Public Perceptions of GPS Monitoring for Convicted Sex Offenders: Opinions on Effectiveness of Electronic Monitoring to Reduce Sexual Recidivism

Abstract

In the United States, electronic monitoring (EM) and global positioning systems (GPS) are new applications that are used to extensively monitor and track convicted sex offenders. What is unclear though are public perceptions of this strategy. This research examines public perceptions of a national sample of Americans on the use of GPS/EM with convicted sex offenders as a method to reduce their sexual recidivism. Using a multinomial regression model, we analyze the effects of sex offender myths and parental status on public perceptions that sex offender GPS/EM is very effective in reducing sexual recidivism. Findings suggest that public perceptions of effectiveness are partially driven by myths and also that parents are unsure of this strategy. The analysis contributes to the growing body of knowledge on public perceptions of GPS/EM to manage sex offenders in communities. Implications of the study and areas for future research are discussed in light of the findings.

Keywords

electronic monitoring GPS public opinion public policy sex offenders sexual recidivism

Introduction

In the United States, electronic monitoring (hereafter, EM), such as global positioning systems (hereafter, GPS), is becoming a frequently used tool to supervise convicted sex offenders, typically as a condition of probation or parole (Armstrong & Freeman, 2011). Despite its popularity, sex offender EM has the potential to confer a false sense of security among the public (Payne & DeMichele, 2011), especially given that impact studies of EM on sexual recidivism have revealed largely null results (e.g., Meloy, 2014; Payne & DeMichele, 2011). There is the related concern that community members are advocating for and supporting more restrictive sex offender community management strategies, like GPS/EM, when public views are often couched in sex offender myths, such as stranger danger and the belief in high rates of sex crime recidivism (Levenson, Brannon, Fortney, & Baker, 2007; Payne, Tewksbury, & Mustaine, 2010; Quinn, Forsyth, & Mullen-Quinn, 2004; Tewksbury & Jennings, 2010; Zgoba, 2004). Notwithstanding the expansion of sex offender EM, relatively few studies have examined public perceptions toward the sanction and by extension the factors that drive these perceptions.

Understanding public opinion toward GPS/EM use with sex offenders, especially concerning its ability to address sexual recidivism, is important, given arguments that public views shape policy, particularly the adoption of new and punitive measures (Burstein, 2009). Moreover, public discussions about sex offender policies are disproportionately likely to be rooted in myth endorsement about sex crime (Fortney, Levenson, Brannon, & Baker, 2007; Quinn et al., 2004). That is, in contrast to policy debates regarding other violent and serious offender groups, the public ascribes to a variety of misperceptions about sex offenders, such as high rates of recidivism, “unreformability,” stranger danger, and belief that mental illness is extensive in this population (Levenson et al., 2007; Quinn et al., 2004). In turn, these perceptions have fueled the use of new and controversial reforms to manage and supervise the sex offender population.

Juxtaposed against this backdrop, to date no national study has analyzed public perceptions in relation to the effectiveness of a debated and far-reaching reform, GPS/EM to address sexual recidivism. By extension, predictors of EM policy support remain unidentified. Divides in public opinion can be expected (e.g., Cullen, Fisher, & Applegate, 2000). That is, policy preferences may be driven by a variety of factors, such as perceptions of sexual crimes, of sex offenders, and sociodemographic characteristics. In short, this absence of empirical attention is problematic, given the role of public opinion in sex offense policymaking and the wide proliferation of EM policies in the United States. For this reason, the present study has the potential to contribute knowledge to current policy debates, extant sex crime literature, and the limited scholarship that examines public perceptions of sex offender GPS/EM laws. To contextualize this research within the small body of prior work on public opinion and EM, we first provide background on EM use in the United States.

Background

EM

Electronic surveillance was first used by the justice system nearly four decades ago (Meloy, 2014). However, over the last two decades there has been an increased reliance on EM and related measures, particularly for the sex offender population (Payne & DeMichele, 2011). To illustrate, Jessica’s Law or the Jessica Lunsford Act (2005), first adopted in the state of Florida, requires that individuals who have committed select felony sex offenses be monitored for life by GPS (S. Brown, 2009). A majority of states have subsequently incorporated similar provisions, and now nearly every state has implemented some form of EM, typically, GPS monitoring to assist in the supervision of convicted sex offenders in the community (S. Brown, 2009; Meloy, 2014). The precise impetus for this proliferation is not known. However, it likely stems from the perception that EM will supplement supervision efforts and deter future crimes by increasing surveillance of sex offenders (Payne & DeMichele, 2010; Tewksbury, Mustaine, & Stengel, 2008). Others have emphasized that the proliferation of EM has followed the promotion of the technology as an effective tool to enhance public safety by private industry (generally, Lyons, 2006).

In a recent review, Meloy (2014) identifies three types of EM that are used throughout the United States: passive, active, and hybrid systems. Passive systems are used most frequently and the least expensive in part because tracking data are typically downloaded once daily. It does not alert possible violations in real time. In contrast, active systems can immediately “alert” to possible violations nearly in real time because of cellular technology, but due to cost are used less frequently. Hybrid systems are a compromise between the two and regularly transmit tracking data to supervisors albeit not as frequently as the active model. If a violation occurs, it switches to a fully engaged active system (T. Brown, McCabe, & Welford, 2007; Jannetta, 2006). Because of such concessions, this system is less expensive than an active system (Meloy, 2014).

In spite of the variety of EM systems that have been implemented in nearly every state, there are potential limitations to this technology. First, EM has been characterized as contributing to a “false sense of security” among the public. Prior research has established that most sex crime victims are familiar with their perpetrators (Black et al., 2011; Tjaden & Thoennes, 2000). Yet, because EM assumes a stranger-danger logic, it is not likely to affect the majority of sex offenses committed by known perpetrators (Payne & DeMichele, 2011). Second, EM is vulnerable to technical glitches, such as failing to alert when offenders are within restricted areas (Armstrong & Freeman, 2011). In these cases, correctional officials would be unaware of possible violations. There is some evidence that “false alarms” have resulted in reduced supervision (Caruso & Riccardi, 2013) and agencies could incur liability in these instances (T. Brown et al., 2007).

Other concerns surround the monetary and workforce costs of EM. Figures vary across states and the type of EM system, but national estimates typically place the daily cost of EM at US$13 to US$36 a day (Meloy, 2014; Payne & DeMichele, 2011). Although sex offenders are expected to pay EM fees, states still expend significant resources to implement and maintain the systems. In Tennessee, for example, even with sex offenders paying a US$50 GPS fee, a fee that is higher than national estimates, the state spent 2 million U.S. dollars in 2 years to supervise sex offenders on GPS (Meloy, 2014). There is the related concern of increasing workloads for officers supervising sex offenders on GPS (Button, DeMichele, & Payne, 2009; Payne & DeMichele, 2010). There are nearly 5 million individuals on parole, probation, or some other form of post-incarceration supervision (Maruschak & Bonczar, 2013). Shrinking fiscal budgets may increase reluctance to hire more correctional officers (Button et al., 2009). At the same time, the rapid advance of sex offender EM nationally raises questions concerning correctional systems’ ability to effectively monitor a growing population of registered sex offenders.

In addition to these concerns about using EM to monitor sex offenders, there is a question about the utility of EM to address sex offender recidivism. Thus far, only a small number of EM evaluation studies analyze the effect of EM on sex offender recidivism. Most prior research indicate no significant effect of electronic surveillance on sexual reoffending. A recent review of three studies using statistically sophisticated methodology (i.e., experimental) determined that EM exerts no significant effect on reoffending among sex offenders living in Tennessee (Tennessee Board of Probation and Parole, 2007) and California (Omori & Turner, 2015; Turner, Chamberlain, Jannetta, & Hess, 2010). At least one quasi-experimental design study suggests positive effects of EM on “high-risk” sex offenders (see Gies et al., 2012), although compliance and recidivism were tracked for only 1 year. It has been argued that intervals of at least 3 years or longer are needed to test the link between supervision and rates of reoffending (King & Elderbroom, 2014). For this reason, the Gies et al. (2012) study indicating success of GPS monitoring of high-risk sex offenders in California is notable but may have been influenced by a relatively short follow-up period.

In summary, jurisdictions are increasingly turning to EM to manage and supervise convicted sex offenders despite research indicating the shortcomings of EM. In addition, there are a variety of concerns and costs associated with EM technology. A missing link in the EM literature, however, involves public perceptions of this new application, especially perceptions about its effectiveness in stemming sex crime recidivism. Given the link between public views and public policy (Burstein, 2009), this is a critical gap to address.

Public Perceptions of Sex Crime Reform

The public is overwhelmingly receptive to new and increasingly punitive measures to manage the sex offender population (Katz Schiavone & Jeglic, 2009). More than 80% approves of sex offender registries and community notification laws, and similar percentages report feeling safer because of such policies (Anderson & Sample, 2008; Comartin, Kernsmith, & Kernsmith, 2009; Levenson et al., 2007). A substantial majority also express approval for other reforms, such as residence restrictions (Levenson et al., 2007). Prior research has identified some correlates of support for sex offender policies, such as having children, lower educational attainment, fear of sex offenders, and the endorsement of sex crime myths—such as stranger danger (Comartin et al., 2009; Mancini, Shields, Mears, & Beaver, 2010; Mears, Mancini, Gertz, & Bratton, 2008; Pickett, Mancini, & Mears, 2013; Zgoba, 2004). The public, thus far, has approved of a variety of methods to address sexual offending.

Our review of prior research identified only a small handful of investigations that focused specifically on sex offender EM or at minimum asked respondents a question about it. One of the first examinations of public opinion toward sex offender EM was part of a 2007 survey of Melbourne, Florida residents (N = 193). The study is notable for demonstrating high level of public support for electronic tracking as 60% of residents believed that EM was effective in reducing sex crime (Levenson et al., 2007). Still, the analysis was primarily descriptive and could not identify predictors of support. In contrast, Comartin and associates (2009) evaluated public approval for sex offender EM, along with other reforms such as registration and residence restrictions, and correlates of those views among a sample of Michigan residents (N = 703). In line with Levenson et al.’s (2007) work, a substantial majority, more than 83% of the public either supported or strongly supported sex offender EM. Greater fear of sex offenders and lower educational attainment were significantly associated with greater endorsement for sex offender policies. The study, however, did not disaggregate by “type” of policy but examined general policy approval for various laws; as a result, findings do not illuminate the specific factors associated with EM support.

In the only study that specifically evaluates predictors of approval for EM, Button, Tewksbury, Mustaine, and Payne (2013) surveyed residents in two cities in Virginia (N = 746). Here, less than a majority of residents, 44%, held “extremely positive” views of GPS monitoring (e.g., believing it was effective in reducing sexual offending). These views were predicted by being female, reporting less annual income, identifying as non-White, residing in the presence of vulnerable populations (e.g., percentage of households in the Zone Improvement Plan [ZIP] code with residents below age 18), and not reporting neighborhood incivility. Missing from their research though are some theoretically relevant factors such as the effect of parental status. This omission may be limiting, given that prior work suggests that parents are significantly more supportive of sex offender restrictions and “get tough” post-incarceration sanctions (Mancini et al., 2010). Parents may be supportive of EM because they perceive that their children, vulnerable populations, are at a higher risk of sexual victimization. More generally, parents, particularly those with minor children, have served as “stakeholders” in the movement to address sexual offending, having had tremendous influence on the creation and continued development of new sex crime laws (Zgoba, 2004). For these reasons, their policy preferences are expected to differ from those without minor children (Anderson & Sample, 2008).

Taken together, these prior findings suggest complexities in public opinion toward EM that should be further explored with samples that allow for greater generalizability. In addition, noticeably absent are studies that have systematically assessed public perceptions of sex offender EM on a national scale. This limitation is troubling, given that EM is widespread and controversial, and because some scholars have implicated that public (mis)perceptions are a catalyst behind similar sex offender restrictions (see, for example, Sample & Kadleck, 2008; Zgoba, 2004). Under this backdrop, we now turn to the current investigation.

The Current Study

The current study investigates public perceptions about the ability of GPS/EM to effectively prevent convicted sex offenders from committing new sex crimes. Because of the limited research on public opinion and GPS use with sex offenders, the three research questions and corresponding hypotheses were developed by drawing on the limited body of research and the wider body of literature on public opinion and sex offender policies (e.g., Button et al., 2013; Comartin et al., 2009; Levenson et al., 2007; Mancini & Budd, 2015; Mancini et al., 2010; Mears et al., 2008; Pickett et al., 2013):

Research Question 1: The stranger danger myth: Do perceptions about the victim–offender relationship influence community members’ opinion that GPS/EM is very effective in reducing sexual recidivism?

Hypothesis 1: Individuals who endorse stranger danger myths will be more likely to feel that GPS/EM is a very effective strategy to reduce sexual recidivism.

Research Question 2: The sexual predator myth: Do perceptions about sex offender recidivism influence community members’ opinion that GPS/EM is very effective in reducing sexual recidivism?

Hypothesis 2: Individuals who endorse sexual predator myths will be more likely to feel that GPS/EM is a very effective strategy to reduce sexual recidivism.

Research Question 3: Are parents of minor children more likely than other individuals to feel that GPS/EM is a very effective strategy to reduce sexual recidivism?

Hypothesis 3: Parents of minor children will be more likely than other individuals to feel that GPS/EM is a very effective strategy to reduce sexual recidivism.

Method

This research analyzed public opinion survey data collected by Zgoby International on behalf of the Center for Sex Offender Management (CSOM)—a publicly funded agency that provides information about sex offenders and related policy. We were granted access and received permission from CSOM to conduct further analyses on the survey data. For the purpose of the survey, sex offenders were defined as “someone who has been convicted of one or more sex crimes involving physical contact, such as molesting a child or raping an adult” (CSOM, 2010, p. 1). CSOM designed the original survey instrument, with input from public opinion specialists and sex crime experts, which was then piloted with a small convenience sample. The survey focused on perceptions of the effectiveness of a variety of criminal justice and community management strategies, specifically designed to target sex offenders. In addition, it asked about subtopics such as perceptions relating to sex offender recidivism, types of victims targeted by sex offenders, and the treatment malleability of sex offenders. Sociodemographic information was also collected from respondents.

The public opinion poll was conducted in the contiguous United States from February to March 2010 using a random digit dialing (RDD) technique. All respondents had to be 18 years of age or older to participate. The resulting sample size was 1,005 respondents. For the total sample, one can say with 95% confidence that the error attributable to sampling is ±3.2 percentage points. Because we used a listwise deletion strategy for missing data, results based on the final model (N = 837) have a margin of error of ±3.4 percentage points.

Dependent Variable

The dependent variable is a categorical variable measuring public perceptions of the effectiveness of GPS/EM to track convicted sex offenders and decrease their likelihood of sexual recidivism. Response choices range from very effective to not at all effective and not sure. Because public opinion research tends to investigate support dichotomously (1 = support vs. 0 = non-support) or be descriptive in nature (e.g., Katz Schiavone & Jeglic, 2009; Levenson et al., 2007), the current analysis is unique in that it examines all five response categories. We include respondents who are “unsure” for two reasons. First, “unsure” respondents could potentially benefit from campaigns to disseminate factual information about sex crime issues. At the same time, no prior research has empirically examined this category.

Independent Variables

Perceptions of victim–offender relationship

Given arguments that sex crime policy support has been shaped largely by distorted perceptions of the nature of sex offending (e.g., Pickett et al., 2013), analysis models the effects of endorsing popular myths on public opinion. Victim–offender relationship is a proxy measure for the stranger-danger myth. The survey asked respondents, “Which of the following statements about sex offenders who victimize children do you think is most true?” Respondents chose one response from the following options: “Most sex offenders victimize children who” . . . are “well known or related to the offender,” are “an acquaintance to the offender,” are “a stranger to the offender,” or are “unsure of the victim-offender relationship.” This was coded into four dummy variables. “Not sure” was the omitted comparison category. There were no missing data for this measure.

Perceptions of sex offender recidivism

Given the public image of sex offenders as highly driven to sexually reoffend (Levenson et al., 2007), the sexual predator myth, we include two sexual recidivism measures. The first variable measures the percentage of convicted sex offenders that respondents believe would sexually recidivate. Response categories ranged from “less than 25%” to “75% or more” and “not sure.” Because of the low response frequency in the “less than 25%” category, we combined “less than 25%” with “between 25% and 50%.” Dummy variables were included in the final model: “up to 50%,” “between 50% and 75%,” “75% or more,” and “not sure.” The second measure is the type of crime the public perceived the convicted sex offender would commit upon reoffense. Respondents chose from a “non-violent, non-sexual offense,” a “similar sex offense,” an “offense that is more serious and violent,” or “not sure.” Dichotomous variables were created to capture each response category. “Not sure” was the omitted comparison category for both recidivism measures. There were also no missing data for these measures.

Parental status

Because prior scholarship indicates that parents hold favorable views toward sex crime laws compared with those without children (Mancini et al., 2010; generally, Zgoba, 2004), we include parental status. Parental status is a dichotomous variable: 1 = a parent of a child under the age of 17 and 0 = not a parent of a child under the age of 17. There were no missing data for the parental status measure.

Sociodemographic characteristics

The models control for age, education, income, place of residence, marital status, race, and sex. Age was a continuous variable that ranged from 19 to 92 years. Approximately 1.5% of age data were missing. Education response choices included “less than high school” through “college graduate.” There were no missing data. Income was measured using six response categories: “less than $25,000” up to “more than $100,000.” Approximately 15% of income data were missing. This finding is not atypical, because measures of annual income frequently incur missing values in public opinion polls (Tourangeau & Yan, 2007). Place of residence included city, suburb, or rural area. Dummy variables were created, and “suburb” was the omitted comparison category. Approximately 0.3% of residency information was missing. Marital status was coded 1 = married and 0 = not married. Approximately 0.2% of marital status data were missing. Race was coded as three dummy variables: White, Black, and other. White was used as the omitted comparison category. Approximately 1.4% of race data were missing. Finally, female respondent (1 = female, 0 = male) was included in the model. There were no missing data on sex.

Analytic Strategy

A multinomial logistic regression model (MNLM) was used to analyze the data, given the non-ordered response categories (see Long & Freese, 2006). “Very effective” was used as the reference category because, as prior research suggests, there is a high level of public support for sex offender laws. All results are interpreted as odds ratios. Because of the complexity of the model and the corresponding output, results in the tables are shown only for the reference category, “very effective,” in comparison with the other outcome categories, although we do discuss statistically significant comparisons between all five response categories in the “Results” section (other results are available upon request). The MNLM used a listwise deletion strategy for item non-response. After missing data were dropped from the independent variables, the final MNLM analyzed perceptions of 837 (83%) respondents concerning their views about GPS/EM as an effective strategy to decrease sexual recidivism.

Results

When looking at the sample as a whole and perceptions of GPS/EM reducing sexual recidivism (see Table 1), approximately 32% of Americans thought that GPS/EM was very effective, 47% thought it was somewhat effective, 11% thought it was somewhat ineffective, 6% thought it was not at all effective, and 3% were unsure of its effectiveness. Based on the bivariate analysis, age, education, and income significantly influence respondents’ perceptions about GPS/EM effectiveness in reducing sexual recidivism for convicted sex offenders living in communities.

Table 1.

Descriptive and Bivariate Statistics on Perceptions of the Effectiveness of GPS/Electronic Monitoring of Convicted Sex Offenders (N = 1,005), Reference Category: Very Effective.

			Very effective		Somewhat effective		Somewhat ineffective		Not at all effective		Not sure
	Minimum	Maximum	M	SD	M	SD	M	SD	M	SD	M	SD
Independent variables
Victim–offender relationship
Well known/related	0	1	0.725	0.447	0.734	0.442	0.795	0.430	0.641	0.484	0.813	0.397
Acquaintance	0	1	0.148	0.356	0.136	0.343	0.130	0.337	0.156	0.366	0.063	0.246
Stranger	0	1	0.086	0.281	0.065	0.247	0.056	0.230	0.078	0.270	0.063	0.246
Percent of sex crime recidivism
Up to 50%	0	1	0.185	0.389	0.210	0.407	0.241	0.430	0.266	0.445	0.156	0.367
Between 50% and 75%	0	1	0.346	0.475	0.361	0.481	0.389	0.490	0.250	0.436	0.250	0.440
75% or more	0	1	0.404	0.492	0.365	0.482	0.315	0.467	0.438	0.500	0.344	0.483
Sex crime recidivism crime type
Non-violent offense	0	1	0.123	0.111	0.036	0.186	0.028	0.165	0.047	0.213	0.031	0.177
Similar sex offense	0	1	0.574	0.495	0.570	0.496	0.611	0.490	0.484	0.504	0.531	0.507
More violent, more serious offense	0	1	0.373	0.484	0.348	0.477	0.333	0.473	0.391	0.492	0.219	0.42
Parental status
Parent of child <17	0	1	0.213	0.410	0.168	0.374	0.213	0.411	0.156	0.367	0.219	0.420
Control variables
Age	19	92	57.865	15.769	59.802	14.164	59.454	14.435	63.556**	14.074	60.219	16.23
Education	1	4	3.120	0.884	3.270*	0.817	3.444**	0.846	2.859*	1.067	3.125	1.100
Income	1	6	3.464	1.789	3.817**	1.676	3.944*	0.846	3.161*	1.787	3.909	1.998
Place of residence
City	0	1	0.512	0.501	0.466	0.499	0.481	0.502	0.500	0.504	0.531	0.507
Rural	0	1	0.236	0.425	0.265	0.442	0.287	0.454	0.266	0.445	0.281	0.447
Marital status
Married	0	1	0.611	0.488	0.639	0.481	0.620	0.488	0.578	0.498	0.516	0.508
Race
Black	0	1	0.122	0.328	0.110	0.313	0.103	0.305	0.065	0.248	0.194	0.402
Other	0	1	0.122	0.328	0.100	0.300	0.065	0.248	0.113	0.319	0.066	0.250
Sex
Female	0	1	0.593	0.492	0.612	0.488	0.602	0.492	0.500	0.504	0.656	0.483

Note. Statistical tests use “very effective” as the reference category. GPS = global positioning systems.

p < .05. **p < .01. ***p < .001.

To disentangle predictors of these views, we turn to the MNLM (see Table 2). Our first research question examined the relationship between the victim and the offender, the stranger-danger myth. Do perceptions about the victim–offender relationship influence community members’ opinion that GPS/EM is very effective in reducing sexual recidivism? Believing that most sex offenders victimize strangers increases the odds of perceiving GPS/EM to be very effective by 6 times relative to being not effective at all, holding all other variables constant (p ≤ .05) . Unexpectedly, all victim–offender relationship categories were significant leading to partial support of this hypothesis. Believing that most sex offenders victimize children who are well known or related to the sex offender or an acquaintance increases the odds of perceiving GPS/EM to be very effective by 4.49 (well known/related) and 4.48 times (acquaintance) relative to being not effective at all, holding all other variables constant (p ≤ .01; p ≤ .05).

Table 2.

Multinomial Regression Model of Perceptions of Effectiveness of GPS/EM in Decreasing Sexual Recidivism, Reference Category: Very Effective (N = 837).

	Somewhat effective		Somewhat ineffective		Not at all effective		Not sure
	Coef.		Coef.		Coef.		Coef.
	SE	Odds ratio	SE	Odds ratio	SE	Odds ratio	SE	Odds ratio
Independent variables
Victim–offender relationship
Well known/related	−0.834		−0.126		−1.501	4.49**	−0.590
	0.433		0.716		0.579		0.888
Acquaintance	−0.812		−0.485		−1.499	4.48*	−1.821
	0.474		0.791		0.695		1.345
Stranger	−1.218	3.38*	−0.610		−1.792	6.00*	−1.403
	0.510		0.845		0.779		1.357
Percent of sex crime recidivism
Up to 50%	0.547		0.333		0.795		−1.499
	0.384		0.595		0.723		0.814
Between 50% and 75%	0.578		0.449		0.433		−1.142
	0.371		0.577		0.716		0.705
75% or more	0.311		−0.015		0.631		−1.227
	0.368		0.583		0.698		0.684
Sex crime recidivism crime type
Non-violent offense	1.856	0.16*	2.134		1.132		1.139
	0.774		1.148		1.018		1.407
Similar sex offense	0.550		1.041		−0.455		−0.365
	0.449		0.810		0.622		0.806
More violent, more serious offense	0.549		0.865		−0.551		−1.233
	0.461		0.834		0.650		0.929
Parent of child <17	−0.221		0.281		0.291		1.282	0.28*
	0.23		0.350		0.465		0.623
Control variables
Age	0.014	0.98*	0.023	0.97*	0.019		0.040
	0.006		0.010		0.012		0.020
Education	0.219	0.80*	0.522	0.59**	−0.163		0.046
	0.106		0.180		0.192		0.310
Income	0.132	0.88*	0.115		−0.063		0.187
	0.060		0.094		0.118		0.177
Place of residence
City	−0.048		0.245		0.022		0.223
	0.202		0.315		0.399		0.589
Rural	0.180		0.368		0.250		0.443
	0.234		0.366		0.445		0.671
Married	−0.142		−0.239		−0.055		−0.189
	0.196		0.304		0.369		0.563
Black	0.190		−0.092		−0.794		0.211
	0.259		0.412		0.638		0.705
Other	−0.781		−0.563		−0.019		−13.795
	0.258		0.451		0.497		539.261
Female	0.065		−0.098		−0.350		0.341
	0.168		0.257		0.320		0.489

Note. Statistical tests use “very effective” as the reference category. For clarity, odds ratios are only presented for variables that are statistically significant in comparison with the reference category, very effective. GPS/EM = global positioning systems/electronic monitoring.

p < .05. **p < .01. ***p < .001.

The second research question investigated two measures of sexual recidivism to assess the sexual predator myth: (a) the percentage of sex offenders the public thought would repeat their sex crimes after conviction and (b) the type of sex crime the offender would commit upon reoffense. The hypothesis that individuals who endorse sex offender predator myths would be more likely to judge GPS/EM as a very effective strategy in reducing sexual recidivism was not supported, although these myths predicted other outcome categories. Recidivism measures were influential in predicting public perceptions on other degrees of effectiveness, especially for individuals who were unsure. For example, believing that between 50% and 75% of sex offenders would repeat their sex crimes after conviction increases the odds of perceiving GPS/EM to be somewhat effective by 5.59 times relative to being unsure about GPS/EM, holding all other variables constant (p ≤ .05).

The second strategy investigated sexual recidivism in relation to the type of crime the public thought the sex offender would commit upon reoffense. If the public believed that sex offenders would recidivate with a non-violent non-sexual offense, they were less likely to feel that GPS/EM is a very effective strategy to reduce recidivism. With this belief, the odds of perceiving GPS/EM to be somewhat effective increase by 6.41 times relative to being very effective, holding all other variables constant (p ≤ .05). No significant differences emerged when investigating perceptions of similar sex crimes and perceptions of more serious, more violent crimes.

Our final inquiry addressed parental status: Are parents of minor children more likely than other individuals to feel that GPS/EM is a very effective strategy to reduce sexual recidivism? Surprisingly, parents were unsure about this strategy. Therefore, this hypothesis was not supported but predicted an unexpected response category, given the state of the literature. For parents with children below the age of 17, the odds of being unsure increase by 3.60 times relative to thinking that GPS/EM is a very effective strategy, holding all other variables constant (p ≤ .05).

Other significant findings pertain to age, education, and income. The odds of perceiving GPS/EM as a very effective strategy to decrease the likelihood of sexual recidivism waned as people got older. For example, for each additional year in respondent age, the odds of perceiving GPS/EM to be somewhat effective or somewhat ineffective increase by 1.01 and 1.02 times relative to being very effective, holding all other variables constant (p ≤ .05). As education increased, the odds of perceiving GPS/EM to be somewhat ineffective increase by 1.69 times relative to being very effective, holding all other variables constant (p ≤ .01). Income followed a similar pattern. As income increased, the odds of perceiving GPS/EM as very effective decreased. For example, for each unit increase in yearly income, the odds of perceiving GPS/EM to be somewhat effective increase by 1.14 times relative to being very effective, holding all other variables constant (p ≤ .05). No significant differences surfaced regarding place of residence, marital status (married), race (Black, other), or sex (female).

Discussion

As policy debates concerning best practices for addressing sex offender management continue, policymakers and scholars should consider, as an important discussion point, public perceptions of sex crime legislation and the factors that shape and augment these views. Seeking to help inform these discussions, this research investigated public perceptions of a new application that is being used in the United States to manage convicted sex offenders: GPS/EM. This research suggests that some myths, in part, increase the public’s belief that GPS/EM is very effective at reducing sexual recidivism of convicted sex offenders. In particular, here, stranger danger was approximately 1.5 times more likely than other victim categories to increase the public’s belief that GPS/EM was very effective at reducing sexual recidivism. While the public perceived GPS/EM as a very effective method in decreasing sexual recidivism for all victim categories, these findings suggest that the stranger-danger myth still persists and is influential enough to shape public perceptions on a new sex offender management strategy. To make informed policy decisions, public perception research that disentangles what is driving public perceptions of public policy should be evaluated alongside with studies that assess whether newly implemented sex offender policies are effective at meeting their intended goals.

There also needs to be an awareness that ambivalence about sex offender policies can and does exist. As discussed previously, sex offender public opinion research, and a larger literature centered on understanding crime policy attitudes, tend to neglect those respondents who are unsure of how lawmakers and other criminal justice actors address convicted sex offenders and community management. This was illustrated here with conflicting results for individuals who were unsure of GPS/EM when investigating the sexual predator myth. Sexual predator myths significantly influenced unsure respondents’ perceptions on the effectiveness of GPS/EM and sexual recidivism ranging from not effective at all, somewhat ineffective, and somewhat effective. In addition, if respondents were a parent of a minor child they were significantly more likely to be uncertain about the usefulness of GPS/EM to prevent sex crime recidivism. Even though GPS/EM falls into line with the continued and increased tracking of convicted sexual offenders, this research suggests that some myths, such as the sexual predator myth, and sociodemographic characteristics, such as being a parent of a minor child, can result in ambivalence when asked to evaluate a sex offender policy. In addition, theoretically, research has suggested that parental status more so than other sociodemographic characteristics helps explain punitive sex crime policy “buy in” (generally, Mancini et al., 2010; Zgoba, 2004). This research suggests that if unsure respondents are neglected from sex crime policy research, levels of punitiveness may vary more than originally predicted. This too could include parental perceptions of punitive sex crime policies.

Other sociodemographic characteristics contributed to attrition in “very effective” perceptions of GPS/EM to combat sexual recidivism. As Americans aged, they were less convinced that EM is very effective in curbing sexual recidivism. Notably, age has not been a consistent indicator of public attitudes toward sex crime policy support (Button et al., 2013; Mancini et al., 2010). As education and income—indicators of socioeconomic status—increased, so too did public pessimism regarding the efficacy of GPS/EM to prevent sex. These findings are in line with prior research such as that of Button and colleagues (2013) who reported that higher annual income was associated with a reduction in extremely positive views of EM, whereas greater educational attainment was correlated with an increase in extremely negative views.

Although these findings contribute to the public opinion literature on sex offender policy, in particular in the new area of using GPS/EM to monitor convicted sex offenders in communities, this study has several limitations. As is typical with public opinion surveys (e.g., Button et al., 2013), some groups were overrepresented in the sample: women, Whites, and older Americans. Although these data are drawn from a national random sample, overrepresentation of specific groups has the potential to limit the generalizability of the results. In addition, there were significant differences pertaining to the missing data on age and sex (i.e., the missing group was significantly older and had a higher representation of females). For age, because the odds ratio was so small (roughly 1.01 and 1.02) and given the mixed findings pertaining to age effects on shaping sex offender policy support (see, for example, Button et al., 2013; Mancini et al., 2010), the marginal age finding should be regarded with caution as there is the potential for bias. Sex, overall, was not a significant predictor in the final model and has also historically been an inconsistent indicator of sex crime policy support. For example, although some studies have found that women are more supportive of some “get tough” reforms, such as requiring juveniles to register as sex offenders (Stevenson, Sorenson, Smith, Sekely, & Dzwairo, 2009), other investigations have found no sex effect on policy support (Mancini, 2014).

Pertaining to the survey instrument, there were no questions that asked whether respondents themselves or someone they know had been a victim of crime or specifically a victim of a sexual crime. Therefore, we had no way to control for respondents’ prior personal or vicarious victimization experiences. There were no questions gauging public knowledge on GPS/EM systems in general. Public knowledge of active, passive, or hybrid systems may influence perceptions of effectiveness in addressing sexual recidivism. What if the public assumes that all systems are active systems that immediately alert to a violation? We also cannot account for why individuals responded the way they did to questions. For example, the survey did not include follow-up questions to further probe unsure responses concerning GPS/EM.

Future Research and Conclusion

Given the small handful of studies centered on public perceptions of GPS/EM as a useful tool for sex offender management and because public opinion has the potential to shape sex crime policy, greater research is needed to better evaluate public perceptions of this strategy. In particular, additional inquiries should consider assessing public perceptions on the appropriate use of GPS/EM in relation to specific types of convicted sexual offenders (e.g., men, women, juveniles), specific sexual crimes (e.g., stranger rape, statutory rape, incest), and monitoring intensity (e.g., active, passive, or combined systems). Pertaining to the type of GPS/EM system, research should determine whether public support is built on the assumption that all systems are active GPS systems or whether ambivalence is the result of not knowing the type of GPS/EM system being used in their community. In addition, as many of these laws are aimed at protecting children and providing parents with tools to protect their children, future research on GPS/EM should further delve into parental perceptions of this strategy in regard to safety, use-value, and resource allocation. Because this study focused on parents with children below the age of 17, it is not clear whether parental status would vary based on the age of the child. Put differently, would those with young children versus teenagers be more supportive of such a policy instead of unsure? These avenues would be important to address as parental status is assumed to be a theoretically important characteristic to assess support of sex crime public policy and laws. Accordingly, carefully designed surveys and qualitative interviewing could be used in future research to advance the current knowledge base of public perceptions toward sex crime policy.

To conclude, in democratic societies, public views matter (Burstein, 2009). We argue, along with others, that public opinion, or at the very least perceptions of it, has shaped the sex crime policy landscape in the United States (Logan, 2009; Meloy, Curtis, & Boatwright, 2013). Notably, EM is just one policy response juxtaposed against an array of new reforms and restrictions for convicted sex offenders living in the United States. Monitoring public views, particularly on a consistent national and international basis, can assist with tracking changes in policy (non)support or revealing nuances in (dis)approval, and even ambivalence, not only in the United States but also in other countries. If public opinion, at least to some extent, drives the development of additional sex crime policies, and to the extent that the public and parents represent key “stakeholders,” it would seem that there is sufficient justification to monitor public opinions on sex offender policy over time as legal responses to sex offenders change. This is especially pertinent if the public, as indicated by unsure responses, are in some instances undecided toward certain sex crime policies.

Footnotes

Acknowledgements

We would like to thank Dr. George Palermo and the anonymous reviewers for their invaluable feedback on the manuscript.

Author’s note

The opinions, findings, and conclusions expressed in this publication are those of the authors and do not necessarily reflect those of the Center for Sex Offender Management or Zogby International.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

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