare facilities in 2003 were obtained from the Florida Department of Children and Families. A subset of data was created for those facilities located in Orange County. Several daycare facilities were found to operate under multiple names at the same physical address; duplicate records were removed. This resulted in a total of 612 daycare facility records. Addresses for the 612 facilities were exported to a DBF file and parcel geocoded using the
6 Parcel geocoding is the process of assigning geographic coordinates to the data based on the county parcel information so that the records can be mapped.
Housing Options for Sex Offenders • 7
Orange County parcel database. A total of 498 records were accurately matched (81%). These 498 daycares are located on 498 unique parcels
Parks
A list of parks was obtained from Orange County. Addresses for the 265 re- cords were exported to a DBF file and parcel geocoded using the Orange County parcel database. A total of 252 records were accurately matched (95%). Of the unmatched records, 6 were boat ramps or fishing piers. The 252 individual parks are located on 237 unique parcels.
Schools
The location of public and private schools in Florida in 2004 was ob- tained from Florida’s Department of Education. A subset was created for those schools located in Orange County. Schools identified as adult education, such as vocational/technical schools, community colleges, and universities, were excluded, as well as those schools that were identified as inactive. In addition, several private schools were found to operate under multiple names at the same physical address; duplicate records were removed. This process resulted in a total of 309 schools. Addresses for the 309 records were exported to a DBF file and parcel geocoded using the Orange County 2004 parcel database. A total of 261 records were accurately matched (84%), including all public schools. These 261 schools are located on 254 unique parcels, since several of the school sites include multiple
Zoning Information
The Orange County parcel database contains a specific zoning category for each parcel; these categories, however, vary with each jurisdiction since each incorporated area within the county has its own zoning code. Therefore, detailed zoning codes were obtained from Orange County and all incorpo- rated areas: Apopka, Bay Lake, Belle Isle, Eatonville, Edgewood, Lake Buena Vista, Maitland, Oakland, Ococee, Orlando, Windermere, Winter Garden and Winter Park. Zoning codes were used to determine the exact meaning and allowable uses of each zoning category. On the basis of this interpretation, generalized zoning categories for all of Orange County were created. Table 1 lists all of the zoning categories in Orange County, including whether residen- tial use is allowed and what unit density is allowed. Three general classes were created: 1)
8 • Justice Research and Policy
* Table 1
Zoning Categories in Orange County, Florida
|
Zoning Category |
Residential Allowed |
Unit Density (No./Acre) |
|
|
|||
|
|
|||||||
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Residential Categories |
|
|
|
|
|
|
|
|
Rural/agricultural |
|
Yes |
Single |
< 0.1 |
|
|
|
|
Rural settlement |
|
Yes |
Single |
0.2 – 2 |
|
|
|
|
Low density residential |
|
Yes |
Single/multi |
2 – 10 |
|
|
|
|
Medium density residential |
Yes |
Single/multi |
10 |
– 20 |
|
|
|
|
High density residential |
|
Yes |
Multi |
20 |
– 75 |
|
|
|
Residential (general) |
|
Yes |
Not specified |
Not specified |
|
|
|
|
|
|
|
|
|
|
|
|
|
Combined Use Categories |
|
|
|
|
|
|
|
|
Planned development |
|
Yes |
Single/multi |
Variable |
|
|
|
|
Mixed use |
|
Yes |
Multi |
10 |
– 75 |
|
|
|
Urban activity |
|
Yes |
Multi |
20 |
– 100 |
|
|
|
Professional office |
|
Limited |
Multi |
10 |
– 75 |
|
|
|
|
|
|
|
|
|
|
|
|
Nonresidential Categories |
|
|
|
|
|
|
|
|
Commercial |
|
No |
- |
- |
|
|
|
|
|
|
|
|
||||
|
Industrial |
|
No |
- |
- |
|
|
|
|
Public |
|
No |
- |
- |
|
|
|
|
Conservation |
|
No |
- |
- |
|
|
|
some cases multiple uses occur within the same parcel (e.g., commercial use on the ground floor and residential units on the 2nd and higher floors of a multi- story building).7
In addition to considering zoning, the presence of water features requires some attention. Parcels represent legal boundaries and include many areas where land occupation is not possible, including water features. Given the many surface water bodies in Orange County, a detailed data layer of surface water bodies was used to erase those parcels and portions of parcels covered by water features.
7 Including parcels which may not be exclusively residential introduces a potential overestimation of the number of properties available to establishing residence. However, apartment complexes and condominiums are located mostly on a single parcel; therefore individual units are not counted separately. This introduces a slight underestimation of the number of properties available to establishing residence. Reliable information on the number of apartment units on each parcel is not available, so the analysis is carried out at the
Housing Options for Sex Offenders • 9
Some parcels completely covered by water do not have a zoning category, but the parcel boundaries for many waterfront residential properties extend into surface water. An example of this is shown in Figure 1. In areas not currently developed, many parcels are quite large and may include large water features. The erase technique in ArcGIS corrects for this potential bias in determining the land area of parcels. In the analysis of distances to parcel boundaries, the original unmodified boundaries were used, but the area calculations by zoning category use the land area corrected for the presence of surface water bodies.
In addition to the zoning category and the presence of water features, a third consideration in the use of the parcel database is whether there are residential units present on the parcels. Many parcels are zoned for residential or combined use, but are not currently developed. Therefore, only those parcels where build- ings were present were selected. A combination of fields in the parcel database
* Figure 1
Parcel Boundaries Covering Water Features
10 • Justice Research and Policy
was used to accomplish this selection, including the year built, the square foot- age of the living area, and the assessed building value. When all three fields were blank and/or zero, the parcel was considered not to have any structure on it. The reliability of these three criteria was confirmed by comparing a sample of selected parcels with digital orthophotography from Orange County for 2004. A random sample of 200 residential and combined use parcels considered “oc- cupied” was selected and a determination was made of whether a structure was indeed present on the parcel; similarly, a random sample of 200 residential and combined use parcels considered “not occupied” was selected and a determina- tion was made of whether a structure was present. For the 200 occupied parcels, 194 were found to contain a residential structure, 1 was found to be vacant, and 5 were found to be under construction. For the 200 unoccupied parcels, 107 were found to be completely undeveloped, 15 were found to have a residential structure, 50 were found to be under construction and 28 were found to be non- residential (i.e., mostly consisting of
Analysis of 1,000- and
A total of five restrictions were used in the analysis: attractions, bus stops, daycares, parks, and schools. With the exception of bus stops, the locations of these restrictions are shown as polygons representing the legal boundaries of the properties.8 Buffer zones of 1,000 and 2,500 feet were created around each unique location; within each of the 5 restriction categories any overlapping buf- fers were dissolved, resulting in one single buffer zone for all locations within a single category combined. This approach is illustrated in Figure 2, which shows the 1,000- and
8 Florida legislation explicitly describes how violations of residency restrictions are to be determined: “The
Housing Options for Sex Offenders • 11
sample study area. Where bus stops are in relatively close proximity to each other, the individual buffers are dissolved to form a single polygon. In effect, this makes it impossible to determine if a particular location is within 1,000 or 2,500 feet of a single bus stop or more than one bus stop. Since the number of bus stops within 1,000 or 2,500 feet is not relevant for determining residency restric- tions, dissolving the individual buffers for each individual restriction category is more meaningful than preserving the separate buffers. Total areas for each of these buffer zones were measured and tabulated and the results are presented in the next section.
The buffer zones of 1,000 and 2,500 feet for each of the five restrictions were compared with the parcel database to determine which occupied residen- tial properties fall within each of the restriction zones. A property was deter- mined to fall within a restricted zone if the boundary of the property is within
* Figure 2
Example of Overlapping 1,000- and
Bus Stops
Parcel Boundaries
12 • Justice Research and Policy
1,000 or 2,500 feet of the boundary of the particular restriction. This approach most accurately represents the interpretation of the Florida statutes (see foot- note 4). For example, in Figure 3, a
For each restriction category, and for all restriction categories combined, all properties falling within the 1,000- and
* Figure 3
Example of Parcels Located Within a
School Property
Parcels Within
Parcels Outside
Housing Options for Sex Offenders • 13
* Results
Zoning in Orange County
Table 2 provides a summary of the zoning categories in Orange County, both in terms of the number of parcels and the total area they occupy. The most dominant category in terms of numbers is low density residential (44.5%), fol- lowed by planned development (25.3%), medium density residential (10.0%) and rural/agricultural (5.8%). In terms of total area, rural/agricultural is by far the most dominant category (48.1%) due to the very large and mostly undevel- oped properties in this category. When considering only those parcels that are residential or combined use and are occupied, the occupation rates of the urban residential categories is very high (93.1% for low density, 91.6% for medium density and 86.3% for high density), a bit lower for the combined use categories (80.7% for mixed use, 80.7% for planned development, 80.7% for professional office and 67.4% for urban activity), and lowest for the rural residential catego- ries (75.1% for rural settlement and 46.2% for rural/agricultural).
Of the 332,859 parcels in Orange County 94.5% are zoned for residential or mixed use. Of those, 85.6% are considered occupied. These properties repre- sent the theoretical number of properties available for establishing residence.
* Table 2
Number and Area of Parcels by Zoning Category in Orange County, Florida
|
|
|
All Properties |
|
|
Percentage Occupied |
|
|||
|
|
|
|
|
|
|||||
|
Zoning Category |
Number |
(%) |
Area (acres) |
(%) |
|
By Number |
By Area |
|
|
|
|
|
||||||||
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Residential and combined use |
|
|
|
|
|
|
|
|
|
|
High density residential |
15,728 |
4.7% |
11,519 |
2.2% |
86.28% |
78.4% |
|
|
|
|
Low density residential |
148,224 |
44.5 |
57,643 |
10.8 |
|
93.06 |
76.9 |
|
|
|
Medium density residential |
33,205 |
10.0 |
9,766 |
1.8 |
|
91.57 |
70.9 |
|
|
|
Mixed use |
1,168 |
0.4 |
4,523 |
0.6 |
|
80.74 |
25.3 |
|
|
|
Planned development |
84,092 |
25.3 |
99,971 |
18.7 |
|
80.69 |
48.5 |
|
|
|
Professional office |
2,278 |
0.7 |
2,486 |
0.5 |
|
80.68 |
67.3 |
|
|
|
Residential |
657 |
0.2 |
331 |
0.1 |
|
88.13 |
88.0 |
|
|
|
Rural/agricultural |
19,155 |
5.8 |
256,880 |
48.1 |
|
46.18 |
30.4 |
|
|
|
Rural settlement |
7,544 |
2.3 |
17,562 |
3.3 |
|
75.13 |
50.9 |
|
|
|
Urban activity |
2,641 |
0.8 |
15,449 |
2.9 |
|
67.40 |
87.9 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Sum |
314,692 |
94.5% |
476,129 |
89.1% |
85.62% |
44.6% |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Nonresidential |
|
|
|
|
|
|
|
|
|
|
Commercial |
7,059 |
2.1 |
10,852 |
2.0 |
|
- |
- |
|
|
|
Conservation |
99 |
0.0 |
1,138 |
0.2 |
|
- |
- |
|
|
|
Industrial |
4,346 |
1.3 |
19,261 |
3.6 |
|
- |
- |
|
|
|
Public |
447 |
0.1 |
2,347 |
0.4 |
|
- |
- |
|
|
|
Unspecified |
6,216 |
1.9 |
24,898 |
4.7 |
|
- |
- |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Sum |
18,167 |
5.5% |
58,496 |
10.9% |
- |
- |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Total |
332,859 |
100% |
534,625 |
100% |
- |
- |
|
|
|
|
|
|
14 • Justice Research and Policy
Characteristics of Restriction Zones
Each of the five restrictions (attractions, bus stops, daycares, parks, and schools) was characterized in terms of the number of locations and the total land area of the 1,000- and
The most dominant restriction in terms of both the number of locations and the areas of the buffer zones are the bus stops. The 17,613 bus stops result in buf- fer zones that are several times larger than any of the other categories. Daycares, schools and parks are roughly similar in terms of their 1,000- and
When comparing the differences in the 1,000- and
* Table 3
Descriptive Statistics of Restriction Categories
|
Number |
Area of |
Area of |
Restriction Type |
of Locations |
Restricted Zone (Acres)a |
Restricted Zone (Acres)a |
Attractions |
22 |
24,545 |
35,934 |
Bus stops |
17,613 |
200,152 |
339,259 |
Daycares |
498 |
32,656 |
105,542 |
Parks |
237 |
39,350 |
99,908 |
Schools |
254 |
35,713 |
110,355 |
Combined |
18,624 |
245,085 |
379,336 |
a The 1,000- and
Housing Options for Sex Offenders • 15
of the
Properties Within Restricted Zones
The 1,000- and
When considering all restrictions combined, 95.2% of potentially available properties fall within 1,000 feet of one or more restricted areas and 99.7% fall within 2,500 feet. The only zoning categories with somewhat lower percentages are rural/agricultural (87.1% for 1,000 feet and 97.9% for 2,500 feet), rural settle- ment (86.5% and 98.6%) and urban activity (80.5% and 88.6%). The urban ac- tivity zoning category is very small (0.79 % of all potentially available properties) and mostly consist of commercial activity with some
When considering the residency restriction categories individually, bus stops are the most restrictive (93.0% of potential properties fall within 1,000 feet of a bus stop and 99.6% within 2,500), followed by daycares (24.2% and 55.4%), schools (19.7% and 55.8%), parks (15.9% and 38.2%) and attractions (0.2% and 1.0%). These results clearly highlight the dominance of bus stops as a re- strictive factor, and show that daycares and schools result in roughly similar restrictions on the residency choices.
When considering the zoning categories, a very consistent pattern emerges across both buffer distances and across all five restriction categories: the percent- age of properties within a restricted zone is much higher for urban residential properties than for rural ones. For example, when considering the
The impact of increasing the buffer zone distance from 1,000 to 2,500 feet is also illustrated by the results in Table 4. Given the highly restrictive nature of the bus stops, the results for all restrictions combined do not reflect a major difference: 95.2% versus 99.7%. However, differences for individual restriction categories are very substantial.
* Table 4
Characteristics of Occupied Residential Parcels Within Restricted Zones
|
|
|
|
|
|
|
|
Potentially Available Properties |
|
|
|
|
|
|
|
||
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|||
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|||
|
|
|
|
|
|
|
|
|
|
|
|
||||||
|
|
|
|
All Restrictions |
Attractions |
Bus Stops |
Daycares |
Parks |
Schools |
|
|||||||
|
Zoning Category |
Number |
Parcels |
Area |
Parcels |
Area |
Parcels |
Area |
Parcels |
Area |
Parcels |
Area |
Parcels |
Area |
|
||
|
|
||||||||||||||||
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1,000 feet |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
High density |
13,570 |
96.4% |
99.1% |
0.3% |
2.3% |
95.4% |
98.8% |
24.8% |
42.6% |
15.8% 18.4% |
23.2% |
27.1% |
|
|||
|
residential |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Low density |
137,944 |
96.9 |
95.9 |
0.0 |
0.0 |
94.4 |
93.5 |
28.7 |
|
27.0 |
19.6 |
18.5 |
22.5 |
23.4 |
|
|
|
residential |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Medium density |
30,406 |
98.7 |
98.5 |
0.0 |
0.0 |
96.1 |
96.0 |
34.0 |
|
32.5 |
27.2 |
30.9 |
29.9 |
31.5 |
|
|
|
residential |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Mixed use |
943 |
99.5 |
93.0 |
0.0 |
0.0 |
85.0 |
89.3 |
23.9 |
|
17.4 |
58.7 |
20.7 |
36.9 |
17.5 |
|
|
|
Planned development |
67,855 |
92.2 |
90.2 |
0.3 |
7.0 |
91.1 |
85.0 |
14.0 |
|
8.8 |
3.6 |
39.2 |
9.8 |
42.0 |
|
|
|
Professional office |
1,838 |
97.2 |
94.6 |
0.0 |
2.6 |
89.1 |
89.0 |
40.0 |
|
33.6 |
43.9 |
44.4 |
46.7 |
35.6 |
|
|
|
Residential |
579 |
92.6 |
92.7 |
0.9 |
0.0 |
72.0 |
68.9 |
33.5 |
|
29.6 |
65.6 |
63.0 |
0.0 |
0.0 |
|
|
|
Rural/agricultural |
8,845 |
87.1 |
70.7 |
0.3 |
0.9 |
85.4 |
68.1 |
4.0 |
|
2.7 |
5.3 |
21.3 |
7.3 |
3.5 |
|
|
|
Rural settlement |
5,668 |
86.5 |
85.9 |
1.2 |
1.5 |
85.0 |
84.3 |
7.5 |
|
5.7 |
2.0 |
3.7 |
10.6 |
11.5 |
|
|
|
Urban activity |
1,780 |
80.5 |
93.0 |
10.5 |
6.1 |
67.1 |
89.9 |
27.5 |
|
9.4 |
35.7 |
9.2 |
42.9 |
77.7 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Sum |
269,428 |
95.2 |
84.9 |
0.2 |
2.5 |
93.0 |
81.9 |
24.2 |
|
12.8 |
15.9 |
23.7 |
19.7 |
23.8 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Policy and Research Justice • 16
|
|
|
|
|
|
|
|
Potentially Available Properties |
|
|
|
|
|
|
|
|||
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
||||
|
|
|
|
All Restrictions |
Attractions |
Bus |
Stops |
Daycares |
Parks |
|
Schools |
|||||||
|
|
|
|
|
||||||||||||||
|
Zoning Category |
|
Number |
Parcels |
Area |
Parcels |
Area |
Parcels |
Area |
Parcels |
Area |
Parcels |
Area |
Parcels |
Area |
|||
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
2,500 feet |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
High density |
13,570 |
100.0% 100.0% |
0.8% 3.8% |
100.0%100.0% |
60.5% 73.1% |
42.6% 38.9% |
60.0% |
67.8% |
|
||||||||
|
residential |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Low density |
137,944 |
100.0 |
100.0 |
0.3 |
0.3 |
|
100.0 |
100.0 |
62.9 |
58.8 |
46.5 |
43.0 |
63.7 |
59.7 |
|
||
|
residential |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Medium density |
30,406 |
100.0 |
100.0 |
0.2 |
0.2 |
|
100.0 |
100.0 |
71.0 |
70.7 |
55.7 |
60.9 |
73.4 |
73.8 |
|
||
|
residential |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Mixed use |
943 |
100.0 |
100.0 |
1.0 |
0.9 |
|
100.0 |
100.0 |
71.8 |
35.9 |
95.4 |
36.9 |
81.5 |
40.1 |
|
||
|
Planned development |
67,855 |
99.5 |
97.6 |
2.2 |
11.2 |
|
99.4 |
95.1 |
38.7 |
22.8 |
13.5 |
44.7 |
36.4 |
55.2 |
|
||
|
Professional office |
1,838 |
100.0 |
100.0 |
1.8 |
1.5 |
|
100.0 |
100.0 |
82.3 |
69.6 |
86.8 |
81.8 |
89.0 |
77.1 |
|
||
|
Residential |
579 |
100.0 |
100.0 |
0.0 |
0.0 |
|
96.4 |
95.9 |
80.1 |
76.3 |
95.5 |
92.9 |
7.9 |
11.2 |
|
||
|
Rural/agricultural |
8,845 |
97.9 |
79.0 |
0.5 |
0.9 |
|
97.4 |
77.0 |
17.2 |
6.3 |
19.1 |
25.8 |
19.4 |
7.0 |
|
||
|
Rural settlement |
5,668 |
98.6 |
96.6 |
2.3 |
2.8 |
|
98.5 |
96.5 |
20.0 |
16.9 |
13.4 |
19.1 |
36.2 |
29.3 |
|
||
|
Urban activity |
1,780 |
88.6 |
97.8 |
26.3 |
9.3 |
|
88.3 |
97.6 |
59.8 |
20.9 |
68.3 |
17.3 |
69.0 |
86.6 |
|
||
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Sum |
269,428 |
99.7 |
91.4 |
1.0 |
3.9 |
|
99.6 |
90.1 |
55.4 |
28.1 |
38.2 |
35.2 |
55.8 |
40.5 |
|
||
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
• Offenders Sex for Options Housing
17
18 • Justice Research and Policy
The percentages represented in Table 4 do not necessarily convey housing choices very accurately from a market perspective, as they do not reflect the rela- tive availability of each zoning category. Therefore, it is meaningful to take the total number of parcels of each zoning category into consideration. Consider a specific example: the most dominant zoning category in Orange County is low- density residential, with 137,944 occupied properties, or 51.2% of all 269,428 occupied residential and combined use properties. Of these 137,944 potentially available properties in this zoning category, 22.5% fall within a
Overall, the results of the analysis of residency restrictions in Table 4 strongly suggest that the housing opportunities outside the 1,000- and
* Conclusions
Results from the current case study of Orange County, Florida, provide strong evidence that housing options for sex offenders within urban residential areas are severely limited. Most housing options for convicted sex offenders are limited to low density rural areas. Moreover, the various restrictive categories examined (i.e., attractions, bus stops, daycare facilities, schools, and parks) vary greatly in terms of how they affect housing options.
Public school bus stops are by far the most restrictive category, followed by daycares, schools, parks, and attractions. The dominance of bus stops is to be expected, given their total number and dispersed nature. Bus stops are such a dominant restriction that very few additional properties are restricted as a result of incorporating the other restrictive categories in the analyses. The dominance of bus stops as a restrictive factor has not previously received a lot of atten- tion, in part because it has not been as widely used a restriction as schools and daycares. Instead, much of the debate regarding residency restrictions has been around the size of the buffer zone.
Increasing the buffer zone from 1,000 to 2,500 feet has a very minor impact in terms of housing options since so few properties (~4% of potentially available properties) fall outside the
* Figure 4
Occupied Residential Parcels in Orange County, Florida
Surface Water Features
Parcels Outside
Parcels Outside
All Occupied Residential Parcels
• Offenders Sex for Options Housing
19
20 • Justice Research and Policy
when only schools and daycares are considered, the
Restriction categories vary greatly in their number and spatial distribu- tion, resulting in very different restriction zones. This study also shows that a
To reiterate, limiting housing options for convicted sex offenders may lead to unintended consequences (Levenson & Cotter, 2005b). Isolation, financial and emotional hardships, and a decrease in stability have been linked to recidi- vism (Hanson & Harris, 1998). Limiting housing options for sex offenders to a few locations in
The current study does not address the efficacy of residency restriction laws for crime prevention. As a result, the value of boundary restrictions to prevent new crimes by known offenders remains unknown. Regardless, the process of leaving prison and returning to society is complex and challenging.9 In 2001, the number of prisoners returning to the community was estimated to be about 1,600 on average each day (Bureau of Justice Statistics, 2006). If sex offender
9 For more information on prisoner reentry, see Travis, Solomon, & Waul (2001).
Housing Options for Sex Offenders • 21
residency restriction laws are so restrictive that successful reentry is not likely to be achieved, all components of the criminal justice system (e.g., enforcement, prosecution, and corrections) will feel the burden. Future research should there- fore examine more closely the effect of sex offender residency restrictions on subsequent recidivism.
Finally, this study demonstrates the utility of GIS in providing a detailed description of the housing options for sexual offenders under various residency restriction scenarios. GIS can also be used to describe several other factors that may play a role in recidivism, such as the proximity of sexual offenders to other measures of socioeconomic isolation. The
Findings from this study suggest that housing options for sexual offenders in a typical metropolitan area are very limited even under some of the least re- strictive scenarios. At present, 16 states have adopted residency restrictions and more are likely to follow. While our knowledge of mobility and displacement of sexual offenders is limited, the logical result of increasing residency restrictions is the displacement of sexual offenders to areas with few or no restrictions. More widespread adoption and enforcement of residency restrictions is also likely to result in larger numbers of sexual offenders being homeless and transient. The broader question as to whether these trends are desirable has not received suf- ficient attention, making it imperative that the unintended consequences of residency restrictions are
22 • Justice Research and Policy
* References
Alexander, M.A. (1999). Sexual offender treatment efficacy revisited. Sexual Abuse: A Journal of Research and Treatment, 11(2),
Association for the Treatment of Sexual Abusers. (2005). Facts about adult sex offenders.Beaverton,Oregon:Author.Retrievedfromhttp://www.atsa.com/ pdfs/ppOffenderFacts.pdf.
Barbaree, H. E., Seto, M. T., & Maric, A. (1996). Effective sex offender treat- ment: The Warkworth Sexual Behavior Clinic. Forum on Corrections Re- search, 8(3),
Blair, M. (2004). Wisconsin’s sex offender registration and notification laws: Has the Wisconsin Legislature left the criminals and constitution behind?
Marquette Law Review, 87(5),
Bureau of Justice Statistics. (2006). Reentry trends in the United States. Wash- ington, DC: U.S. Department of Justice, Office of Justice Programs. Re- trieved from http://www.ojp.usdoj.gov/bjs/reentry/reentry.htm.
Colorado Department of Public Safety. (2004). Report on safety issues raised by living arrangements for and location of sex offenders in the commu- nity. Denver, CO: Sex Offender Management Board. Retrieved from http: //dcj.state.co.us/odvsom/Sex_Offender/SO_Pdfs/FullSLAFinal01.pdf.
Edwards,W., & Hensley, C. (2001). Contextualizing sex offender management legislation and policy: Evaluating the problem of latent consequences in community notification laws. International Journal of Offender Therapy and Comparative Criminology, 45(1),
Elbogen, E. B., Patry, M., & Scalora, M. J. (2003). The impact of community notification laws on sex offender treatment attitudes. International Journal of Law and Psychiatry, 26,
ESRI (2005). ArcGIS Desktop Release 9.1, ESRI, Redlands, CA.
Hanson, R. K., & Harris, A. J. R. (1998). Dynamicpredictorsofsexualrecidivism. Ottawa, Canada: Department of the Solicitor General of Canada. Retrieved from
Iowa County Attorneys Association. (2006). Statement on sex offender residency restrictions in Iowa. Retrieved from
Levenson, J. S., & Cotter, L. (2005a). The impact of Megan’s Law on sex of- fender reintegration. Journal of Contemporary Criminal Justice, 21(1),
Levenson, J. S., & Cotter, L. P. (2005b). The impact of sex offender residence restrictions: 1,000 feet from danger or one step from absurd? Interna- tional Journal of Offender Therapy and Comparative Criminology, 49(2),
Housing Options for Sex Offenders • 23
Marques, J., Day, D., Nelson, C., & West, M. (1994). Effects of
Marshall, W., & Barbaree, H. (1988). The
Marshall, W., Eccles, A., & Barbaree, H. (1991). The treatment of exhibition- ists: A focus on sexual deviance versus cognitive and relationship features.
Behavior Research and Therapy, 29(2),
Minnesota Department of Corrections. (2003). Level three sex offenders resi- dential placement issues. St. Paul. MN. Retrieved from http://www.corr. state.mn.us/publications/legislativereports/pdf/2004/Lvl%203%20SEX%
Mustaine, E. E., Tewksbury, R, & Stengel, K. M. (2006a). Residential location and mobility of registered sex offenders. American Journal of Criminal Jus- tice 30(2),
Mustaine, E. E., Tewksbury,R , & Stengel, K. M. (2006b). Social disorganiza- tion and residential locations of registered sex offenders: Is this a collateral consequence? Deviant Behavior 27(3),
Rice, M., Quinsey, V., & Harris, G. (1991). Sexual recidivism among child mo- lesters released from a maximum security psychiatric institution. Journal of Counseling and Clinical Psychology, 29(3),
Robinson, D. (1996). Factors influencing the effectiveness of cognitive skills training. Forum on Corrections Research, 8(3),
Schram, D., & Milloy, C. D. (1995). Community notification: A study of of- fender characteristics and recidivism. Olympia, WA: Washington Institute for Public Policy.
Tewksbury, R. (2004). Experiences and attitudes of registered female sex of- fenders. Federal Probation, 68(3),
Tewksbury, R. (2005). Collateral consequences of sex offender registration.
Journal of Contemporary Criminal Justice, 21(1),
Tewksbury, R., & Lees, M. (2006). Consequences of sex offender registration: Collateral consequences and community experiences. Sociological Spec- trum, 26(3),
Tewksbury, R., & Mustaine, E. E. (2006). Where to find sex offenders: An ex- amination of residential locations and neighborhood conditions. Criminal Justice Studies, 19(1),
Travis, J., Solomon, A. L., & Waul, M. (2001). From prison to home: The dimensions and consequences of prisoner reentry. Washington, DC: The Urban Institute. Retrieved from http://www.urban.org/UploadedPDF/from_ prison_to_home.pdf.
24 • Justice Research and Policy
Walker, J. T., Golden, J.W., & VanHouten, A. C. (2001). The geographic link between sex offenders and potential victims: A routine activities approach.
Justice Research and Policy, 3(2),
Welchans, S. (2005). Megan’s Law: Evaluations of sexual offender registries.
Criminal Justice Policy Review, 16(2),
Wright, R. G. (2003). Sex offender registration and notification: Public at- tention, political emphasis, and fear. Criminology & Public Policy, 3(1),
Younglove, J. A., & Vitello, C. J. (2003). Community notification provisions of “Megan’s Law” from a therapeutic jurisprudence perspective: A case study.
American Journal of Forensic Psychology, 21(1),
Zevitz, R. G., Crim, D., & Farkas, M. A. (2000). Sex offender community noti- fication: Examining the importance of neighborhood meetings. Behavioral Sciences and the Law, 18,
Zevitz, R. G., & Farkas, M. A. (2000). Sex offender community notification: Managing high risk criminals or exacting further vengeance? Behavioral Sciences and the Law, 18,
* Legislation and Cases
Adam Walsh Child Protection and Safety Act. Legislative Notice. U.S. Senate Republican Policy Committee (2006).
Doe. v. Miller, 405 F.3d 700, 710 (8th Cir. 2005).
Florida House Bill 91 CS. Residence of sexual offenders and predators. (2006). Florida Statute §947.1405(7a)(2). Conditional release program. (2005). Florida Statute §948.30(1b). Additional terms and conditions of probation or
community control for certain sex offenses. (2005).
Iowa Code §692A.2A. Residency
Jacob Wetterling Crimes Against Children and Sexually Violent Offender Reg- istration Act, 42 U.S.C. §14071 (1994).
Megan’s Law, Pub. L. No.
Township of Manalapan, NJ: Chapter
Washington Senate Bill 6325. Sex offenders – Residency requirements. (2005).