Abstract
Sex offender management is one of the highest-profile issues in public safety today. Although states have enacted community notification laws as a means to protect communities from sexual offending, limited research has been conducted to examine the impact of these laws on public safety. As such, this study used a quasi-experimental design to examine the relationship, if any, between community notification legislation and sex offender rearrest. Sex offenders who were subject to community notification (n = 10,592, 61.7%) were compared to sex offenders who were not subject to community notification requirements (n = 6,573, 38.3%). Results indicate that sex offenders subject to community notification were rearrested twice as quickly (for a sexual offense) and 47% more quickly (for a nonsexual offense) than those not subject to community notification. The findings yield implications for sex offender interventions and public policies and suggest that notification may not be an effective strategy for significantly reducing sexual offenses.
The return of convicted sex offenders to local communities has received a great deal of attention in recent years, both in the public forum and within the criminal justice community. National statistics indicate that 272,350 rapes and sexual assaults occurred in 2006 (Rand & Catalano, 2007). In addition, an estimated one in six women will be the victim of an attempted or completed sexual assault in their lifetime (Tjaden & Thoennes, 1998). As a result of these sexual crimes committed against vulnerable populations such as women and youth, policy makers in recent years have enacted legislation with the goal of increasing public safety by reducing the likelihood that convicted sex offenders will reoffend (see Edwards & Hensley, 2001; Levenson & Cotter, 2005a). Community notification laws represent one of these techniques. Currently, all 50 states and the District of Columbia have laws mandating that the community be notified of certain convicted sex offenders residing in the area (Zevitz & Farkas, 2000).
Despite the widespread use of community notification, a paucity of research has been conducted that empirically evaluates its impact on not only the community and its safety, but also the rearrest of convicted sex offenders. Therefore, the current study sought to empirically assess the relationship, if any, between community notification laws and rates of sexual offender rearrest for a sample of offenders in New York State. Specifically, rearrests for sexual and nonsexual offenses were compared for a group of sex offenders who were subject to community notification requirements and for a group who, because of a federal injunction, were not subject to the same notification requirements.
Registration and Community Notification Laws
Society’s perception that sexual offenses are particularly heinous crimes has prompted policy makers to develop methods to prevent future sexual victimizations and reduce the reoffending of convicted sex offenders. The two most influential federal legislative attempts to date are the development of sex offender registries under the Jacob Wetterling Crimes Against Children and Sexually Violent Offender Act (1994), and the addition of community notification, which has become known as Megan’s Law (1996). No standardization of these systems was required, and, therefore, states vary in how registration and community notification are employed. Because this study focused exclusively on the impact that New York State’s community notification legislation had on the rearrest of convicted sex offenders, only New York State’s notification procedures are presented. Because New York’s notification system is comparable to that of other states, it offers a prime example of such legislation and its impact on the rearrest of convicted (registered) sex offenders.
New York State’s Sex Offender Registration Act
In compliance with federal regulations, New York established the Sex Offender Registration Act (SORA) in 1995, which became effective January 21, 1996. The law requires the public release of information and the notification of communities about the presence of individuals who, because of their history of committing sexual crimes, may present a danger to public safety (Doe v. Pataki, 1996). All sex offenders convicted, under probation or parole supervision, or discharged, paroled, or released on or after January 21, 1996, are mandated to register under this Act (Division of Criminal Justice Services, 2004a, 2004b).
When sex offenders are registered in New York, they are assigned a risk level (Level 1 to Level 3) based on the court’s assessment regarding (a) an offender’s likelihood to repeat the same or similar registerable offense and (b) the potential danger to the community. Level 1 represents a low risk of repeat offense; Level 2 indicates a moderate risk of repeat offense; and Level 3 represents a high risk of repeat offense and a threat to public safety. The level of risk determines not only the length of registration but also the extent of community notification.
Federal Injunction
In March 1996, shortly after the enactment of SORA, the Legal Aid Society filed a federal lawsuit on behalf of several released sex offenders challenging the legality of New York State’s community notification law on the grounds that (a) the notification provisions of SORA violated the ex post facto clause (i.e., it punished offenders after the fact) and (b) the minimal due process in regard to risk level proceedings had not been granted. The court ultimately found in favor of the Legal Aid Society’s challenge, and an injunction was established prohibiting community notification for all sex offenders who committed their crimes before the enactment of SORA, on January 21, 1996, and who were under probation or parole supervision or were still incarcerated for their offenses. 1 Therefore, the injunction created two distinct groups: (a) sex offenders who committed their crimes prior to the enactment of the law and, therefore, were not subject to community notification requirements; and (b) sex offenders who committed their crimes on or after the enactment of the law and, therefore, were subject to notification requirements. By comparing the rearrest rates of these two groups, the relationship between community notification laws and sex offender rearrest can be estimated.
Evaluations of Community Notification Laws
The primary objective of community notification laws is to increase public safety by reducing incidents of future sexual victimization (Levenson & Cotter, 2005a). Therefore, these laws provide the public access to information that may help them to better protect themselves, their families, and their communities from sex offenders. Several outcome studies have attempted to evaluate the effects of community notification laws on sex offender recidivism. These studies have (a) examined convicted sexual psychopaths to determine the likelihood that community notification would prevent future sexual offenses (Petrosino & Petrosino, 1999), (b) compared registered sex offenders subject to community notification requirements to convicted sex offenders who would have been subject to registration and notification requirements had the laws been in effect at the time of their convictions (Adkins, Huff, Stageberg, Prell, & Mussel, 2000; Schram & Milloy, 1995), (c) compared sex offenders subjected to extensive notification to those subjected to limited notification (Zevitz, 2006), and (d) used time-series analysis to determine the general deterrent effect of registration and community notification laws (Sandler, Freeman, & Socia, 2008; Walker, Maddan, Vásquez, VanHouten, & Ervin-McCarthy, 2005). Despite the differences in methodologies, these previous studies have all found minimal support for the effectiveness of community notification laws to reduce sex offender rearrest and reconviction rates.
Two recent studies in Washington State (Barnoski, 2005) and Minnesota (Duwe & Donnay, 2008) did find that community notification laws significantly reduced rates of sexual recidivism. The reductions in offending noted by Barnoski (2005), however, may have simply been due to historical crime trends (and unrelated to registration and community notification laws) because the analyses examined rates of recidivism at three points in time through three logistic regressions. Although these studies provided empirical examinations of community notification’s impact on rearrest, the results are limited by small sample sizes (usually containing only those offenders released from prison), short follow-up periods, and limited control variables.
Method
To examine the relationship, if any, between community notification and the rearrest of convicted sex offenders, a sample of sex offenders in New York State was used, including those in the community under criminal justice supervision (i.e., probation and parole) and those not under supervision. As of June 4, 2004 (the date that the injunction was settled), there were 18,602 sex offenders registered in New York State. It has been well established, however, that female sex offenders are different from male sex offenders (see Center for Sex Offender Management, 2007). As such, all female sex offenders, as well as offenders whose gender was unknown, were dropped from the study (n = 343, 1.8%). Those offenders who were deceased (1.6%), deported (4.3%), or supervised by another state (n = 1) were also excluded from the sample. Therefore, the final sample was limited to male registered sex offenders in the community who were under criminal justice supervision or not (n = 17,165, 92.2%). Although this population included all sex offenders affected by legislative mandates (i.e., registration and community notification), it did not encompass those individuals who were charged with a sexual offense and (a) were not convicted or (b) pled to a lesser offense that did not require registration on the state sex offender registry.
The data were retrieved from two sources. First, information was obtained from the New York State sex offender registry, which contains information for all registered sex offenders in the state, including offender demographics, offense characteristics, and victim information. Second, criminal history information was extracted for all registered sex offenders from the New York State computerized criminal history database, which contains official information for all arrests that resulted in a fingerprint record. Specifically, criminal history files contain information regarding characteristics related to arrest, conviction, disposition, and sentencing events. Because the criminal history information was limited to New York State, crimes that occurred in other states were not included in this study.
Almost two thirds of the sex offenders were White (63.6%), whereas 30.6% were Black and 1.4% were categorized as Indian or Asian. 2 The average registered sex offender was 32.88 years old (SD = 11.77) at the time that he was arrested for his registerable sexual offense, with a range from 14 to 91 years of age. Most sex offenders were registered for sexual intercourse (43.4%) or sexual contact (30.2%), with the remaining offenders having been registered for committing deviant sexual intercourse (16.6%), promoting the sexual performance of a child (or possessing material thereof) (1.8%), disseminating indecent materials to a minor (0.2%), kidnapping or unlawful imprisonment (0.4%), or patronizing/promoting prostitution (0.1%). 3 Table 1 displays offenders’ characteristics by community notification status, and Table 2 displays the correlation matrix for the predictor variables.
Offender Characteristics by Community Notification Status
Sexual offenders not subject to community notification requirements.
Correlation Matrix for the Predictor Variables
p < .001 (two-tailed).
Offenders were followed starting from the date of their first release into the community after the instant offense. The follow-up period ceased before the end of the study if the offender was arrested for a new criminal offense before June 4, 2004. This date was selected as the last day of the follow-up period because it is the settlement date of the injunction that prohibited notification for those offenders who committed their crimes before the enactment of SORA (see Doe v. Pataki Settlement, 2004).
Dependent Variables
Research has shown that sex offenders are likely to engage in sexual and nonsexual offenses (Langan, Schmitt, & Durose, 2003). Therefore, two measures of recidivism were used in the present study: rearrest for a registerable sexual offense and rearrest for any nonsexual offense. For the purposes of the current study, a registerable sexual offense was defined as any sexual crime that resulted in mandated registration with the New York State sex offender registry, as stipulated in Correction Law Article 6c, including but not limited to rape, incest, sodomy, sexual misconduct, sexual abuse, and promoting sexual performance by a child. Each rearrest measure was a dichotomous indication of whether or not the offender was rearrested for the specific offense.
Community Notification Status
The federal injunction in New York State created a unique opportunity to study the relationship between community notification and rearrest by creating two groups: (a) those sex offenders who committed their crimes prior to the enactment of SORA and, therefore, were not subject to community notification requirements (henceforth, the comparison group; n = 6,573, 38.3%) and (b) those who committed their crimes on or after the enactment of SORA and, therefore, were subject to notification requirements (henceforth, the notification group; n = 10,592, 61.7%). Although the injunction distinguished offenders based on the time in which their offenses were committed, all sex offenders in the sample were in the community during the same period. Moreover, during this period, offenders in both groups (notification and comparison) were mandated to register with the state sex offender registry. As such, any changes in community factors or police practices that occurred between 1996 and 2004 or any effects that occurred by the registration process would affect both groups.
Predictor Variables
The predictor (independent) variables fell into three categories: offender demographics, criminal history, and victim information. 4 Each variable is delineated in the following sections.
Offender Demographics
Race
Because the majority of sex offenders in the current sample were White, offender race was dummy-coded as White (1) and non-White (0).
Offenders’ age
Marshall and Barbaree (1988) found offenders’ age to be significantly related to their offending behavior, whereas Abel, Becker, Cunningham-Rathner, Mittelman, and Rouleau (1988) noted that early onset of sexual offending increases the likelihood for future sexual offending (also see Hanson & Bussière, 1998). Therefore, offenders’ age at the time of the arrest for the registerable offense was included in the model.
Supervision type
Given that the sample included probationers, parolees, and those not under supervision, a variable indicating the supervision type (0 = probation, 1 = parole, 2 = no supervision) was included to control for any differences in supervision that may have affected the likelihood of detection and/or reoffense.
Risk level
Offenders’ registry risk level was a categorical variable: Level 1 (low risk), Level 2 (moderate risk), and Level 3 (high risk). Decisions regarding risk levels were based on the facts of each case, including but not limited to the following: the age of the victim (or victims), the number of victims, the offender’s relationship to the victim (or victims), the duration of the offense conduct with the victim (or victims), the use of weapons or force during commission of the crime, and the offender’s age at his first sexual misconduct (Division of Criminal Justice Services, 2004c). This variable controlled for the varying levels of supervision that may have resulted from an offender’s risk level, which should control for any increased observation/supervision of some sex offenders. Risk levels were also included in the model because the extent of community notification was based on the offender’s level of risk. Although risk level comprised other variables in the model, auxiliary regression equations indicated that only 27% of the variation in risk level was shared with the other model variables.
County of residence
The model included a categorical variable representing the offender’s county of residence (and supervision) to control for potential regional impacts across counties, such as differences in community notification strategies. This variable also controlled for disparities in supervision levels that may have affected the probability of detection (see Kruttschnitt, Uggen, & Shelton, 2000). The county variable was coded into rural (fewer than 50,000 people), midsize (between 50,000 and 499,999), and urban (500,000 or more).
Criminal History
Violent felony offense arrests
Sex offenders who physically harm their victims and have a past history of violent behavior are at increased risk to reoffend (Berliner, Schram, Miller, & Milloy, 1995; Dempster & Hart, 2002; Hanson & Bussière, 1996, 1998). Therefore, the analysis included a continuous variable for each offender’s number of prior violent felony offense arrests.
Sexual offense arrests
Numerous studies have indicated that the more sexual offense arrests offenders have in their criminal histories, the more likely they are to recidivate (Hanson & Morton-Bourgon, 2005; Harris & Hanson, 2004). Given these salient findings, the number of prior sexual offense arrests was included in the model.
Drug offense arrests
According to the sex offender recidivism literature, adult drug abuse has been identified as being significantly related to both general and sexual offending (Hanson & Bussière, 1998; Motiuk & Brown, 1996). As such, the number of prior drug offense arrests in offenders’ criminal histories was entered in the model.
Variety offense arrests
Hanson and Bussière (1996) noted that sex offenders who have criminal histories containing a variety of different sexual crimes were at increased risk to reoffend compared to those whose criminal histories were limited to one type of crime. Given this research, a measure was included in the analysis that indicated the number of different types of crimes that an offender had engaged in during his criminal career.
Incarceration terms
Berliner and colleagues (1995) found that sex offenders who reoffended were more likely to have histories of violent behavior and previous adult convictions. Thus, a measure of the number of prior incarceration terms (jail and prison) was included in the analysis.
Supervision violations
Dempster and Hart (2002) found that male sex offenders with unsuccessful past parole and probation supervisions were significantly more likely than those without to reoffend (also see Hanson & Morton-Bourgon, 2005). For that reason, the number of past supervision violations (parole and probation) was entered into the model.
Victim Information
Victim gender
Hanson and Bussière (1998) found sex offenders’ choice of victim gender to be related to their overall offending, with those sex offenders who selected male victims being significantly more likely to recidivate than those who selected male and female victims. Furthermore, both these groups were significantly more likely to recidivate than were those who selected only female victims (also see Hanson, Steffy, & Gauthier, 1993). Given these findings, three gender variables were included in the analysis: male victim (1 = male, 0 = other), female victim (1 = female, 0 = other), and mixed victim gender (1= both male and female victims, 0 = other).
Victim age
A categorical variable representing the age of the victim was included, given the research suggesting that the age of victims favored by a sex offender is strongly related to the offender’s criminality, with offenders who select younger victims being more likely to reoffend that those who select older victims (Hanson & Bussière, 1998). This variable was coded to correspond to the conventional categorization found in the extant research: victim under 12 years old, victim between the ages of 13 and 17 years old, and victim 18 years old and older.
Number of victims
In addition to victim gender and age, number of victims in the instant offense was included, given that it has been found to be related to offender recidivism (Barbaree & Marshall, 1988; Motiuk & Brown, 1996). Approximately 85.6% of the offenders had only one victim in the instant offense arrest, with the number of victims ranging from 1 to 11.
Analysis
Given that the follow-up period varied considerably among the sample (i.e., sex offenders were registered at different times throughout the follow-up period), Cox regressions were employed because they not only indicate whether an offender was rearrested, but also take into account the length of time that an offender was at risk to reoffend. Time spent incarcerated during the follow-up period (e.g., for parole technical violations) was accounted for by subtracting this time from the overall at-risk period. 5 Time spent in the community was measured in days from the day of the first release after the instant offense until the date of the first rearrest for a sexual offense (for that model) and a nonsexual offense (for that model) or until June 4, 2004 (the date the injunction was settled) for those who were not rearrested. The majority of those rearrested for an offense (nonsexual or sexual) were rearrested by the end of the 8th year in the community (with a range from 0 to 8,033 days; see Table 3). Therefore, all subsequent analyses were ceased at the end of a 3,000-day follow-up period (i.e., 8.2 years).
Rates of Nonsexual and Sexual Rearrest
Note: The 1-, 3-, and 5-year rates of rearrest were calculated using only those offenders who had at least 1, 3, or 5 years in the community postrelease. Thus, if an offender was first arrested 1.5 years before the censor date (June 4, 2004) and did not recidivate, then he would be counted in the denominator for the 1-year rearrest rate but not the 3- or 5-year rate.
Results
Of the 17,165 sex offenders in the sample, 7,995 (46.6%) were rearrested for any offense during the follow-up period. Specifically, 2,063 offenders (12.0%) in the sample were rearrested for a violent felony offense, and 4,387 (25.6%) were rearrested for a felony offense. 6 Regarding specific offenses, most were arrested for assault (15.3%), controlled substances (10.3%), property offenses (7.7%), or burglary (6.0%). As the frequencies indicate, approximately half the sex offenders in the sample recidivated during the follow-up period, however, only a small percentage of those arrests were for sexual offenses (7.0%, n = 1,196).
Nonsexual Offense Rearrest
All variables were entered into the model in one step, and the overall model yielded significant results, χ2(21, N = 15,646) = 4,051.29, p < .01. Table 4 summarizes the Cox regression results. After controlling for the other risk factors, as well as time at risk, significant differences in the rate of rearrest for a nonsexual offense emerged between the notification and comparison groups. In fact, sex offenders who were subject to community notification were rearrested for a nonsexual offense 47% faster than those not subject to community notification.
Cox Regression for the Two Outcome Measures
Coded notification (1), comparison–no notification (0).
Compared to no supervision.
Compared to urban.
Compared to Level 3.
Coded White (1), non-White (0).
Compared to child and adult victims.
Compared to mixed.
p < .05.
Sex offenders who had no criminal justice supervision, but were subject to community notification requirements, were arrested for a subsequent nonsexual offense more quickly than probationers and parolees, regardless of their notification status. Furthermore, sex offenders who were under probation or parole supervision and were subject to notification requirements were rearrested for a nonsexual offense more quickly than their counterparts who were not subject to notification requirements. Although this finding does not indicate that community notification causes recidivism, it does lend support to the conclusion that notification status, as compared to supervision type, has a greater impact on being arrested for a subsequent nonsexual offense.
Risk factors for nonsexual offense rearrests
Nine variables emerged as significant predictors of nonsexual offense rearrest: (a) number of prior incarceration terms, (b) number of prior supervision violations, (c) number of prior violent felony offense arrests, (d) number of prior drug offense arrests, (e) number of prior different types of criminal offense arrests, (f) offender race, (g) offender age, (h) county of residence, and (i) supervision type. Specifically, each prior incarceration term increased the rate of nonsexual offense rearrest by 7.6%; each prior supervision violation increased the rate of rearrest by 2.9%; and each additional type of prior criminal offense arrest increased the rate of rearrest by 24.1%. Moreover, the rate of rearrest for a nonsexual offense decreased by 4.9% for each prior violent felony offense arrest and by 4.5% for each prior drug offense arrest. White sex offenders were rearrested 15.2% slower than non-White offenders, and each 1-year increase in age resulted in a small decrease in the rate of rearrest for a nonsexual offense (3.8%). Finally, county of residence and supervision type had a significant effect on nonsexual offense rearrests. Sex offenders residing in rural and midsize counties were rearrested at a slightly faster rate than that of those residing in urban counties. Sex offenders under parole or probation supervision, however, tended to be rearrested for a nonsexual offense less quickly than those under no criminal justice supervision (31.5% and 19.6%, respectively).
Sexual Offense Rearrest
An additional Cox regression was estimated to examine the relationship between community notification and sexual offense rearrest. All variables were entered into the model in one step, which yielded a significant overall model, χ2(21, N = 14,903) = 650.05, p < .01. Similar to the results for nonsexual offense rearrest, results of this analysis suggest that sex offenders who were subject to community notification were rearrested twice as quickly as sex offenders in the comparison group. Sex offenders who had no criminal justice supervision, but were subject to community notification, were rearrested for a sexual offense more quickly than all other sex offenders. Furthermore, probationers and parolees in the notification group were rearrested more quickly than those who were not subject to community notification, regardless of the type of supervision. This result suggests that notification status, not the supervision type, has the greatest impact on the time to arrest for a subsequent sexual offense. 7
Risk factors for sexual offense rearrests
As can be seen in Table 4, several predictor variables were significantly associated with the rate of sexual offense rearrests. For example, numerous criminal history variables increased the rate of rearrest for a sexual offense, including each prior incarceration term served (by 3.7%), each prior sexual offense arrest (by 29.0%), and each additional type of crime in an offender’s history (by 25.2%). However, three criminal history factors decreased the rate of arrest for a subsequent sexual offense, including prior supervision violation (by 12.1%), prior drug offense arrest (by 6%), and prior violent felony offense (by 7.2%). Risk levels, which affect the extent of notification, also yielded significant results in terms of the rate of rearrest for a sexual offense. Level 3 sex offenders (high risk) were rearrested more quickly than sex offenders classified as Level 1 (low risk) and Level 2 (moderate risk). In addition, sex offenders residing in rural counties were rearrested for a sexual offense twice as quickly as those in urban counties, whereas those residing in midsize counties were rearrested 33% more quickly than those in urban counties. Finally, being younger, under probation supervision, and, as noted earlier, not subject to community notification all reduced the rate of rearrest for a sexual offense. Victim age, victim gender, number of victims in the instant offense, and offender race did not significantly influence the rate of rearrest for a sexual offense.
Discussion
The present study used a sample of 17,165 convicted (registered) sex offenders in New York State to evaluate the impact of community notification, as stipulated in New York State’s SORA. Specifically, the study proposed the general question of whether there was a relationship between community notification and sex offenders’ nonsexual and sexual rearrests. Results of the study indicate that those sex offenders who are subject to community notification requirements are rearrested twice as quickly for subsequent sexual offenses and 47% more quickly for nonsexual offenses than sex offenders who are not subject to the same notification requirements. These results remain even after controlling for several risk factors, as well as time at risk in the community.
These results yield three possible interpretations. First, community notification may result in an increase in the identification and monitoring of sex offenders who are subject to community notification. In other words, as a result of community notification, law enforcement and community members may be monitoring sex offenders more closely; therefore, crimes committed by this group of offenders are detected more quickly than crimes committed by sex offenders in the comparison group. Although numerous variables were included in the model to control for the increased supervision and observation of sex offenders in the notification group, no direct measures were included and thus, it remains a possible explanation for the results.
Second, it is possible that community notification laws create a false sense of security among community members, thereby reducing guardianship and increasing opportunities for motivated sex offenders to access suitable victims. Empirical research has suggested that sex offenders do not always commit crimes within their areas of residence and, thus, the areas in which notification occurs (Levenson & Cotter, 2005b; Petrosino & Petrosino, 1999). Indeed, studies in Colorado and Minnesota found that sex offenders are unlikely to offend close to their homes and within the area that notification occurs (Colorado Department of Public Safety, 2004; Minnesota Department of Corrections, 2003); rather, sex offenders may travel, on average, 3 to 5 miles (about 5 to 8 kilometers) to gain access to victims (Warren et al., 1998; also see Beauregard, Proulx, & Rossmo, 2005). With the ease of transportation and mobility, motivated offenders can simply travel to neighboring communities (i.e., outside the area in which notification occurs) to find suitable victims (Prentky, 1996). Because communities are under the perception that they will be notified regarding the presence of sex offenders, they may be less guarded and conclude that their communities are safe. This perception of safety creates an atmosphere where motivated offenders can easily access potential victims.
A third explanation for the findings is that the public disclosure resulting from community notification negatively impacts an offender’s social integration, which leads to sex offenders who are subject to notification committing crimes more quickly than sex offenders who are not subject to notification requirements. In fact, a great deal of research indicates that sex offenders are suffering further punishment as a result of community notification, such as being discriminated against in terms of employment and housing opportunities (Tewksbury, 2005; Zevitz & Farkas, 2000). Restrictions placed on housing can result in sex offenders who move from one community to another, making the reintegration process difficult and affecting the tracking and monitoring of these offenders (Levenson & Cotter, 2005b). Overall, the more difficulty that released sex offenders face in creating a prosocial life, the more likely they may return to a life of crime.
In support of these conclusions, offenders have noted that it is difficult to “start over” after incarceration because they have lost their anonymity. Notification laws assume that by informing the public of the whereabouts of convicted sex offenders, citizens will act responsibly to protect themselves and their families. Many states, however, have reported incidents in which released sex offenders were harassed by community members after the notification process (Matson & Lieb, 1996, 1997). According to Bedarf (1995, p. 909), the harassment that results from notification alerts could cause sex offenders to move numerous times, to create an alias, or to fail to comply with registration requirements. When these situations occur, the positive benefits that can be produced by community notification are mislaid and public safety is further jeopardized. Furthermore, the harassment that results from community notification can cause sex offenders to revert to a life of crime by aggravating triggers to reoffense, such as loneliness, stress, and social isolation. These explanations provide a theoretical context to explain why, in the present study, sex offenders who were subject to community notification requirements were rearrested more quickly than those not subject to the same notification requirements.
Community Notification, Rearrest, and Risk Factors
Several variables emerged as predictors of sexual and nonsexual offense rearrest in addition to the finding that sex offenders who are subject to community notification are rearrested more quickly than sex offenders not subject to the same notification requirements. Consistent with prior research, sex offenders who are young, who have a history of committing sexual offenses, who have a criminal history that contains numerous types of offenses, and who have served a number of incarceration terms are at increased risk to be rearrested for a sexual offense. Interestingly, the number of prior supervision violations reduce the rate in which offenders are arrested for subsequent sexual offenses. Although the negative relationship is surprising, it is possible that those sex offenders who violated the terms of their probation and/or parole were more deterred from future violations than offenders who had never served a supervision term or those who successfully completed supervision.
In addition, Level 3 sex offenders were rearrested for a sexual offense more quickly than offenders classified as Level 2 and Level 1. This finding suggests that sex offenders receiving the highest extent of community notification are rearrested more quickly than those subject to a lesser extent. As noted earlier, this finding could be attributed to an increase in the monitoring and/or supervision of Level 3 sex offenders. However, given that all registered sex offenders in New York State are required to adhere to the similar supervision conditions, the findings are more likely due to the social consequences experienced by those offenders receiving the highest extent of community notification.
Moreover, those who live in rural or midsize areas are at increased risk to be rearrested for a nonsexual and sexual offense. This finding is supported by prior research, which found that sex offenders residing in nonmetropolitan areas experience more social consequences as a result of registration and community notification (e.g., job loss, denial of promotion, rude treatment) than do their counterparts (Tewksbury, 2005). Experiencing these consequences from community notification may explain the heightened rearrest rates that emerged in this study. It cannot be ruled out, however, that the anonymity associated with living in urban areas explains why sex offenders residing in rural communities may be monitored more closely and are, therefore, more quickly rearrested for sexual and nonsexual offenses.
Results of the current study also build on the paucity of research that has explored risk factors of nonsexual offenses for sex offenders. Consistent with the research on general offenders, being under criminal justice supervision (either probation or parole), having a limited criminal history, being older, and being White reduced the risk of being rearrested for a nonsexual offense. Risk increased for young offenders with a criminal history containing numerous types of offenses, as well as for those with prior incarceration terms, prior supervision violations, and residence in rural or midsize counties. These risk factors are consistent with prior research of nonsexual recidivism for sex offenders (Hanson & Morton-Bourgon, 2005; Prentky, Knight, & Lee, 1997; Zgoba & Levenson, 2008).
Limitations
One of this study’s major limitations is that the outcome measures of sexual and nonsexual arrests were only an approximation of the true behavior of interest: sexual and nonsexual offending. Arrest was chosen as the proxy to sexual offending because, of the variables available, it was most likely to show the impact of community notification. It would be useful for a study to replicate the analyses presented here with different measures of offending (e.g., self-reports revealed through polygraph, victimization reports). Furthermore, because only crimes that occurred in New York State were included, the results could be underestimating the true rate of sexual reoffending. Although this fact is a possible limitation, of the 272,111 offenders released from prison in 1994, only 5.0% of the 67.5% who were rearrested within 3 years were rearrested out of the state in which they were released (Langan & Levin, 2002).
As a result of using a quasi-experimental design, it was impossible to discern what components of community notification (e.g., the registry, door-to-door notifications, flyers) influence sex offender rearrests. Additional research is needed to determine what aspects of community notification have the greatest impact on rearrest rates. Finally, independent of community notification, there may be community factors influencing the likelihood that an offender will be arrested for a crime (e.g., community demographics, economic well-being). These explanations and factors were outside the scope of the current study. As such, future empirical examinations should explore the impact that community factors have on the relationship between community notification and sex offender rearrest.
Conclusion
The findings of the present study support those of prior research (Petrosino & Petrosino, 1999; Sandler et al., 2008; Schram & Milloy, 1995; Walker et al., 2005) and cast doubt on the effectiveness of community notification laws to significantly reduce rates of sexual offending. In fact, not only do the results indicate that community notification is not reducing rates of recidivism, but they lend support to the conclusion that notification increases rearrests. Although increased awareness, identification, and monitoring of sex offenders cannot be ruled out as a possible explanation, prior research supports the conclusion that the results of the current study are more likely due to the aggregation of stressors related to sexual reoffending and the stigma experienced as a result of community notification.
Although these statements are not meant to suggest that community notification laws would never prevent a sexual offense from occurring, the current findings, as well as the extant research, indicate a limited likelihood that community notification laws deter and/or prevent sexual recidivism. Furthermore, even with registration and community notification, the public remains unprotected from first-time offenders, who perpetrate the majority of sexual victimizations (Sandler et al., 2008). Perhaps it is time to alter the policies and practices of community notification to ensure that the public is protected against sexual victimizations. A shift away from reactionary policies to a system where legislation is based on empirical research cannot be accomplished, however, without public education and a true understanding of sex offenders and sexual offenses.
Footnotes
Author’s Note
Data for this project were furnished by the New York State Division of Criminal Justice Services. However, DCJS was not responsible for the methods of statistical analysis or the conclusions reached. Any opinions and suggestions within this paper are those of the author only, and not representative of the views of DCJS. I would like to thank Donna Hall, James Acker, Alissa Worden, David McDowall, and Anne Bartol, as well as Jeffrey C. Sandler, for their support of this research.