Romeo,Juliet,and Statutory Rape

Abstract

Statutory rape is an important yet understudied topic. There is broad public support for the prosecution of older adults who engage in sexual relationships with minors regardless of perceptions of consent by either party. However, some scholars worry that expansive definitions within these laws have led to the widespread involvement of the justice system in the lives of similarly aged teenagers engaging in relatively normal sexual behavior, so called “Romeo and Juliet” liaisons. This, in turn, has called into question the legitimacy of national policies, such as sex offender registration, because of the presumption that registries are likely filled with these kinds of cases which may not represent the intent of legislatures and the public. Despite the importance of these debates, there is little research assessing the prevalence of Romeo and Juliet cases in official crime statistics or that analyze differences in characteristics of statutory rape as a function of victim–offender age differences. Drawing on more than 20 years of police data from over 6,000 police departments in the United States, this study found statutory rape cases were rare and Romeo and Juliet cases were even rarer. Multivariate models showed several distinctions between statutory rape cases as a function of the age differences between victim and offender. Of note, the odds that additional forms of sexual aggression occurred in the incident grew as the age difference expanded.

Keywords

National Incident Based Reporting System Romeo and Juliet sex offender registry sex crimes statutory rape

Introduction

Age of consent laws exist to protect minors from sexual exploitation from older partners (Glosser, Gardiner, & Fishman, 2004; Manlove, Ryan, & Franzetta, 2007). The underlying premise is that minors lack the cognitive capacity to effectively guard against manipulation by adults and that this is particularly pronounced as age differences increase between sexual partners (Manlove, Moore, Liechty, Ikramullah, & Cottingham, 2005). Differences in physical, cognitive, and social power imply juveniles have limited ability to willingly consent to sexual advances from adults. Regardless of an adult’s intention to manipulate a youth, or perception of consent by either party, age of consent laws assert that sex cannot be consensual within certain age restrictions. As such, laws exist in all states establishing a minimum age at which an individual may legally consent to sex. Some states also establish an age difference between partners for consent purposes before a sexual encounter is designated a crime. Violations of these statutes are referred to as “statutory rape.”

Violations of statutory rape laws have resulted in thousands of arrests and prosecutions in the United States (Oliveri, 2000; Troup-Leasure & Snyder, 2005). The public has generally remained supportive of the enforcement of these laws in cases where there are large age differences between victims and offenders (Beck & Boys, 2012; Horvath & Giner-Sorolla, 2007; Kernsmith, Craun, & Foster, 2009). However, age of consent laws can become controversial when applied to like-aged teenagers who are prosecuted for what many believe to be normative sexual behavior (see, for example, Cohen, 2011; Franklin, 2012).

To illustrate, some states allow the prosecution of a 17-year-old who has a mutually willing sexual relationship with a 15-year-old (Cohen, 2011; Oberman, 2000). Generally, the public does not believe this type of sexual encounter warrants criminal justice involvement (Koon-Magnin & Ruback, 2013; Sahl & Keene, 2012). For example, Beck and Boys’ (2012) found only a small percentage of survey respondents, less than 10%, felt that criminal charges should be possible when same-aged teenagers engaged in consensual sex. Importantly, only a fraction of those supporting criminalization also felt the charge should be a felony or include the possibility of sex offender registration.

This stance by the public is likely tied to the fact that sexual relationships between teenagers who are close in age are fairly common in the United States. National statistics show a large portion of adolescents engage in sexual intercourse. In 2013, surveillance data from the Centers for Disease Control found that 46.8% of juveniles have had sexual intercourse in their lifetime, 15% had four or more partners, and 34% had sex in the 3 months prior to the survey (Kann et al., 2014). Furthermore, national probability samples indicate approximately half of sexually active adolescents report their first sexual partner was 3 or more years older than themselves (J. S. Manlove et al., 2007). Collectively, these studies indicate there are several million sexual encounters each year which qualify as statutory rape.¹

National statistics also show the vast majority of teens engaged in sexual encounters deem them consensual (Finer & Philbin, 2013; Laumann, 1994; Martinez, Copen, & Abma, 2011). The fact that sexual encounters between teenagers close in age are common, or that most youth believe them consensual, does not mean they are lacking in exploitation or are otherwise healthy. Public opinion research shows that most adults in the United States, and most other Western nations, believe that sexual behavior by teenagers aged 15 and below is almost always “wrong” (Widmer, Treas, & Newcomb, 1998). Regardless, the public is skeptical of the assertion that sexual encounters between similarly aged youth should all be characterized as criminal (see, for example, Beck & Boys, 2012; Koon-Magnin & Ruback, 2013; Sahl & Keene, 2012), that they should be treated similarly to older adults who engage in sexual activity with minors. This controversy over the potential criminal prosecution of teenagers close in age engaging in consensual sex is illustrated by the tendency in scholarship, law, and policy to refer to them as “Romeo and Juliet” cases.

Use of the phrase “Romeo and Juliet,” hereafter R&J, as a moniker for these types of criminalized sexual encounters first appeared in academic literature via Huffman and Huffman’s (1987) work tracing more than a century of concern, expressed primarily in pop culture, over the criminalization of these encounters. The term grew in prominence across the United States, formally appearing within legal debate and legislation several decades later. In 2007, 40 years after academia first introduced the term in this context, Florida legislators made explicit reference to R&J in debating sex offender registration reforms sparked by the Adam Walsh Act (The Florida Senate, 2011). In this case, some legislators were expressing concern that the Adam Walsh Act would require registration for high school students engaged in consensual sexual relationships with partners close in age rather than what many saw as the intended population of registries: those “deemed too dangerous and likely to reoffend to be left unmonitored” (Sahl & Keene, 2012, p. 3).

While violations of age of consent laws are a distinct criminal issue, they are also intertwined with debate and policy that surrounds sex offender registration, as demonstrated in Florida. Anecdotal evidence reinforces this related concern between age of consent laws and sex offender registration. As described by Franklin (2012, p. 309),

Shane Sandborg cannot drop his daughter off for her first day of school. He cannot coach his son’s little league team. He cannot attend any of his children’s birthday parties. Due to his oldest daughter’s birth, Shane cannot do any of these things. After Shane’s sixteen-year-old fiancée gave birth to their now seven-year-old daughter, Shane was investigated, charged, and convicted of criminal sexual abuse. He was just 15 months older than his fiancée. Shane was required to register on the Illinois Sex Offender Registry, and the label “sex offender” has haunted him ever since.

In response to such cases, some states have started to implement R&J exceptions that allow legal recourse for consenting teenage sexual partners who are close in age.

Notwithstanding the power of anecdotal evidence, policy debates are rarely fruitful when case studies are the only kind of information available. It is unclear, for example, how often or how accurately these anecdotes describe the problem facing policy makers. That is, there is a great need for empirical facts within this debate—yet few exist. First, little research speaks to whether R&J cases are a rare exception or common occurrence among statutory rape crimes reported to the police. Second, it is unclear whether cases which are referred to as R&J have similar or different characteristics from other statutory rape cases with more egregious age differences (e.g., 4 or more year’s difference). In fact, as noted by Hines and Finkelhor (2007), there is very little empirical research on statutory rape in general. The dearth of literature is at least in part a function of the difficulty in measurement implied by these laws. Statutory rape, and R&J in particular, represents a crime with exceptional variation over time and place regarding the underlying definitions and legal processes surrounding the behavior, the complexity of laws defining these crimes.

Complexity in Age of Consent Laws

While the phrase “statutory rape” is typically not found in state statutes (James, 2009), the concept is pervasive in criminal codes across the nation. In the United States, statutory rape laws are primarily based on the age of the minor (Cocca, 2004), but there is no national standard defining age of consent. Rather, states use different statutory variations to set an age of consent for those under the age of 18. Some states also set legal rules for differences in age between victim and offender (Smith & Kercher, 2011). Using state’s 2015 statutory codes, Table 1 describes the age of consent in all U.S. states and the District of Columbia. Table 2 lists all age-difference clauses for the 34 states with such a clause.

Table 1.

Age of Consent by State: 2015 Statutes.

Age of consent	States and territories
16	Alabama, Alaska, Arkansas, Connecticut, District of Columbia, Georgia, Hawaii, Indiana, Iowa, Kansas, Kentucky, Maine, Maryland, Massachusetts, Michigan, Minnesota, Mississippi, Montana, Nebraska, Nevada, New Hampshire, New Jersey, North Carolina, Ohio, Oklahoma, Pennsylvania, Rhode Island, South Carolina, South Dakota, Vermont, Washington, West Virginia (n = 32)
17	Colorado, Illinois, Louisiana, Missouri, New Mexico, New York, Texas, Wyoming (n = 8)
18	Arizona, California, Delaware, Florida, Idaho, North Dakota, Oregon, Tennessee, Utah, Virginia, Wisconsin (n = 11)

Note. Age of Consent laws are found within the state statutes listed in Table 2.

Table 2.

Romeo and Juliet Clauses in 34 States: 2015 Statutes.

State	Age	Consent exception	State statue(s)
Alabama	16	Minor ≥ 12 and defendant < 2 years older	§ 13A-6-62
Alaska	16	Minor ≥ 13 and offender is < 3 years apart	§11.41.436
			§ 11.41.438
			§ 11.41.440
Arizona	18	<2 years apart in age when both minors are ≥ 15 years old	§ 13-1405
Arizona	18	Protects defendants in high school who are ≤ 24 months older than the victim and the conduct is consensual	§ 13-1407
Arkansas	16	<3 years older if victim is < 12 years old	§ 5-14-103
		<4 years older if victim is ≥ 12 years old	§§ 5-14-125 & -126
		≤3 years older if victim is < 14 years old
Colorado	17	Minor < 15 if person < 4 years apart	§§ 18-3-402(1)(d)(e)
Colorado	17	Minor ≥ 15 but < 18 if person < 10 years apart	§§ 18-3-402(1)(d)(e)
Connecticut	16	Minor ≥ 13 if person ≤ 2 years apart	§§ 53a-70 & -71
Connecticut	16	Minor ≥ 13 but < 16 if person ≤ 3 years apart	§§ 53a-70 & -71
D.C.	16	<4 year age difference between victim and perpetrator	§ 22-3008
Florida	18	Minor ≥ 16 but ≤ 17 if defendant ≤ 23 years old	§ 794.05
Florida	18	R&J exception sex offender registry removal, consensual sex where victim ≥ 13 but < 18 and defendant ≤ 4 years older	§ 943.04354
Hawaii	16	Minor ≥ 14 but ≤ 15 if defendant is < 5 years older	§ 707-730
Hawaii	16	R&J exception for sex offender registry, person convicted of statutory rape is required to register unless < 18 at the time of the crime	§§ 846E-1 & -2
Indiana	16	Minor ≥ 14 but ≤ 15 if person is < 4 years older, defendant and victim were dating or in an ongoing personal relationship, and defendant is < 21 years old	§ 35-42-4-9(a)(e)
		R&J exception for sex offender registry, court can release defendant from requirement if crime is a Class C felony and defendant is < 4 years older than the minor	§ 11-8-8-4.5
			§§ 11-8-8-7 & -8
			§ 11-8-8-19
Iowa	16	Minor ≥ 14 but ≤ 15 if defendant is < 4 years older	§ 709.4
Kentucky	16	Minor > 12 but < 16 if defendant is close in age to the minor R&J exception for sex offender registry, person convicted of a sex crime against a minor is required unlessdefendant is < 18 at the time of the crime	§§ 510.040 & -.050
			§ 17.500
			§ 17.510
Louisiana	17	Minor ≥ 13 but < 17 if victim–offender age difference ≤ 2 and defendant < 17	§ RS 14:80.1
Maine	16	Minor ≥ 14 but ≤ 15 if defendant is < 5 years older	§ 17-A s 254
Maryland	16	Minor ≥ 14 if person < 4 years older	§ 3-304§§ 3-306 & -307
Maryland	16		§ 3-304§§ 3-306 & -307
Minnesota	16	Minor > 13 but < 16 and age difference < 2 years (penetration)	§§ 609.344 & .345
Minnesota	16	Minor > 13 but < 16 and age difference < 4 years (contact)	§§ 609.344 & .345
Mississippi	16	Minor ≥ 14 and < 16 if person is ≤ 3 years older	§§ 97-3-65, 97-3-95
		R&J exception for sex offender registry, above criteria and if person was ≤ 18 at the time of the crime	§ 97-3-97
			§ 45-33-23 & -25
Nebraska	16	Minor ≥ 12 and < 16 if person is ≤ 18	§ 28-319
New Hampshire	16	Minor > 13 and < 16 and defendant is ≤ 4 years older	§§ 632-A:2, -A:3, &
New Hampshire	16	R&J exception for sex offender registry, above criteria and if person engages in consensual sexual penetration	-A:4
New Jersey	16	Minor ≥ 13 and if person is < 4 years older	§§ 2C:14-2 & -3
New Mexico	17	Minor ≥ 13 and defendant < 18 and < 4 years older	§ 30-9-11 & -13
North Carolina	16	Minor ≥ 13 and defendant is < 4 years older	§§ 14-27.23 – .25
North Carolina	16	Minor ≥ 15 and the defendant is ≤ 5 years older	§ 14-27.30
Ohio	16	Minor ≥ 13 but < 16 and person is < 18	§ 2907.04
Oklahoma	16	Minor ≥ 14 but < 16 and person is < 18	§21-1112
Pennsylvania	16	Minor ≥ 13 but < 16 and defendant is < 4 years older	§§ 3122.1, 3125
Rhode Island	16	Minor ≥ 14 but < 16 and person is < 18	§§ 11-37-6
South Carolina	16	Minor ≥ 14 and person is ≤ 18	§ 16-3-655(B2, C)
Tennessee	18	Minor ≥ 13 but < 15 and defendant is < 4 years older	§§ 39-13-506(b1, b2)
Tennessee	18	Minor ≥ 15 but < 18 and defendant is ≤ 5 years older
Texas	17	Minor ≥ 14 and actor < 3 years older	§§ 22.011, 22.021
Utah	18	Minor ≥ 14 but < 16 and actor is ≤ 17	§ 76-5-401
Utah	18	Minor ≥ 16 but < 18 and person is < 7 years older	§ 76-5-401.2
Vermont	16	Minor ≥ 15 and person is < 19	§3252(c2)
Virginia	18	Minor ≥ 16 but ≤ 17 and person < 18	§§ 18.2-63, 18.2-371
Washington	16	Minor < 12 and person < 2 years older	§9A.44.073
		Minor ≥ 12 but < 14 and person < 3 years older	§ 9A.44.076
		Minor ≥ 14 but < 16 and person < 4 years older	§ 9A.44.079
West Virginia	16	Minor < 15 and defendant ≤ 15 years old and < 4 years older	§ 61-8B-5
West Virginia	16	Minor ≤ 11 and defendant ≤ 13 years old	§ 61-8B-7

Note. The following states do not currently have age differential laws but do maintain age of consent laws (see Table 1): California (§ 261. 5(b)-(d)), Delaware (§ 770), Georgia (§ 16-6-3), Idaho (§ 18-6101), Illinois (§ 5/11-1.60), Kansas (§§ 21-3503 & -3504), Massachusetts (§ 265 s 22A), Michigan (§§ 750.520(b)-(d)), Missouri (§§ 566.032, 566.034), Montana (§ 45-5-625), Nevada (§§ 200.366, 200.368), New York (§ 130.05, § 130.30), North Dakota (§ 12.1-20-03.1), Oregon (§§ 163.355, 163.435), Wisconsin (§§ 948.02, 948.025, 948.05), and Wyoming (§ 6-2-308).

Three important observations derive from these tables. First, all states and the District of Columbia have a minimum age of consent: 32 states at 16 years old, eight states at 17 years old, and 11 states at 18 years old (see Table 1). In addition, 34 states include an age-difference clause that allows individuals within certain age ranges to legally consent even if one or both parties are younger than the official age of consent (e.g., 16 years old; see Table 2). Second, age-difference laws are exceptionally varied across states. They differ in what age differences matter and whether there are additional caveats for the age-difference exceptions to apply to the alleged perpetrator (e.g., like being in high school). Third, these laws have changed over time.

Glosser et al. (2004), for example, produced a similar state-level table capturing age of consent laws in 2003. Since that time, two states (New Mexico and Wyoming) have increased their age of consent from 16 to 17 years. Now only 32 states set the age of consent at age 16 and eight states set age of consent at 17 (Table 1). In addition, consent exceptions (i.e., age-span laws) have become more complex often using multiple age ranges in a state’s criminal code for differing degrees of sexual assault severity (Table 2). For example, Arkansas now has different age spans for second-degree, third-degree, and fourth-degree sexual assault. As another example, Wyoming repealed their age-span exception in 2007. Overall, these changes imply that statutory rape laws have become both more nuanced, and also somewhat stricter, over time.

Given the complexity of these laws, as illustrated in Tables 1 and 2, cross jurisdictional or national research on this form of sex crime is exceptionally difficult to plan. The complexity also reflects, perhaps, the need for research to inform the crafting of these laws. That is, absent empirical data describing basic facts about statutory rape cases, it is difficult to know which age differences in fact distinguish statutory rape cases from one another. Absent a body of empirical research on which to ground law, legislation appears to develop with incredible variation across time and place.

Statutory Rape: Incident Characteristics

To date, there is no research that describes R&J crime characteristics, much less literature which compares them to statutory rape cases with larger age differences. However, there is a small pool of studies that address characteristics of statutory rape incidents in general. Although that literature is small, it does draw on a variety of kinds of data (e.g., official statistics as well as survey) and samples (e.g., criminal justice as well as health). As such, it is a useful starting point in building an empirical understanding of R&J cases.

Health data are particularly useful in this regard, providing descriptive information to the field and also revealing the importance of victim age and gender within statutory rape incidents. In a prominent example, Manlove and colleagues (2005) used the 2002 National Survey of Family Growth, a population-based self-report survey, to analyze sexual experiences of respondents aged 15 to 24 who had their first sexual experience at age 15 or younger with someone who was 3 or more years older (n = 2,059 males and 2,513 females). Their analysis showed that, compared with males, females were more likely to report first sexual intercourse at age 15 or younger with a partner that was 3 or more years older than themselves, typically a sexual partner around 18 to 20 years of age. A minority of the sample of males (13%) and females (14%) reported first sexual experience with someone who was 8 or more years older.Typically, the younger the respondent was at first sexual intercourse, the more likely that respondent was to have the first sexual experience with someone at least 3 years older (Manlove et al., 2005).

These age patterns are mirrored in other health data. For example, Lindberg, Sonenstein, Ku, and Martinez (1997) found that 40% of births to 15-year-old girls were due to sexual intercourse with partners 5 or more years older (see also, Leitenberg & Saltzman, 2003). In a separate study, an examination of birth certificates revealed that 11- to 12-year-old girls giving birth involved fathers on average 10 years older than the girls (Males & Chew, 1996).² Nearly identical statistics were found in a similar study 20 years earlier (Skolick & Woodworth, 1967). That is, as the age of the child declines, the age of offender tends to increase (Hines & Finkelhor, 2007). Finally, and perhaps related, health data reveal that compared with other sexually active females, young female respondents with older male sexual partners were more likely to report that the sexual encounter was involuntary or coercive (Manlove et al., 2005).

The importance of gender and age differences in statutory rape cases is observed in criminal justice data as well. The pattern of an older male perpetrator with an adolescent female victim appears in studies of prosecutions of statutory rape (Cohen, 2011) and police data (Troup-Leasure & Snyder, 2005). The latter study by Troup-Leasure and Snyder (2005) is particularly important as it is the largest descriptive analyses to date of statutory rape. They used the National Incident Based Reporting System (NIBRS; 1996-2000) which included more than 13,000 statutory rape sex crimes from 21 states reported to police. Similar to other studies, they found the majority of victims of statutory rape were female with male perpetrators. Regardless of victim gender, approximately 60% of the victims were 14 or 15 years old. Importantly, they found statutory rape was characterized by large age differentials. Female offenders were a median 9 years older than their male victims, while male offenders were a median 6 years older than their female victims. They also found important information with respect to relationship status. Approximately 30% of offenders were boyfriends or girlfriends and roughly 60% were acquaintances. A very small proportion (2%) were strangers known less than 24 hours. Within their sample, arrest rates were modest (42%) and declined as the victim’s age increased. However, they did not report whether arrest, or other aspects of incidents, varied as a function victim–offender age span.

Despite the importance of Troup-Leasure and Snyder’s (2005) work, it leaves several critical questions unanswered about statutory rape incident crime characteristics. The research bulletin, intentionally brief, did not test whether any descriptive differences were significant or include an analysis of what are now termed R&J scenarios. Most importantly, the analysis represents statutory rape incidents that are now more than 15 years old and predates important growth in the number of states and jurisdictions contributing to the NIBRS.

The Current Study

It is difficult to speak to policy debates or otherwise inform policy makers and treatment providers on statutory rape or R&J incidents because of the dearth in empirical research. First, there are relatively few studies which describe the victims, offenders, and contextual crime characteristics among incidents of statutory rape which come to the attention of police. Detailed descriptive information is needed to help policy makers find answers to a variety of practical questions; for example, they need to know what portion of statutory sex crimes reported to police are R&J scenarios to inform resource allocation and/or training. Descriptive information of police data can also speak to policy debates, such as those deriving from the assertion that these laws produce a national sex offender registry (hereafter, NSOR) that is saturated by R&J cases. Knowing whether R&J scenarios represent a majority or a fraction of statutory rape sex crimes reported to police may have important implications for debates on these kinds of national policies. In short, good policy, as well as theoretical work, is grounded in broad, detailed, and relevant descriptive data. The field needs to know how common these cases are, and their incident characteristics, to craft policy and advance scientific theory. The lack of these kinds of information and analyses represent an important limitation in the field today.

Because so little is known about the offenders, victims, and offense characteristics of statutory rape and R&J statutory rape cases, this study will focus on the following questions:

What proportion of statutory rape cases coming to police attention are R&J scenarios?

Do arrest patterns vary as a function of age differences between victims and offenders?

Are there important distinctions between these incidents as a function of the difference in ages between victims and offenders?

Method

This study used the NIBRS. The NIBRS is an incident-based reporting system maintained by the Federal Bureau of Investigation (FBI). It records information about crime incidents as reflected in police data systems from across the United States, including details about offenses, victims, and offenders. Because one of the goals of the NIBRS is to improve the quantity and quality of the crime data, these data are thoroughly audited by the FBI. The data are then made publicly available annually via the Inter-University Consortium for Political and Social Research (ICPSR; for other analyses using the NIBRS, see, for example, Budd, Bierie, & Williams, 2017; Williams & Bierie, 2015). This system was first launched in 1991 and has grown in the number of agencies contributing to it since that time. By 2013, the most recent year data were available when the study began, more than 6,000 law enforcement agencies across 37 states and the District of Columbia were submitting crime data to NIBRS. This study used all years which were available to the public at the time the study began (1991-2013).

In total, the NIBRS contained approximately 1.1 million sex crimes reported to police. However, this study only used an incident if there was at least one statutory rape crime reported in the incident (n = 73,561). We removed incidents in which a statutory sex crime occurred but (a) the victim was over 18 (n = 5,023), (b) the victim was older or equal in age to the offender (n = 3,434), and (c) incidents where victim or offender age was not recorded or had nonsensical values (n = 4,740). The final data set consisted of 60,364 incidents of statutory rape.

Variables

The analysis included the following victim characteristics: number of victims of a crime (approximately 10% of incidents had two or more victims, range 1-10), age (range 5-17), gender, race, victim–offender relationship, and whether the sexual assault was heterosexual in nature. Victim gender was represented by three mutually exclusive binary variables: male, female, or both genders present if there was more than one victim in the incident. Similarly, a series of mutually exclusive race variables were created to indicate victim race: Black, White, Hispanic, and Other. There were too few Asian and Native American youth to allow separate analyses of these race groups so they were collapsed for analyses.³ The NIBRS contains 25 possible victim–offender relationships. These were aggregated into four binary categories: positions of trust (e.g., victim was a stepchild, employee, neighbor, etc.), acquaintance (e.g., victim was a friend, acquaintance, or otherwise known), romantic partner (e.g., boyfriend/girlfriend), and stranger (unknown or known less than 24 hr). A binary item was also coded to indicate whether more than one relationship type was present (e.g., if the victim and offender were in a romantic relationship and a position of trust). We also assessed whether incidents of statutory rape were heterosexual, based either on (a) the “homosexual relationship” category being flagged, or (b) the offender and victim gender being the same.

The analysis included the following offender characteristics: age (range 10-89), gender, and race. These were coded the same as similarly named items for victim data described above, but with one exception. Unlike the victim-race variable, the NIBRS groups Hispanic and White offenders under the category of White. This error cannot be corrected in the underlying files.

The analysis included the following binary crime characteristics: an additional crime (any type), a forcible sex crime, if there was computer involvement (e.g., production of child pornography), pimping or prostitution was present, and there was drug or alcohol use. The count of additional crimes was also computed (mean 1.11, range 1-8) as well as the count of offenders (10% had multiple offenders, range 1-20). The NIBRS records more than 40 incident locations. Because of small cell counts in many of the categories, these locations were collapsed into seven binary and mutually exclusive variables. Location groupings were selected based on similarity in the areas with respect to their likely age-graded appeal or convenience for sexual encounters. These locations included car, home, hotel, service area (e.g., hospital, school, church), outdoor area (e.g., woods, parks, playground, abandoned building, rest stop, construction site), and business (e.g., bar, restaurant, store, mall, gas station). If the incident took place at more than one location, this was coded as “location moved” (0/1). Using the victim-age and offender-age items described above, difference in age was computed (mean 9.83 years, range 1-78 years).

Finally, because no common R&J definition exists across states, we coded several options. Our primary and simplest binary item was coded 1 if the incident involved a statutory rape case in which the difference in age between the victim and offender was less than 4 years and 0 otherwise. This definition captures the most common defining feature of statutory rape across the nation (see Table 2; also Glosser et al., 2004). However, legal reviews and the press have tended to emphasize cases in which victim and offender operated in similar social situations (e.g., the same high school) and are relatively closer in developmental stage. In short, a 4 year age difference may represent an exceptional cognitive and social distance when comparing a 14-year-old offender and a 10-year-old victim. However, a 4 year difference is relatively smaller, developmentally, when comparing a 17-year-old victim and a 21-year-old offender.⁴ Given these developmental concerns and the legal discourse on the concept of statutory rape, we created a second item which restricts R&J cases to those in which the age difference was less than 4 years and the victim was aged 15 or above. Finally, we created an even more restrictive definition of R&J that gets, unambiguously, to the heart of the debate: a victim who is a minor and an offender who was either 1 or 2 years older. To summarize, the three forms of R&J were coded as follows: (a) an age difference of less than 4 years; (b) an age difference of less than 4 years and the victim was 15 years old or older; and (c) an age difference of no more than 2 years and the victim was under 18. Victim, offender, and crime characteristics of incidents are described in Table 3.

Table 3.

Descriptive Statistics of Incidents of Statutory Rape (N = 60,364).

	M or percent	SD
Crime
R&J category
Less than 4 year age difference	16%
Less than 4 year age difference and victim 15-17 years old	9%
Less than 2 year age difference	6%
Arrest	38%
Age difference (years)	9.83	9.25
Heterosexual	99%
Any additional crime	4%
Any forcible sex crime	1%
Pimping/prostitution	0.1%
Computer involvement	1%
Substance use	7%
Single offender/victim incidents	84%
Count of additional crimes	1.11	0.36
Location
Business	1%
Car	5%
Home	76%
Hotel	3%
Location moves	0.3%
Outdoors	3%
Service area	3%
Offender
Count of offenders	1.17	0.54
Age (years)	23.74	8.96
Female	5%
Race
Black	24%
White or Hispanic	74%
Other	1%
Victim–offender relationship
Romantic partner	29%
Acquaintance	60%
Position of trust	12%
Stranger	2%
Multiple relations	3%
Victim
Count of victims	1.13	0.41
Age (years)	13.91	2.08
Female	95%
Race
Black	19%
Hispanic	9%
Other	1%
White	71%

Note. The victim–offender relationship category is greater than 100% in the descriptive tables due to the multiple relationship category.

Table 3 displays mean and standard deviation (SD) for all continuous items, and a percentage for all binary items. The table shows, for example, that the average offender was nearly 10 years older than the average victim in statutory rape cases reported to police (median difference of 6). Specifically, offenders were on average nearly 24 years old and victims were just under 14 years of age.

Analytic Strategy

The analysis proceeded through four steps. First, the data were described with respect to the four categories of statutory rape (i.e., the three definitions of R&J, and a final category for incidents with larger age differences; see Tables 3 and 4). The primary goal here was to address the first research question regarding the prevalence of each type of statutory rape reported to police. A secondary goal was to offer a breadth of information about the underlying incident characteristics of these different types of statutory rape. That is, the field currently has very little descriptive information on which to ground future scholarship. The descriptive tables are intended to help correct this limitation.

Table 4.

Descriptive Statistics of Incidents of Statutory Rape by Victim–Offender Age Span.

	Less than 2 years		Less than 4 years and victim 15-17 years		Less than 4 years		Greater than 4 years
	M or percent	SD	M or percent	SD	M or percent	SD	M or percent	SD
Crime
Arrest	23%		29%		30%		40%
Age difference (years)	1.97	0.12	3.00	0.13	3.01	0.17	11.23	9.50
Heterosexual	99%		99%		99%		99%
Any additional crime	3%		4%		4%		4%
Any forcible sex crime	1%		1%		1%		1%
Pimping/prostitution	0%		0%		0.1%		0.2%
Computer involvement	1%		1%		1%		1%
Substance use	5%		7%		5%		7%
Single offender/victim incidents	85%		84%		78%		84%
Count of additional crimes	1.09	0.36	1.09	0.33	1.11	0.34	1.12	0.37
Location
Business	1%		1%		1%		1%
Car	5%		6%		5%		5%
Home	71%		74%		73%		77%
Hotel	2%		2%		2%		3%
Location moves	0.3%		0.4%		0%		0%
Outdoors	4%		3%		4%		3%
Service area	8%		4%		6%		3%
Offender
Count of offenders	1.20	0.68	1.19	0.62	1.28	0.81	1.16	0.50
Age (years)	16.39	1.46	18.30	0.58	16.31	1.15	25.06	9.22
Female	4%		4%		2%		5%
Race
Black	25%		18%		31%		24%
White or Hispanic	73%		80%		67%		74%
Other	1%		2%		1%		1%
Victim–offender relationship
Romantic partner	46%		52%		33%		26%
Acquaintance	51%		47%		62%		61%
Position of trust	5%		2%		6%		13%
Stranger	1%		1%		2%		2%
Multiple relations	3%		4%		3%		3%
Victim
Count of victims	1.09	0.37	1.11	0.42	1.15	0.43	1.13	0.42
Age (years)	14.41	1.45	15.29	0.57	13.30	1.13	13.83	2.18
Female	96%		95%		97%		95%
Race
Black	19%		14%		25%		20%
Hispanic	9%		8%		9%		9%
Other	1%		2%		1%		1%
White	71%		77%		66%		70%
n	3,502		3,263		3,096		50,503

Second, we estimated two multivariate regression models: a pooled negative binomial model and a fixed-effects negative binomial model. The age difference between victim and offender was the dependent variable in all models. These multivariate regressions were estimated within a negative binomial regression framework because the outcome was a count distribution (years of age difference) that was truncated at zero with long right tail and a mean unequal to variance (see Long & Freese, 2006, for more detail).

We estimated both pooled and fixed-effects models (i.e., fixed on states) because both models had strengths and weaknesses which complimented one another in the context of these research questions. The pooled multivariate regression model estimated incident-level coefficients simultaneously. This model showed the impact of each independent variable, all else in the model constant, averaged across the data set as a whole. Although this gave a useful view of the patterns in these data, it also had potential limitations deriving from the fact that cases were not evenly dispersed across states. Specifically, pooling data across states could lead to deflated standard errors and also bias in coefficient estimates through contextual contamination (Iverson, 1991).

The fixed-effects model corrected for these potential errors. The fixed-effects model was similar to the pooled multivariate regression in that the same covariates were entered into the equation and the regression and results were interpreted similarly. However, all incident-level coefficients were estimated within-states themselves then aggregated into the final coefficients presented in the table. This within-state estimation excluded the potential of deflated standard errors, contextual contamination, or any state-level omitted variable bias. Although the fixed-effects models were the most accurate for generating incident-level estimates, they also had costs. They required a significantly greater number of degrees of freedom and likely lacked power to estimate coefficients for items which had small cell counts within the states themselves. Both pooled and fixed-effects regression models, then, had strengths and limitations. We presented both models to create a more complete picture of the patterns in these data.

Third, we replicated the above pooled and fixed-effects models after restricting the data to incidents with a single victim and single offender. Because ages were averaged if more than one victim and/or more than one offender was reported in the incident, some error in age-difference computations could have emerged. Therefore, for each model (pooled and fixed), we ran two variations of the model: (a) Model 1 with all incidents included and (b) Model 2 with only incidents that had one victim and one offender. Within this data, 90% of the multiple-offender incidents had offenders who were within 2 years of age of one another. This age pattern was also found in incidents with multiple victims. While overall this implies the potential error in age computations was probably small (i.e., a small error within 10% of cases), we presented the results of each variation of the models because of the potential importance even minor differences in age may have on the results.

Fourth, we presented key findings after converting to a more easily interpreted metric showing the magnitude of effects. Because the analyses were based on an exceptionally large sample of cases, small differences had the power to be statistically significant. That does not mean, however, that all statistically significant coefficients were substantively meaningful. Thus, to better illustrate the magnitude of key relationships, we generated marginal effects for coefficients estimated within the models. Marginal effects refer to the predicted value of the outcome (i.e., number of years of age difference) derived from the multivariate model when all coefficients in that model were held at their mean value except one key independent variable of interest. The prediction was estimated once with the key variable assumed at its highest value with all other variables held at their mean and then once again with that variable at its lowest value with all other variables held at their mean. Jointly, these two estimates gave a unique perspective on the magnitude of impact associated with that key item. They showed the change in outcome associated with that variable (a) in an interpretable metric (i.e., count of years) and (b) for individuals who are otherwise statistically identical with respect to all measured covariates except for change in that key variable (see Long & Freese, 2006, for more detail).

Results

The first research question focused on the prevalence of R&J incidents coming to the attention of police (see Tables 3 and 4). Only 5%, or 60,362, of the 1.1 million sex crimes reported to police in the NIBRS included statutory rape. Of those 60,362 statutory rape incidents, 16.3% (n = 9,861) met the broadest definition of R&J, that is, less than a 4 year age difference between the victim and the offender. Just over one half of those 9,861 involved incidents in which the victim was aged 15 or older (n = 5,517). As expected, the most restrictive definition was the most rare with 5.8% of statutory rape incidents involving an offender who was no more than 2 years older than the victim (n = 3,502). R&J sex crime incidents represented only a fraction of the 1.1 million sex crime cases reported to the police from 1991 to 2013—less than one half of 1%.

Similar findings emerge when restricting analyses to incidents which included an arrest. Approximately 26% of all sex crimes reported to the NIBRS resulted in an arrest (see Williams & Bierie, 2015). Overall, arrest was substantially higher among statutory rape incidents (38%). These findings are similar to other work examining closure rates among sex crimes in NIBRS (Chaffin, Chenoweth, & Letourneau, 2016; Troup-Leasure & Snyder, 2005). The higher arrest rate is likely a function of the definition of statutory rape itself: the charge generally cannot be reported to police unless an offender’s age, and therefore identify, is already known. In contrast, some of the other sex crimes in the NIBRS, such as rape, involved unknown offenders.

While statutory rape had a higher clearance rate than sex crimes in general, the pattern varied across victim–offender age differences. Incidents involving more than 4 years age difference resulted in an arrest in 40% of cases. The broadest definition of R&J (less than 4 years age difference) resulted in arrest in 30% of incidents, the second broadest (less than 4 year age differences and victim was 15 years or older) resulted in arrest 28% of the time, and the most restrictive definition (2 years or fewer difference in age) resulted in an arrest in only 23% of cases (i.e., 805 incidents over the entire 20 year period of NIBRS). This decline may imply that law enforcement is attuned to age differences when making decisions about arrests in these cases.

The third research question focused on comparisons of incidents as a function of the difference in age between victims and offenders. As a first step toward addressing this question, Table 4 described offense, offender, and victim information for each R&J categorization.⁵ There were several similarities between definitions. Regardless of definition, most incidents involved male offenders, female victims, and occurred in homes. As might be expected from the definition of R&J, offender age varied significantly as a function of R&J categorizations. Offenders in statutory rape cases without an R&J implication (i.e., greater than 4 years age difference) were 25 years old on average, while the average age of R&J offenders was 16 to 18 years old (depending on the definition of R&J). An important pattern was that victim age decreased as the age of offenders increased. For example, statutory rape cases with a 2-year age difference had victims an average of 1 year older than cases involving an age difference of 4 or more years.

The data in Table 4 are important for building a descriptive context for understanding the distributions of variables entering later multivariate analyses. However, they should be interpreted with caution because they are bivariate comparisons. Any specific similarity or difference could be caused by omitted variable bias. Thus, statistical comparisons of age differences were computed within a multivariate framework below.

Table 5 provides pooled multivariate estimates for prediction of age differences.⁶ Model 1 includes all incidents regardless of the number of victims or offenders. Model 2 then repeats the analysis after restricting the data to incidents which had a single offender and single victim. The analysis showed that differences in age between victims and offenders correspond to numerous statistically and substantively significant differences in incident characteristics. Further, these differences were consistent between models.

Table 5.

Age Differences Between Victims and Offenders: Multivariate Pooled Negative Binomial Regression.

	Model 1 (n = 52,487)All incidents			Model 2 (n = 47,742)Incidents with only one victim and one offender
	Coefficient	SE	p > z	Coefficient	SE	p > z
Any forcible sex crime	0.17	0.03	.000	0.25	0.18	.172
Pimping/prostitution	0.29	0.08	.000	−0.18	0.52	.723
Computer involvement	0.28	0.04	.000	n/a	n/a	n/a
Substance use	0.03	0.01	.038	0.03	0.01	.021
Single offender/victim incidents	0.02	0.01	.024	n/a	n/a	n/a
Location
Business	0.15	0.03	.000	0.16	0.03	.000
Car	−0.04	0.01	.004	−0.03	0.02	.067
Hotel	0.16	0.02	.000	0.18	0.02	.000
Location moves	−0.04	0.06	.471	n/a	n/a	n/a
Outdoors	−0.16	0.02	.000	−0.14	0.02	.000
Service area	0.001	0.02	.934	0.01	0.02	.740
Offender
Female	−0.03	0.07	.620	−0.02	0.12	0.883
Race, Black	−0.08	0.01	.000	−0.08	0.01	0.000
Victim–offender relationship
Acquaintance	0.43	0.01	.000	0.46	0.01	.000
Position of trust	1.00	0.01	.000	1.04	0.01	.000
Stranger	0.68	0.02	.000	0.77	0.03	.000
Multiple relations	−0.37	0.02	.000	n/a	n/a	n/a
Victim
Age (years)	−0.05	0.001	.000	−0.04	0.002	.000
Female	−0.18	0.06	.004	−0.16	0.12	.169
Race
Black	0.03	0.01	.020	0.03	0.01	.005
Hispanic	−0.03	0.01	.005	−0.02	0.01	.199
Other	−0.06	0.03	.048	−0.02	0.03	.602
Constant	2.63	0.07	.000	2.57	0.12	.000
/lnalpha	−0.96	0.01		−0.99	0.01
Alpha	0.38	0.003		0.37	0.00

Note. Reference categories are as follows: offender = White or Other; victim = White; location = home; victim–offender relationship = romantic partner.

As differences in ages between victims and offenders became larger, the odds of a statutory rape incident also involving a forcible sex crime, pimping/prostitution, or computer involvement increased (p < .001). Likewise, the odds of substance abuse in the incident increased as the age difference expanded (p < .04).

Although these sexual assaults were most likely to occur at a home for all age-difference categorizations (see Table 4), the location of the statutory rape varied significantly as a function of offender–victim age differences. The odds that the incident occurred at a business or hotel increased as the age difference increased between the victim and offender (p < .001). Conversely, as age differences declined, the odds increased that the incident occurred in an outdoor area such as the woods, waterway, or camp grounds (p < .001).

The victim–offender relationships also varied significantly as a function of age differences. As age differences expanded, victim–offender relationships were more likely to change from a romantic partner to an acquaintance (p < .001), stranger (p < .001), and especially relationships that involved a position of trust (p < .001). Finally, interesting patterns emerged with respect to victim characteristics. As the age differences between the offender and victim grew larger, the age of victims significantly decreased (p < .001). Larger age differences were also associated with a significant decline in the odds the victim was female or Hispanic (p < .01, all incidents). The only items which did not vary as a function of age differences were offender gender, use of a car, and the presence of multiple victims or offenders.

Table 6 shows the results of the fixed-effects framework using within-state comparisons. As noted above, this is important because states vary in their populations of offenders as well as laws and criminal justice system processes which may in turn lead to error in coefficient estimates or standard errors in pooled regression (i.e., contextual contamination). Table 5 includes two models: Model 1 analyzing all incidents and Model 2 analyzing incidents with a single victim and single offender. There were similar results between the fixed-effects and pooled regression model in terms of significance tests and direction of coefficients. Only one substantive change occurred between the models: There is a change in significance for the items that capture “additional types of sex crimes.” Model 2 of Table 5 shows that the odds of a statutory rape incident also involving a forcible sexual assault, pimping, or computer involvement were no longer statistically significant. This change may indicate that the reason these additional forms of risk or victimization are associated with increasing age differences (Table 5, Model 1) is that incidents with egregious age differences (a) occur in states which have higher odds of these additional crimes in general, and (b) are pronounced in cases that have more offenders or victims present.⁷ However, the change may also be an artifact of computational instability in this final model. That is, despite the large sample size of the model (N = 47,732), the rarity of these additional forms of victimization still imply a potential decline in power and stability for that item in these models which are taxing on degrees of freedom. For example, the data set only included 83 cases of pimping or prostitution. When spread between 37 states, and limited to the cases in which there was only one victim and offender, the data are likely too thin to interpret for that coefficient within Table 5 Model 2.

Table 6.

Age Differences Between Victims and Offenders: Multivariate Fixed-Effects Negative Binomial Regression.

	Model 1 (n = 52,487)All incidents			Model 2 (n = 47,732)Incidents with only one victim and one offender
	Coefficient	SE	p > z	Coefficient	SE	p > z
Crime
Any forcible sex crime	0.14	0.03	.000	0.28	0.18	.124
Pimping/prostitution	0.27	0.08	.000	−0.37	0.51	.470
Computer involvement	0.25	0.04	.000	n/a	n/a	n/a
Substance use	0.03	0.01	.004	0.04	0.01	.002
Single offender/victim incidents	0.02	0.01	.089	n/a	n/a	n/a
Location
Business	0.13	0.03	.000	0.14	0.03	.000
Car	−0.05	0.01	.001	−0.03	0.02	.022
Hotel	0.16	0.02	.000	0.18	0.02	.000
Location moves	−0.02	0.06	.740	n/a	n/a	n/a
Outdoors	−0.14	0.02	.000	−0.12	0.02	.000
Service area	−0.01	0.02	.541	−0.01	0.02	.716
Offender
Female	−0.05	0.06	.476	−0.07	0.11	.567
Race, Black	−0.07	0.01	.000	−0.06	0.01	.000
Victim–offender relationship
Acquaintance	0.41	0.01	.000	0.43	0.01	.000
Position of trust	0.97	0.01	.000	1.01	0.01	.000
Stranger	0.63	0.02	.000	0.72	0.03	.000
Multiple relations	−0.32	0.02	.000	n/a	n/a	n/a
Victim
Age (years)	−0.04	0.00	.000	−0.04	0.002	.000
Female	−0.18	0.06	.005	−0.19	0.11	.092
Race
Black	0.05	0.01	.000	0.06	0.01	.000
Hispanic	0.00	0.01	.974	0.01	0.01	.235
Other	−0.03	0.03	.362	0.03	0.03	.381
Constant	2.55	0.25	.000	2.75	0.22	.000
/lnalpha	−1.02	0.01		−1.05	0.01
alpha	0.36	0.003		0.35	0.003

Note. Reference categories are as follows: offender = White or Other; victim = White; location = home; victim–offender relationship = romantic partner.

Finally, it is helpful to note the magnitude of these relationships. To that end, marginal effects were generated for the additional-harm items. First, the impact of substance abuse was assessed by holding all other items in the model at their mean, then estimating the predicted value of “age-difference” with and without substance use being present. This showed that the presence of controlled substances in the incident was associated with a 1-year increase in age difference (above the mean of 9 years). In contrast, repeating the exercise with the item “forcible sexual assault” indicated incidents with a forcible sex crime present in addition to statutory rape had an average of 7 additional years in age difference above the mean.

Discussion

Statutory rape, and R&J in particular, is an important but understudied topic. Debates on the crafting of sex crime law or policy, such as sex offender registration, are deeply tied to assumptions regarding the prevalence of R&J cases in the criminal justice system, as well as presumed distinctions in the nature of crimes as a function of age differences between victim and offender. Despite the importance of these topics, there is very little empirical work to date on statutory rape and almost none on R&J cases specifically. This research attempts to address these gaps in the literature by drawing on more than 20 years of policing data as represented in the NIBRS. This data set has several strengths for these specific questions. By examining crimes reported to police, the study avoids selection bias in statutory rape cases which may otherwise occur as cases are filtered into and through the adjudication process. The analysis benefits from using thousands of police jurisdictions across the United States. This increases the relevance of findings to large portions of the nation and also maximizes variation in case characteristics and potential explanatory variables.

The results of these analyses were often consistent with prior research on statutory rape, such as females being the majority of the victims and males being the majority of the offenders. They also showed, again consistent with prior research, that the majority were described as sexual liaisons between acquaintances (60%), around 30% of statutory rape cases were characterized by a “romantic” relationship, and approximately 2% of relationships involved “strangers” (see, for example, Troup-Leasure & Snyder, 2005). Unlike prior research, we distinguished relationships based on positions of trust (e.g., employer, babysitter, or stepparent). These were present in nearly 12% of the incidents. Future research may benefit from further investigating this relationship type in the context of statutory rape.

Ultimately, this research sheds new light on aspects of statutory rape that have not been explored before. We found that in more than 20 years of data, statutory rape was rarely reported to the police and that R&J incidents that came to the attention of courts (i.e., resulted in an arrest) were even more rare. Despite anecdotal evidence of consenting teenagers who are close in age being adjudicated as sexual offenders, the data indicate that the criminal justice system is not saturated with R&J cases specifically nor statutory rape in general because, simply, they only represent a fraction of sexual assault incidents coming to the attention of the police. Fewer than 5% of sex crimes reported to the NIBRS involved statutory rape and most of those that do come to law enforcement involve egregious age differences. For example, 84% of statutory rape incidents had a 4 or more year age difference and 50% had a 6 or more year age difference. The average offender was age 23.7 years old and the average victim age was 13.9 years old. These represent age spans for which the public supports criminal justice involvement (see, for example, Koon-Magnin & Ruback, 2013; Sahl & Keene, 2012). We posit this is an age difference few would argue represents an overreach or unintended net widening by law enforcement.

Second, some scholars have expressed concern that broad definitions embodied in statutory rape laws allow or encourage an unintended expansion of the criminal justice system into the lives of teenagers engaging in relatively normative sexual behavior. However, our results do not support that assertion. For example, the U.S. Census shows approximately 25 million youth aged 12 to 17 in 2013, and national statistics described above estimate half will have had sexual intercourse (Kann et al., 2014). National statistics also indicate half of these encounters involved age differences of 3 or more years and 90% will have been deemed consensual by the youth (Martinez et al., 2011). That is, there were approximately 5 to 6 million statutory rape eligible encounters in 2013. Presumably, 34% would have occurred in jurisdictions covered by NIBRS (i.e., around 2 million), and the majority of these would have been R&J scenarios (Manlove et al., 2005). Yet, in these data, only 643 incidents of statutory rape involving 4 or fewer year’s difference in age were reported to police in 2013 (of which 170 resulted in an arrest). Even if we assume national estimates of the prevalence of sexual encounters qualifying as R&J were half what current research indicates, the conclusion would remain the same: Police do not appear to be a pervasive presence in the sexual lives of teenagers engaging in R&J scenarios.

Third, anecdotes and news coverage, as described above, make clear that some R&J encounters have led to sex offender registration. Some legal scholars posit that the relatively common occurrence of teenagers engaged in sexual relationships with slightly older partners, as well as broad definitions of statutory rape, has potentially saturated sex offender registries with R&J cases (see, for example, James, 2009). This, in turn, could call into question the very legitimacy of the registry itself. This premise, however, is not supported by the NIBRS data. For example, over the 20 year time period of these data, there were only 805 cases of an arrest occurring in an incident of statutory rape which involved an offender and victim within an age difference of 2 years, and 2,648 for the broadest R&J definition (4 or fewer years in age difference). There are currently 670,000 registrants on the national sex offender registry and presumably one third, or approximately 225,000, overlap with the NIBRS jurisdictions. Even if one assumes that every R&J case that involved an arrest resulted in a conviction and requirement to register, an unlikely scenario, R&J cases would still account for a fraction of a percent of the registry. In reality, R&J incidents probably represent even less than this given that a sizable portion of sex crimes entering courts result in no conviction or are pled down to a non-sex crime charge which does not carry a registration requirement (Letourneau, Armstrong, Bandyopadhyay, & Sinha, 2013).

Fourth, this research offers evidence that the age difference between victims and offenders is important. The way incidents emerge, and the level of risk to victims, appears to be significantly associated with the difference in ages between victims and offenders. As the age difference expands, the chances that substances such as alcohol or drugs are involved in the incident increases. Perhaps more alarming, the odds that the victim will also experience a forcible sexual assault, prostitution, or computer involvement—presumably child pornography production—grows as the age difference between offender and victim increase. In analyses not shown (but available upon request), an item measuring the presence of “any additional crime” was substituted for these three specific forms of risk here (i.e., forcible sex crime, computer, and prostitution). The patterns for all items in Table 6 Model 2 were substantively identical, except that the new global “additional crime” item was positive and significant (p < .001). That is to say, the findings imply that age differences are associated with risk to youth engaged in ostensibly consensual relationships. It should be noted that this does not mean that these additional indicators of harm were often present even in cases of egregious age difference. They were not. However, the relative risk did increase and this is probably an important indicator of an underlying or latent difference in incidents.

Fifth, regardless of model specification, the results were similar. The models varied little as a function of the inclusion of cases with multiple victims or offenders versus one victim with a solo offender. In addition, few differences emerged as a function of state-level contamination. This implies, perhaps, that although laws vary significantly between states, crimes are reported to police and processed in fairly similar ways across the nation.

While this research expands our understanding of statutory rape and R&J cases, it has limitations. While the NIBRS is the largest data set in the nation which tracks police records and includes basic information about cases such as offender and victim age, it is not representative of the nation as a whole. Further, it relies on thousands of individuals across more than 6,000 police departments to enter data into the system. Although all users receive uniform training and records are audited, there may be clerical errors or differences in data entry as a function of local policy or resources. In addition, it does not include several variables that would likely have been important in these models. For example, the NIBRS does not include criminal histories of offenders. It is likely that our understanding of arrest decisions, and perhaps risk within the incidents themselves, would have been greatly enhanced by having this information. Likewise, the NIBRS does not contain unique identifiers for offenders. Therefore, the same offender could have been present in many different rows of data (for a discussion, see Bierie, 2015). It also does not include ethnicity data for offenders, because the NIBRS groups together Hispanic and White offenders.

Despite these limitations, these analyses offer new and useful information for policy makers as well as academia. Prevalence and incident characteristics can help criminal justice entities design better proactive strategies to identify and prevent statutory rape crimes, including those that fall in the purview of R&J cases. These analyses suggest policy makers should be hesitant to craft law based on the assumption that R&J cases comprise a large portion of sex crimes, or even statutory rape crimes, entering the criminal justice system. In addition, this research may help treatment providers understand prevalence as well as offender, victim, and crime characteristics which, in turn, help them plan for future clients and to know in what way clients they treat are (dis)similar in offending patterns from other types of individuals who commit statutory rape. And, finally, the breadth of these data in terms of geography, time, and items measured give rise to new puzzles for academics. They challenge the field to engage replications and extensions of these findings to better understand why harms such as forcible sexual assault grow as the age difference between victim and offender increase. They also challenge the field to develop a better understanding of the way sexual assault behavior and tactics change as age differences expand and also the meaning behind those changes.

Future research may benefit from building on these analyses in three ways. First, national debate on sex offender registration and the existence of R&J cases may benefit from a more direct investigation of the registry itself. Data exist which details every registrant, their criminal charges, and other basic information which could inform this debate. Second, it is important to understand why R&J cases sometimes do invoke law enforcement attention. Although the above discussion has focused on the relative rarity of these kinds of charges, that should not detract from the observation that there are R&J cases which have come (formally) to the police and courts. Again, anecdotes as described above tend to suggest these represent unintended, or even tragic, miscarriages of justice. Yet, we know very little about these cases. How many, for example, invoked police attention because the offender had prior arrests for forcible sexual crime? How many involved other kinds of exploitation not covered in these data, such as victims who were close in age but developmentally disabled? Or, how many R&J cases come to police attention for extra-legal and nefarious reasons such as stigma or disdain regarding sexual orientation, interracial relationships, or other forms of bias? Perhaps related, it may be useful to explore the meaning of relationship status. Dating was relatively rare in these data (30%). Is it possible that law enforcement views statutory rape as more deviant when it involves some kinds of relationships (e.g., sex between acquaintances or strangers)? Do youth and law enforcement use the same words, and have the same meaning, attached to relationship statuses underlying these encounters? These are important questions to explore to continue to increase our knowledge about statutory rape and also as a way to explore discretion within the justice system in general. Statutory rape remains a critical topic to governance and the public. Building a greater understanding of these offenses and criminal justice responses is likely to build important advances for academic theory, treatment, policy, and the justice system as a whole.

Footnotes

Acknowledgements

We would like to thank Paul J. Detar for offering comments and ideas on this article, and to thank Elizabeth Ulan and Katelyn Sheffield for research assistance. The views and opinions within this article do not necessarily reflect those of the U.S. Department of Justice nor the United States Marshals Service.

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.

Notes

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