Hate Crimes and Youth

At the federal level, hate crimes are defined as crimes motivated by bias against others because of their actual or perceived race, ethnicity, sexual orientation, gender, gender identity, religion, or disability. To be considered a hate crime, two elements must be present: 1) the act is an offense under criminal law, and 2) the act was motivated by bias (USDOJ, n.d.f). Two examples of hate crimes are assaulting someone because of their race and defacing someone’s property with graffiti because of their religion. Hate crimes are often not about the specific victim, but rather their membership in a particular group (Steinberg, Brooks, and Remtulla, 2003). While there is an established federal definition of hate crimes, definitions at the state levels can differ greatly on which groups are protected, the offenses involved, and the statute type (Nolan et al., 2015). For example, bias motivation categories may change by state, where one state can include sexual orientation bias in its hate crime statute and another state may not. According to the Department of Justice, only two states (South Carolina and Wyoming) do not have state laws that protect against crimes motivated by at least one of the federally protected bias categories including race, color, national origin, religion, sexual orientation, gender/sex, gender identity, or disability (USDOJ, n.d.d). While all states and territories that have hate crime statutes address crimes committed based on an individual’s race, ethnicity, and religion, there is considerable variation across states regarding additional protected categories such as disability, sex or gender, sexual orientation, gender identity, and age. State hate crime laws create enhanced penalties for perpetration, by either using a distinct hate crime statute to create a new, independent crime, or by using general sentencing statutes to identify what characteristics (such as bias motivation) of a crime may justify enhanced sentencing (Movement Enhancement Project, 2021). Further, some but not all jurisdictions require collecting data on hate crimes (USDOJ, n.d.d).

When an incident is motivated because of another person’s race, ethnicity, sexual orientation, gender, gender identity, religion, or disability but falls below the criminal threshold (that is, no criminal act occurred), these acts are referred to as bias incidents (or, sometimes, hate incidents) [USDOJ, n.d.f; Schweppe, 2021]. Examples of bias incidents are name calling and derogatory slurs. Thus, although hate crimes and bias incidents are both motivated by bias, they differ in that hate crimes include a criminal act or acts, whereas bias incidents do not. For example, hate speech—defined as words or symbols promoting and inciting hatred, discrimination, or violence against a protected group (Kilvington, 2021; GAO, 2021)—is considered a biased incident rather than a hate crime because, technically, no criminal act has occurred. However, a targeted, direct threat against a specific individual is not protected speech under the First Amendment, and the perpetrator could face criminal consequences.[²] Although bias incidents—whether occurring in person or online—fail to meet the criminal threshold to be considered a hate crime, these incidents can influence hate crime.

When hate speech is conveyed through online platforms, it is called cyberhate. Cyberhate can present in the form of advocacy of terrorism or violence, harassment, exclusion, and hatred of social groups based on certain characteristics, such as race, religious orientation, or sexual orientation (Douglas et al., 2005; Wachs, Wright, and Vazsonyi, 2019). Youths may engage in cyberhate through acts such as posting hateful speech online (Wachs, Wright, and Vazsonyi, 2019).

Another related concept to hate crimes and bias incidents that youth may experience (through perpetration or victimization) is called identity-based bullying (IBB). This is a form of bullying that occurs because of a youth’s actual or perceived social identity or identities and involves physical or verbal assaults or harassment based on discrimination or prejudice (Price et al., 2019; Russell et al., 2012). Two examples of IBB are racist name calling and pushing another student because of their actual (or perceived) sexual orientation. A study by Galán and colleagues (2021) of almost 4,000 students in Pittsburgh, Pa., found that nearly 40 percent of students reported experiencing IBB in the past 12 months. An incident of IBB can be considered a hate crime when the incident becomes criminal. For example, a student using a racist slur against another student based on their actual or perceived race would be an example of IBB that is a bias incident, as no crime has been committed. However, if a student assaults another student based on their actual or perceived race, that could be considered a hate crime, for an actual crime (the assault) has been committed with the addition of a bias motivation.

Another aspect related to hate crimes is hate groups. The Southern Poverty Law Center defines a hate group as an organization or collection of individuals that has beliefs or practices that attack or vilify an entire class of people, usually for characteristics the members have no control over, including race, religion, ethnicity, sexual orientation, and gender identity. These groups do not necessarily have to engage in criminal conduct to be considered a hate group. Examples of whom the Southern Poverty Law Center consider to be hate groups are the Proud Boys, the Ku Klux Klan, and Aryan Nations (Southern Poverty Law Center, n.d.). To recruit individuals, hate groups may use hate sites and hate materials (Hawdon, Oksanen, and Räsänen, 2014). (For more on recruitment, see the Recruitment of Youth to Hate Groups section below.) A hate site is defined as a website that contains any form of hateful, textual, visual, or audio-based rhetoric (Cohen–Almagor, 2018:40). Hate materials may include artwork, photos, music, and online games (Hawdon, Oksanen, and Räsänen, 2014).

There are five important federal legislations that govern the enforcement of hate crimes. One of the earliest pieces of legislation was passed in 1948 called the Conspiracy Against Rights Act, which made it unlawful for two or more people to conspire to injure, threaten, or intimidate a person in free exercise or enjoyment of any right or privilege secured to that person by the U.S. Constitution (USDOJ, n.d.d). 

The most important pieces of legislation with regard to hate crimes were the Civil Rights Acts, passed in 1964 and 1968. Although the Civil Rights Act of 1964 was the landmark piece of civil rights legislation that made it illegal to discriminate against any individual based on race, color, religion, sex, or national origin, the Civil Rights Act of 1968 has been referred to as the “catalyst for modern hate crime legislation” (Hall, 2013:24). The Violent Interference With Federally Protected Rights, passed as part of the 1968 Act, made it a crime to use (or threaten to use) force to interfere with a person’s federally protected rights, such as the right to vote, public education, participation in jury service, interstate travel, and access to public places and services, because of a person’s race, color, religion, or national origin. Although the 1968 Act was important legislation, it required that the prosecution prove the defendant was motivated by bias when committing the given crime (Wang, 2000). Thus, the 1968 Act did not make the impact its legislators intended, because it was challenging for the prosecution to prove motivation in a given crime (Wang, 2000; Jacobs and Potter, 1998). During the same year, Congress passed the Fair Housing Act of 1968, which prohibited discrimination regarding the sale, rental, and/or financing of houses based on religion, national origin, race, or sex.

Later, Congress passed the Church Arson Prevention Act of 1996, which prohibited the intentional defacement, damage, or destruction of religious property because of the religious nature of that property and criminalized the obstruction of any person’s free exercise of religious beliefs by force or threat of force (USDOJ, n.d.d). Finally, in 2009, Congress passed the Matthew Shepard and James Byrd Jr. Hate Crimes Prevention Act (Shepard Byrd Act), named after two victims of hate crimes, which expanded the definition of hate crimes to include a victim’s gender, sexual orientation, or gender identity. The Shepard Byrd Act enhanced the tools available to prosecutors and increased the ability of the federal government to support state and local jurisdictions in prosecutions of hate crime. The Shepard Byrd Act was the first statute to allow the federal government to prosecute perpetrators for crimes motivated by the victim’s sexual orientation, gender, or gender identity (Matthew Shepard and James Byrd Jr. Hate Crimes Prevention Act, 2009). Most significantly, this Act required the Federal Bureau of Investigation (FBI) to collect data on hate crimes committed against or by juveniles (previously, only data related to adults had been collected).

In addition to federal legislation that addressed enforcement efforts with regard to hate crimes, legislation was passed to empower and mandate data collection efforts. In response to an increasing concern about hate crimes, in 1990 Congress passed the Hate Crime Statistics Act (USDOJ, n.d.a). This Act, and the Violent Crime Control and Law Enforcement Act of 1994, mandated data collection on crimes motivated by bias against others because of race, ethnicity, religion, sexual orientation, or disability. Further, to enhance and sustain the data collection and reporting of hate crimes, the Church Arson Prevention Act of 1996 made hate crime statistics a permanent addition to the FBI Uniform Crime Reporting (UCR) Program (USDOJ, n.d.a). 

In response to the recent increase in hate crimes against Asian Americans, Congress enacted the COVID–19 Hate Crimes Act in May 2021. This Act strives to make the reporting of hate crime more manageable by increasing public outreach and resources at state and local levels, while also providing states and local governments with grants to implement programs to prevent and respond to hate crimes (COVID–19 Hate Crimes Act, 2021).

The scope of youth involvement in hate crimes (as perpetrators and victims) can be illustrated through many different data sources at the national level (such as the FBI’s UCR) and through various studies conducted at a more local level (such as surveys conducted at high schools). The sections that follow will feature rates and trends of perpetration and victimization of hate crimes, with specific information on youth rates when available.

Data Sources

In the United States, two principal data sources provide information annually on hate crime offenses: 1) the FBI’s UCR Program and 2) the Bureau of Justice Statistics’ (BJS’s) National Criminal Victimization Survey (NCVS). Both sources define hate crime according to the Hate Crime Statistics Act, though there are differences in the data they collect. The UCR includes only crimes reported to the police, based on law enforcement agency reports and classifications. Law enforcement agencies report a bias crime as defined by federal law to the FBI’s UCR Program only if an investigation finds objective facts to show the crime was motivated, in whole or in part, by bias (USDOJ, n.d.e). The 2020 UCR data included submissions from 15,138 law enforcement agencies, with information about the reported offenses, those who offended, victims, and locations of hate crimes (USDOJ, n.d.a). The NCVS, by contrast, collects data from crime victims and thus includes hate crimes both reported and unreported to the police (Masucci and Langton, 2017). NCVS is collected from a nationally representative sample of households that are interviewed twice a year about criminal victimization. This self-report survey collects data on the frequency, characteristics, and consequences of nonfatal personal crimes (such as rape or sexual assault, robbery, aggravated and simple assault, and personal larceny) and household property crimes (such as burglary, motor vehicle theft, and other theft) both reported and not reported to police (USDOJ, n.d.a). NCVS also differs from the UCR in that it captures hate crimes only against individuals ages 12 and older and does not include crimes against businesses/organizations, institutionalized populations, and individuals in military barracks. Therefore, because of the difference in scope of the two sources, the annual counts of hate crime in the United States are usually significantly higher based on NCVS data, than the UCR Program (Masucci and Langton, 2017).

Limitations of UCR and NCVS Data

These data sources are not without limitations. With regard to the UCR, the type of data collected by each jurisdiction varies, owing in part to the differences in state-level hate crime laws affecting data collection requirements, in part to different requirements for department training on hate crime reporting, and also because of the voluntary nature of local law enforcement reporting to the program (Alongi, 2017; James and Hanson, 2021; USDOJ, n.d.d). Differing definitions between the FBI and state statutes regarding what constitutes a hate crime may lead to confusion on the part of law enforcement over which standard should be used to determine whether a hate crime occurred and should be reported. Further, as only a few states provide mandatory training for officers on investigating, identifying, and reporting hate crimes, it may be difficult for law enforcement to recognize biases in crimes or conduct full investigations, and this may hinder their ability to accurately report to the FBI UCR Program (James and Hanson, 2021).

Although more than 15,000 state and local law enforcement agencies voluntarily participate in the UCR (USDOJ, n.d.a), many agencies (potentially) underreport or do not report hate crimes to the FBI (Alongi, 2017). As part of the Hate Crime Statistics publications, the FBI publishes specific documentation that includes the agencies that indicate no incidents of hate crimes occurred in their respective jurisdictions during the quarter (or quarters) in a given year for which they submitted reports (FBI, 2019a). For 2019, of the 15,588 law enforcement agencies that participated in the UCR Program’s Hate Crime Statistics Program, 86.1 percent of agencies reported that no hate crimes occurred in their jurisdictions (FBI, 2019b).

In addition to the methodological limitations of the UCR, there are other factors that may contribute to the underreporting of hate crimes in official police data. As Pezella, Fetzer, and Keller (2019) explain, a distrust of law enforcement has been found to lower the chances that victims of hate crimes will report the incident to police, especially for members of marginalized groups. Further, there could be agency-level factors (such as a heavy caseloads or resource allocation issues that could influence the response to hate crimes) and individual-level factors (such as a officers’ beliefs in the legitimacy or fairness of hate crime legislation) that can affect the response, classification, and reporting of hate crimes in a jurisdiction. Regarding hate crime investigation, Haider–Markel (2002) analyzed survey data from 152 police departments and 37 district attorney’s offices across the country to examine implementation of hate crime laws, particularly for crimes based on sexual orientation. Findings suggested that the support and efforts of rank-and-file police and their leaders, the perceived tractability of state and local laws to address hate crime, and funding and training for police in hate crime procedures each made an impact on local law enforcement activity on hate crime.

Finally, there also are numerous methodological limitations with regard to NCVS data. NCVS estimates from the household interview samples are subject to a margin of error because the data are weighted to provide estimates for the entirety of the United States population (FBI, 2013; OJJDP, n.d.a). Moreover, one significant limitation of the survey for the provision of data on juvenile victimization is the exclusion of household members under 12 years old (OJJDP, n.d.a). Since NCVS data are self-reported victimizations, there is also the possibility the victim misinterpreted bias motivation (Pezzella, Fetzer, and Keller, 2019).

Overall Rates of Hate Crimes

According to the most recent data available from the UCR, in 2020 there were 11,129 hate crime offenses committed in the United States (FBI, 2020a). Yet according to the most recent data available from the NCVS, in 2019 (just 1 year earlier) there were 305,390 hate crime victimizations of people 12 years and older (Kena and Thompson, 2021). 

Further, according to the NVCS, between 2010 and 2019 there was an annual average of 243,770 hate crime victimizations, of which 44 percent were reported to the police; of those reported, only 13 percent were confirmed by police investigators as hate crimes. The data also showed that, between 2010 and 2019, youths ages 12 to 17 accounted for a higher proportion of hate crime victims compared with their proportion of the general U.S. population (youths accounted for 17 percent of hate crime victims but were only 9 percent of the general population) [Kena and Thompson, 2021].

Data from both the UCR and NCVS show that hate crimes are more likely to be violent than nonviolent offenses. The differences in annual rates between the two data sources underscore the large number of hate crimes that can go unreported to law enforcement.

Data Trends

Beginning in 2013, law enforcement started reporting the number of hate crimes committed by or against juveniles (under age 18) in keeping with the requirements of the Shepard Byrd Act. 

• According to the UCR, in 2013 there were 6,933 hate crime offenses committed by 5,814 known individuals, which affected 7,242 victims (FBI, 2013a). When age was reported, juveniles accounted for 32 percent^[3] of known persons who offended (FBI, 2013c) and 16 percent of the victims (FBI, 2013b).
• According to the UCR, in 2020 there were 11,129 hate crime offenses committed by 6,780 known individuals, which affected 11,472 victims (FBI, 2020a). When age was reported, juveniles accounted for 10.9 percent (FBI, 2020c) of known persons who offended and 9.4 percent of the victims (FBI, 2020b).

Taken together, these numbers indicate that between 2013 and 2020 there was a 60.5 percent increase in hate crime offenses. Regarding age, between 2013 and 2020 the proportion of hate crime offenses committed by juveniles decreased substantially (32 percent in 2013, compared with 10.9 percent in 2020). During this same period, the proportion of juvenile victims also decreased (16.0 percent in 2013, compared with 9.4 percent in 2020).

Victims of Hate Crimes and Bias Incidents

Numerous surveys, studies, and other data sources provide information and insight on hate crime victimization, for the general population and youth specifically, at the national and local levels.

At the national level, according to the most-recent data published by the UCR, in 2020 there were 11,472 victims of hate crimes known to law enforcement, of which 11,126 were victims of single-bias incidents.[⁴] Of the 8,245 victims of single-bias incidents whose age was reported, 7,248 (90.6 percent) were adults and 748 (9.4 percent) were juveniles (FBI, 2020b). Additional demographic information (such as race/ethnicity) about victims was not provided.

With regard to specific hate crime victimization of youth in 2020 for single-bias incidents (FBI, 2020b):

• Most juveniles (589) were victims of race-/ethnicity-/ancestry-motivated hate crimes. These included 408 victims of anti-Black or anti–African American  bias, 61 victims of anti-Hispanic or anti-Latino bias, 64 victims of anti-white bias, 24 victims of anti–multiple races bias, 14 victims of anti-Asian bias, 9 victims of anti–other race/ethnicity/ancestry bias, 6 victims of anti-American Indian or Alaska Native bias, and 3 victims of anti-Arab bias. 
• There were 109 juvenile victims of sexual orientation–motivated hate crimes, including 53 victims of antigay (male) bias, 39 victims of antilesbian, antigay, antibisexual, or antitransgender (mixed group) bias, 14 victims of antilesbian bias, 2 victims of antiheterosexual bias, and 1 victim of antibisexual bias.
• There were 32 juvenile victims of religion-motivated hate crimes, including 12 victims of anti-Jewish bias, 9 victims of anti-Muslim bias, 6 victims of other religion bias, 3 victims of anti-Protestant bias, and 2 victims of anti-Sikh bias.
• There were 22 juvenile victims of gender identity–motivated hate crimes, including 15 victims of antitransgender bias and 7 victims of anti–gender nonconforming bias. 
• There were 19 juvenile victims of disability-motivated hate crimes, including 10 victims of anti-physical bias and 9 victims of anti-mental bias.
• There were 5 juvenile victims of gender-motivated hate crimes, including 4 victims of antifemale bias and 1 victim of antimale bias. 

Figure 1 illustrates the breakdown of juvenile hate crime victimization for single-bias incidents by bias motivation. Most juvenile victims of hate crimes are victims of race-/ethnicity-/ancestry-motivated hate crimes.

Another report that captures youths’ experience with hate crime victimization at the national level is the annual Indicators of School Crime and Safety, a collection of data gathered from a variety of national and international surveys (the School-Associated Violent Death Surveillance System, the National Vital Statistics System, the Teaching and Learning International Survey, the Campus Safety and Security Survey, and many others) of students, teachers, principals, and other school personnel (Wang et al., 2020). Hate incidents are captured through the School Crime Supplement of the NCVS (while BJS sponsors the NCVS data collection efforts, the National Center for Education Statistics sponsors the School Crime Supplemental portion of the survey). The School Crime Supplement specifically targets students between 12 and 18 years of age enrolled in public, private, and home schools and asks them about incidents that have occurred in the past 6 months or the previous school year, including incidents of bullying, weapons on campus, gang activity, and other items related to school safety. With regard to hate incidents experienced by students, the School Crime Supplement to the NCVS asks students nationwide specific questions related to their experiences of being called hate-related words and seeing hate-related graffiti at school. Wang and colleagues (2020) reported that in 2017 about 6 percent of students reported being called hate-related words at school (“hate related” was defined as derogatory terms used by others in reference to students’ personal characteristics), while 23 percent of students reported seeing hate-related graffiti at school. Notably, Wang and colleagues (2020) focused on hate incidents experienced by students, not on hate crimes.

In addition, a 2021 report from the Government Accountability Office (GAO) examined students’ experiences with bullying, hate speech, and hate crimes in schools, using data from the School Crime Supplement of the NCVS (specifically looking at data from 2014–15, 2016–17, and 2018–19), the School Survey on Crime and Safety, and the Office of Civil Rights’ Case Management System from the U.S. Department of Education. The GAO found that 

• One in four students experienced bullying that was based on their race, national origin, religion, disability, gender, or sexual orientation (examining data from 2018–19). 
• One in four students reporting seeing hate words or symbols (such as those referencing homophobic slurs) written in their schools (examining data from 2014–15, 2016–17, and 2018–19). This is a rate similar to that reported by Wang and colleagues (2020), who looked at data reported from only 2017. 
• Approximately 7 percent of students experienced hate speech related to their race, religion, ethnic background/national origin, disability, gender, or sexual orientation (examining data from 2018–19).
• The number of hate crimes in schools doubled from 2015–16 to 2017–18. From 2015–16, the number of hate crimes in schools was approximately 3,166; it increased to 5,732 in 2017–18. The most common bias motivation for the hate crimes in schools was race or color.

With regard to studies conducted at the local level, Jones and colleagues (2019) developed and tested an instrument called the Youth Bias Victimization Questionnaire to measure youth bias crime exposure in a sample of youth from three distinct geographic areas of the United States. Approximately 854 youths from Boston, MA, Philadelphia, PA, and areas of Tennessee were asked questions about experiencing bias victimization, questions about witnessing bias victimization, and incident-specific questions (for those who had reported direct bias victimization). The study asked the sample of youth about incidents that could be considered hate crimes (i.e., whether youths were ever hit or physically attacked on purpose because of their race, ethnicity, or skin color) and incidents that could be considered bias incidents (i.e., whether youths were ever called names or whether lies/rumors were ever spread about them because of their race, ethnicity, or skin color); thus, the results are not directly comparable with the findings from the UCR and other surveys described above. The results showed that, with regard to general exposure:

• 63 percent of youths in the sample reported lifetime exposure to any type of bias victimization, with 42 percent reporting victimization in the past year. 
• 95 percent of youths in the sample reported witnessing some kind of bias victimization in their lifetime, with 83 percent reporting witnessing the bias victimization in the past year. 

With regard to incident-specific characteristics, the most frequent bias victimization (for youths reporting direct bias victimization) was related to targeting one’s race, ethnicity, or skin color (43 percent), followed by sexual orientation (28 percent), gender identity (19 percent), religion/religious beliefs (19 percent), country of origin (16 percent), and disability (14 percent). 

Jones and colleagues (2019) also examined bias victimization type. The most common type was verbal abuse (57 percent), followed by having lies told or rumors spread (41 percent), being physically threatened (26 percent), verbal sexual harassment (26 percent), robbery by physical force (18 percent), being hit or physically attacked (16 percent), and vandalism or damage to property/belongings (13 percent). 

Further, experiencing one incident of bias victimization increased the chances of the youth experiencing multiple bias victimizations. While the survey found that 63.3 percent of sampled youths experienced at least one type of bias victimization in their lifetime, 38.7 percent reported experiencing two or more types of bias victimization in their lifetimes. The results also showed that experiencing one type of bias victimization (bias attributable to race/ethnicity, gender, sexual identity, etc.) increased the relative odds of experiencing another type of bias victimization by twofold (Jones et al., 2019), although further research with a larger and more representative sample of youth is needed. 

Perpetrators of Hate Crimes

Little is known about the youths who perpetrate hate crimes. According to the most recent data published by the UCR, in 2020 there were 6,780 individuals known to have committed hate crimes, of whom 6,657 committed single-bias incidents. Of the 6,263 known persons who offended whose age was reported, 5,581 were adults (89.1 percent) and 683 were juveniles (10.9 percent) [FBI, 2020c]. However, the UCR does not further disaggregate offenses by age, therefore it is not clear whether and how youths who perpetrate hate crimes differ from adults who perpetrate hate crimes. As a result, the information provided below is about all individuals who committed hate crimes, not only juveniles. 

With regard to specific single-bias incidents of hate crimes for adults and juveniles (FBI, 2020a):

• The majority of known persons (4,339 out of 6,657) committed hate crimes motivated by race/ethnicity/ancestry, including 2,302 known persons motivated by anti-Black or anti–African American bias, 825 known persons motivated by anti-white bias, 525 known persons motivated by anti-Hispanic or anti-Latino bias, 239 known persons motivated by anti-Asian bias, 196 known persons motivated by anti–other race/ethnicity/ancestry bias, 114 known persons motivated by anti–multiple races bias, 74 known persons motivated by anti–American Indian or Alaska Native bias, 52 known persons motivated by anti-Arab bias, and 12 known persons motivated by anti-Hawaiian or other anti–Pacific Islander bias.
• There were 1,043 known persons who committed hate crimes motivated by sexual orientation, including 680 known persons committing hate crimes motivated by antigay (male) bias, 250 known persons motivated by antilesbian, antigay, antibisexual, or antitransgender (mixed group) bias, 89 known persons motivated by antilesbian bias, 14 known persons motivated by antibisexual bias, and 10 known persons motivated by antiheterosexual bias.
• There were 814 known persons who committed hate crimes motivated by religion, including 401 known persons committing hate crimes motivated by anti-Jewish bias, 126 known persons motivated by anti-Islamic (Muslim) bias, 59 known persons motivated by anti-Sikh bias, 47 known persons motivated by anti-Catholic bias, 44 known persons motivated by anti–other religion bias, 30 known persons motivated by anti–Eastern Orthodox (Russian, Greek, other) bias, 27 known persons motivated by anti–other Christian bias, 26 known persons motivated by anti-Protestant bias, 19 known persons motivated by multiple religions bias, 14 known persons motivated by anti-Buddhist bias, 7 known persons motivated by anti-Mormon bias, 6 known persons motivated by anti-Hindu bias, 5 known persons motivated by anti-atheism/anti-agnosticism bias, and 3 known persons motivated by anti–Jehovah’s Witness bias.
• There were 279 known persons who committed hate crimes motivated by gender identity, including 226 known persons motivated by antitransgender bias and 53 known persons motivated by anti–gender nonconforming bias.
• There were 117 known persons who committed hate crimes motivated by disability, including 70 known persons motivated by anti-mental bias and 47 known persons motivated by anti-physical bias.
• There were 65 known persons who committed hate crimes motivated by gender, including 41 known persons motivated by antifemale bias and 24 known persons motivated by antimale bias.

Figure 2 illustrates the breakdown of single-bias incidents by bias motivation for known persons (adults and juveniles) who committed hate crimes. Most known persons who commit hate crimes do so based on race-/ethnicity-/ancestry-motivated bias.

Trends in Recruitment Approaches

Hoping to recruit new members, hate groups historically used radio and television broadcasts and print publications to spread their messages (Schafer, 2002). Blazak (2001) conducted interviews with 65 self-identifying skinheads, half of whom admitted to being involved in recruitment and many who were under age 20. They discussed recruitment tactics such as disseminating informational flyers (with contact information) in schools—particularly targeting high schools that promoted multiculturalism—and alternative music rock clubs. They reported recruiting youths in areas where there were economic, racial, or sexual perceived threats to identity (for example, in areas where there had recently been significant job layoffs, offering young people an outlet for blame).

Since the Internet launched to the general public, hate groups have been using the platform to connect with people who share the same ideologies and recruit new members to their cause. The first recognized online hate bulletin board was in 1984 (Berlet and Lyons, 2000), and the first documented hate site was Stormfront, established in the mid-1990s (Lennings et al., 2010), which had a specific “kids page” containing a history of the white race and an online coloring book (Borgeson and Valeri, 2004).

Hate groups use various websites dedicated to hateful content, mainstream social media (such as Facebook, Twitter, or Reddit), file archives, blogs, chat groups, and online video games to spread their ideologies, promote association with their groups, and encourage participation in events or activities related to their causes (Hawdon, Oksanen, and Räsänen, 2014; Graham, 2016; Arbeit et al., 2020). The Internet offers users anonymity and the opportunity to conveniently debate and advance hateful ideologies (Schafer, 2002). Arbeit and colleagues (2020) also cited research by Lewis (2018) that white supremacist groups share content online (for example, in chat rooms or advice videos) that initially seems reasonable and relatable to young people, to gradually recruit youths to endorse the ideology. 

Hate groups use unique and creative means to target youth recruitment. Schafer (2002) found that, of 132 hate sites on the Internet, 4.5 percent targeted pre-adolescent children with bright colors, animation, and references to popular cartoon characters. Another way modern hate-based groups use the Internet to attract young members is through hosting “white power” music on their sites, which include violent, hateful, and profane lyrics often set to a heavy metal tune (Schafer, 2002). This music may appeal to some young people who would not usually be open to a blatantly hateful ideology. In a live performance format (which gives the opportunity to interact with other fans and draw out new recruits [Futrell, Simi, and Gottschalk, 2006]), youths may slowly desensitize to racist images and messages and may be more accepting of the beliefs of hate organizations. Research by Cohen–Almagor (2018) also discusses hate groups’ efforts to appeal to youths through video games and music that teaches them that violence is acceptable. These tactics by hate groups also “cultivate a sense of community” and promote opportunities for socialization at events such as rallies or music festivals.

Exposure to Online Hate Speech and Hate Materials

Online hate speech is of growing concern in today’s social media–driven society (Kilvington, 2021; Schweppe, 2021). For example, some studies have demonstrated a positive association between the occurrence of online hate speech (especially in certain social media platforms such as Twitter) and incidences of offline hate crimes, meaning that as online hate speech has increased in-person hate crimes also have increased (Williams et al., 2020; Relia et al., 2019; Chan, Ghose, and Seamans, 2016). 

Unfortunately, youths are exposed to cyberhate, hate speech, and other hate materials online at very high rates. Costello and colleagues (2020) found 42.6 percent of youths reported occasionally seeing materials online that expressed negative views toward a particular group, while Hawdon, Oksanen, and Räsänen (2014) found 53.4 percent of youths reported seeing hateful or degrading writings or speech online, and Harriman and colleagues (2020) found 57.0 percent of youths related coming across hate messages on social media or on a website.

Several studies have examined factors that put youth at risk of exposure to hate speech and other hate materials online. For example, Costello and colleagues (2020) surveyed youths ages 15 to 24 about their exposure to materials online that express negative views toward specific social groups. They found that certain characteristics of youths were statistically significantly associated with an increase in exposure to online hate material, including they 1) spent more time online per day, 2) had greater dissatisfaction with the current direction of the United States, 3) were white, and 4) were interacting with friends online. Harriman and colleagues (2020) conducted a similar study with students ages 15 to 19 on their exposure to hateful material online and found that time spent online, messaging with someone online whom they had not met in person, benign online disinhibition, and good academic performance were factors statistically significantly associated with higher exposure to online hate messages. 

Further, researchers have recently begun to examine youths as the producers of cyberhate. As cited in Hawdon, Oksanen, and Räsänen (2014), research has found that exposure to online hate speech can encourage youth to perpetuate online hate speech (Foxman and Wolf, 2013). Bernatzky, Costello, and Hawdon (2020) surveyed a sample of 520 youths and young adults (ages 15–36) who were avid social media users, to examine what led to the production and posting of online hate. Approximately 14.5 percent of the survey respondents reported that they had produced online material that other people would likely interpret as hateful or degrading. The study showed that certain factors, such as differential association (measured as closeness to an online community) and differential reinforcement (measured as participating in ongoing hateful online interactions and showing agreeableness with deviant definitions of behavior), statistically significantly increased the odds that respondents reported producing cyberhate. Conversely, closeness with one’s family statistically significantly decreased the likelihood of respondents producing cyberhate. Other factors, such as closeness to friends, closeness to a religious community, and low self-control made no significant impact on producing cyberhate. Overall, the results suggested there are myriad factors that can affect youths’ development and posting of online hate; additional research is needed to explore what other factors could increase or decrease the production of cyberhate by youth.

In addition, researchers have begun to examine the connection between online misinformation and hate speech. While the relationship has yet to be empirically established (Cinelli et al., 2021), this is an important area of research regarding youths’ exposure to and acceptance of hateful messaging. Digital misinformation has become so pervasive in online social media that in a 2013 report the World Economic Forum listed it as “one of the main threats to human society” (Del Vicario et al., 2016:558). 

With regard to youth exposure to hate sites, analysis showed that in the United States, in general, hate sites more often do not advocate direct violence (Lennings et al., 2010) owing to exceptions to the free speech protection that can restrict or punish individuals for speech that threatens or facilitates violence in a specific or immediate way, creates a clear and present danger to others, or contributes directly to the commission of a crime (Killion, 2019; Kiska, 2012; Paz, Montero–Diaz, and Moreno–Delgado, 2020). Douglas and colleagues (2005) had similar findings; in their analysis of 43 white supremacist websites, most of the content exhibited higher levels of advocated conflict rather than violence. Instead, the site contents contained strategies of “social creativity” that attempted to justify the hate group’s superiority over the out-group without direct hostility or competition. This type of communicative function may help create a climate online that is conducive to conflict, where individuals feel their resentment is justifiable. Nevertheless, specific materials such as video games and music promoted on hate sites have been found to include lyrics calling for violence sometimes directly demonstrate or simulate violence against certain groups (Cohen–Almagor, 2018). 

It is well documented that youths are not only exposed to but also targeted by hate groups online; however, exposure does not guarantee buy-in to hateful ideology. Lee and Leets (2002) tested the persuasion of online hate messages over time in a sample of 108 adolescents ages 13 to 17. Respondents reviewed passages that represented the different narratives and persuasive attempts used by online hate sites. Low-narrative messages (“messages that do not link actions or events together in a meaningful way, or forms of presentation and argument that do not include plots or character identification” [2002:933]) and explicit messages (statements that are consistent with the speaker’s intention) led to longer-term persuasion. Individuals who were neutral on message receptivity—those who were neither for nor against—were more persuaded by implicit messages, defined as statements in which the speaker’s intention and the message content are sometimes inconsistent (Lee and Leets, 2002). Lennings and colleagues (2010) interpreted the results of this study, explaining that young people with uncommitted political opinions are more likely to be influenced by the use of techniques designed to present information, allow for counterargument, and then provide responses to this counterargument—essentially, a website chat room to allow users to debate the message.

Overall, further research is needed in this area. Lennings and colleagues’ (2010) review found individual cases that show people have used information shared on the Internet to commit hate crimes and established the feasibility of recruitment. But the extent to which active recruitment and actual radicalization of youth populations occurs online is unclear. Schafer (2002) made a similar assertion, that while hate groups can provide a wide range of information and resources on websites, this does not necessarily mean that groups will experience growths in membership or support.

Hate crimes make a unique impact on both the victim and the wider community (Garcia and McDevitt, 1999; Iganski, 2001; Duncan and Hatzenbuehler, 2014; Paterson, Walters, and Brown, 2019). Compared with their non–hate crime victim counterparts, hate crime victims are more likely to experience heightened psychological distress and more symptoms of anxiety, depression, anger, and posttraumatic stress disorder (Herek, Gillis, and Cogan, 1999; Kercher, Nolasco, and Wu, 2008). In the wider community, individuals who share the same characteristics as the victim may feel vulnerable to future attacks. This heightened vulnerability may result in individuals restricting their movements and/or activities, decreasing community cohesion (Freilich and Chermak, 2013; IACP, n.d.).

Youth victims of hate crimes can face serious negative impacts owing to their victimization. Examining the sample from the study on the Youth Bias Victimization Questionnaire, Mitchell and colleagues (2020) explored the relationship involving trauma symptoms, perceptions of social support, and exposure to multiple types of bias victimization. The study authors found that youths who reported experiencing bias victimization (due to race/ethnicity, gender, sexual identity, etc.) also reported increased symptoms of trauma and decreased perceptions of social support. They found that, for youths who reported experiencing multiple forms of bias, there was an incremental relationship to increased trauma symptomology and less perceived social support, meaning youths who experienced more than one type of bias victimization were more likely to experience symptoms of trauma and feel as though they do not have social support.

A study by Mendez and colleagues (2016) explored the impacts of bias-based peer victimization by surveying more than 13,000 students in grades 5 to 12 across the United States. Almost 10 percent of the sample (1,268 students) reported experiencing a form of bias-based peer victimization (including victimization based on race, sexual orientation, and disability status). The study found that youths who experienced bias-based victimization because of their sexual orientation, disability, and race were statistically significantly more likely to report a high–severe emotional impact (such as having trouble eating or sleeping or feeling unsafe and threatened) compared with youths who were victimized for other reasons (such as for their looks or family income). The findings suggest that even among youths who experience peer victimization at school, youths who experience bias-based victimization may face harsher emotional consequences. 

Other research has also illustrated the negative consequences that youths experience with regard to bias-based harassment from peers (compared with youths' experiencing non–bias-based harassment), including greater risks for substance use; lower levels of academic achievement and higher levels of truancy; higher likelihood of losing friends; and higher rates of mental health issues such as depression, psychological distress, and suicidal ideation (Russell et al., 2012; Sinclair et al., 2012; Tucker et al., 2016; Jones et al., 2018). Taken together, the research suggests the negative consequences can be experienced to a greater extent for youths who are victims of hate crimes and bias-based harassment, compared with youths who experience other types of crimes or other types of victimizations.

Federal and State-Level Responses to Hate Crimes

There are a variety of federal initiatives that are focused on the reduction and prevention of hate crimes. Staff from the FBI’s UCR Program and the Civil Rights Unit have developed a training program for local agencies to help increase hate crime statistics reporting. The U.S. Department of Justice’s (USDOJ’s) Community Relations Service—established under Title X of the Civil Rights Act of 1964 and expanded under the Shepard Byrd Act of 2009—responds to community conflicts that stem from differences of race, color, national origin, gender, gender identity, sexual orientation, religion, or disability (USDOJ, n.d.c). This agency initiated the City–Site Problem Identification and Resolution of Issues Together (City–SPIRIT) program, which helps communities address tension and conflict related to issues of race, color, national origin, gender, gender identity, sexual orientation, religion, or disability (CRS, n.d.). The USDOJ’s Community-Oriented Policing Services Office (commonly called the COPS Office) provides resources for law enforcement to support communities affected by hate or biased crimes, including case studies and sample policies for eliminating bias against the LGBTQ+ community, increasing trust in immigrant communities, and a full hate crimes curriculum focused on law enforcement response, investigation, and reporting (COPS Office, n.d.). The USDOJ Civil Rights Division enforces federal statutes prohibiting discrimination on the basis of race, color, and sex (USDOJ, n.d.b). In addition, the Bureau of Justice Assistance (BJA) has invested in communities that focus on investigating and prosecuting hate crime offenses, through the Edward Byrne Memorial Justice Assistance Grant Program, the Emmett Till Cold Case Investigations Program, and the most recent 2021 Matthew Shepard and James Byrd Jr. Hate Crimes Program, which supports law enforcement and prosecution agencies in their outreach to and education for the public about hate crimes. The program also supports victims, agency staff, and partners who have been harmed by these crimes. Finally in 2021, the Office of Juvenile Justice and Delinquency Prevention launched a comprehensive national initiative to prevent youth hate crimes and identity-based bullying that includes a webinar series, a youth hate crime prevention curriculum, and a series of youth round tables, among other resources (OJJDP, n.d.b).

There is also work being done at the state level to combat hate crimes, including the creation of hate crime task forces to tackle the issue. The New York Police Department’s Hate Crime Task Force, founded in 1980 and still operational today, is an example of a specialized unit designed to reduce hate crimes through efforts such as outreach to diverse communities and advocacy groups to help create trust; developing data collection methods to increase the gathering of hate crime incidents across the various precincts; establishing relationships with prosecutors to help increase prosecution of hate crime cases; and making use of the police department’s victim support services for hate crime victims (Levin and Amster, 2007; Rabrenovic, 2007).

An example of an ongoing state-level initiative specifically focused on youth is the Maine Civil Rights Team Project, which began with BJA funding support and is managed out of the state Attorney General’s Office. This is a statewide, school-based program for preventing bias-motivated behaviors and harassment currently available in more than 175 schools. The program involves Civil Rights Teams made up of students, adult advisers, and school administrators who meet regularly to reflect on and discuss issues related to race, national origin and ancestry, religion, disabilities, gender identity and expression, and sexual orientation. The teams raise schoolwide awareness of bias and prejudice that may be within their schools, and forums are organized to allow students to talk about harassment and related issues. The Attorney General’s Office offers support to schools to address these issues (Wessler, 2000; Office of the Maine Attorney General, n.d.).

Interventions to Prevent Youth Hate Crimes or Bias Incidents

In general, there has not been much rigorous research conducted to examine the effectiveness of hate crime prevention and intervention programs in the United States, including the federal initiatives described above, and many programs have not sustained long-term implementation, usually owing to lack of funding (Iganski and Smith, 2011; Shively, 2005). Some advocacy groups and human rights organizations (such as the Southern Poverty Law Center and the Simon Wiesenthal Center) have focused on developing programs to reduce hate in society, but the programs have not been rigorously evaluated.

As with many prevention programs that focus on reducing youth antisocial behavior, those programs that have been designed to address hateful, racist, bias, or other related behaviors are predominately school based. Facing History and Ourselves is a school program that uses lessons of history to challenge teachers and their students to stand up to bigotry and hate. It is a 10-week-long course that explores historical case studies (for example, the Holocaust) and has students reflect on the causes and consequences of prejudice, discrimination, and violence along with the courage, compassion, and social action that may have also occurred. A 2001 evaluation of the Facing History and Ourselves program by Schultz, Barr, and Selman included 346 eighth grade students (212 treatment group students who participated in the program and 134 comparison group students who did not) and found that treatment group students showed statistically significant decreases in racist attitudes relative to comparison group students, suggesting that participating students became less racist across the school year.

An evaluation by Esbensen (2009) examined the effects of Teens, Crime, and the Community’s Community Works, a school-based program based on a risk factors approach. The program consisted of three parts:

1. A curriculum with 31 lessons that address topics such as guns, violence, hate crimes, substance abuse, conflict management, and preventing victimization

2. The use of Community Report People (such as teachers, doctors, or lawyers) as role models to help deliver the curriculum 

3. The use of Community Report People (such as teachers, doctors, or lawyers) as role models to help deliver the curriculum

The use of “Action Projects” to allow program participants to apply what they learned in school and the community

The program was implemented in 15 schools in nine cities across four states, and the evaluation looked at 46 different outcome measures. Overall, there were mixed results. While students who participated in the program experienced statistically significant reductions in measures of overall delinquency and violent offending, compared with students who did not participate, there was a statistically significant reduction in conflict resolution of students who participated in a program (suggesting a negative effect of the program); most of the other outcome measures were not significant. 

School-based hate- and bias-prevention programs attempt to address tolerance, diversity, and prejudice, which are tenants of bullying prevention. Englander (2007) discussed similarities and differences between characteristics of youth bullying and hate crime perpetration, and how this could inform effective approaches to reduce bullying. Youths who perpetrate both bullying and hate or bias incidents target individuals who are considered “different” from others. Acknowledging the connection, many bullying-prevention programs do include tolerance and respect as part of the curriculum (Englander, 2007). The author asserted that both bullying- and hate crime–prevention programs need to acknowledge and teach the unacceptability of unequal power conflicts for mediation.

Wachs, Wright, and Vazsonyi (2019) similarly discussed the nuances between cyberhate and cyberbullying. Both involve the intention to harm a person or group by using information and communication technologies, while cyberbullying is often directed at a single person and cyberhate is based more on general prejudice about a group. Given the overlap, certain tenets of bullying prevention programs in school could help in addressing and preventing hateful behavior. The School-Based Bullying Prevention Programs practice, featured on the Model Programs Guide (MPG), provides examples of programs that seek to reduce bullying and victimization (including physical, verbal, and psychological bullying) in school settings. These programs are aimed at students directly involved in bullying incidents by implementing strategies such as teacher trainings, parent informational meetings, or bullying prevention curriculum materials, and also at bystanders who witness incidents through elements such as video reenactments (Wong, 2009; Polanin et al., 2012; Gaffney, Ttofi, and Farrington, 2019). The practice provides examples of bullying prevention programs that could incorporate components of antiracism or antidiscrimination teachings into the curricula. Across the three meta-analyses, there were statistically significant reductions in bullying perpetration and victimization and improvements in bystander intervention behavior, but there were no statistically significant effects on empathy for the bullying victim.[5]

Another example of a school-based curriculum is Resolving Conflict Creatively (New York City), which focuses on character education and social and emotional learning to improve conflict resolution in children ages 6–13. The curriculum seeks to develop several core skills, such as countering bias, resolving conflicts, fostering cooperation, appreciating diversity, communicating clearly, expressing feelings, and dealing with anger. Students who participated in the program demonstrated statistically significant increases in prosocial behaviors such as “is helpful to others” and “acts friendly to others,” compared with students who did not participate (Aber, Brown, and Jones, 2003); however, outcomes measuring behaviors related to countering bias and appreciating diversity were not included in the evaluation.

Another practice on MPG is School-Based Conflict Resolution Education, which includes programs that seek to reduce school-based conflict and encourage long-term prosocial behavior by teaching students to understand the nature of the conflict and providing acceptable options for responding. A meta-analysis by Garrard and Lipsey (2007) examined the results from 36 studies on conflict resolution education programs and found statistically significant reductions in measures of antisocial behavior, including reductions in the proportion of students being called hate-related words (which dropped on average from 11 percent to 7.5 percent).

Finally, the U.S. Department of Education’s What Works Clearinghouse has compiled a list of evidence-based curricula related to combating racism in K–12 settings (Regional Education Laboratory Northeast & Islands, 2020). Approaches such as ethnic studies curricula, antibias curricula, and culturally relevant pedagogy seek to address children’s racial attitudes and improve educational outcomes for minority students (Dee and Penner, 2017; Martell, 2018). While some of the studies on the list have been evaluated, there were no outcome measures examining reductions in hate or bias behaviors of students.

Example of Emerging Ideas for Prevention

Inoculation theory is an established social psychological/communication theory and is emerging as one theoretical underpinning for strategies to prevent youth involvement in hate and bias incidents. Developed by William McGuire in the early 1960s, the theory posits that individuals can be made resistant to persuasion if they first perceive threat from an impending attempt to change their beliefs or attitudes, and then receive information to refute such an attempt (Braddock, 2019). Applying this concept to hateful messaging or content, exposing individuals to weakened arguments can inoculate (or protect) them against stronger arguments of the same nature (McGuire, 1961a; McGuire, 1961b). Eventually, the ability to create one’s own counterarguments can increase resistance to persuasive influences (Carthy et al., 2020). Previously cited research by Lee and Leets (2002) and Lennings (2010) about the persuasive attempts used by online hate sites and how youths can be influenced by these sites underscores the importance of this theory in shaping prevention efforts for youth. While inoculation theory has been researched in the context of numerous youth health attitudes and behaviors such as preventive alcohol education (Duryea, 1984) and gang prevention (Breen and Matusitz, 2009), there is need for further exploration on how it could inform efforts to prevent youth susceptibility to hateful content.

One example of an intervention for misinformation based on the principles of inoculation theory is the “Bad News” web-based game. Participants enter a simulated social media environment and are gradually exposed to weakened “doses” of common misinformation strategies, including impersonating people online, using emotional language, group polarization, spreading conspiracy theories, discrediting opponents, and trolling (Maertens et al., 2020). Basol, Roozenbeek, and van der Linden (2020) examined the efficacy of the Bad News game in conferring attitudinal resistance to misinformation in a sample of adolescents (modal age bracket 18–24) in England. Participants were randomly presented with 18 fictitious Twitter posts and reported on how reliable they perceived each post to be and how confident they were in their judgments. The study authors found that adolescents in the inoculation condition who played the game demonstrated a larger decrease in perceived reliability of fake news items. While these findings show promise, a follow-up study by Maertens and colleagues (2020) found that inoculation effects decreased after 2 months. Though short term, these findings suggest that a gaming intervention could help improve youths’ ability to identify and resist misinformation, which could in turn help combat misinformation related to hateful messages.

There are many gaps in the research literature exploring the prevalence, causes, and consequences of hate crimes, especially with regard to the involvement of youth. Five, in particular, follow. 

First, research on youth involvement (as perpetrators and victims) is lacking. For example, although the UCR reports that juveniles constituted 9.4 percent of hate crime victims and 10.9 percent of persons who committed hate crime offenses, specific information—such as a breakdown of youth demographic characteristics or an examination of the specific types of crime committed by youth (i.e., violent hate crime versus property hate crime)—is not available. This type of data could provide useful information, such as whether youth hate crime perpetrators are more likely to commit property offenses, compared with violent offenses, or how hate crimes committed by juveniles may differ from non–hate crimes committed by juveniles. A report by Masucci and Langton (2017) found that, between 2011 and 2015, juveniles who offended accounted for 15.4 percent of violent hate crimes and 17.3 percent of violent non–hate crimes, showing that with regard to violent offending juveniles were arrested at a slightly higher rate for non–hate crimes than for hate crimes. However, the report provided only a breakdown of violent hate crimes versus violent non–hate crimes, and there has been no research to further explore the similarities of and differences between juvenile hate crimes and non–hate crimes.

Second, improved data collection efforts (at the national and local levels) are needed to ensure that information about youth hate crimes is accurate. For example, McDevitt and colleagues (2002) examined the collection of bias crime statistics nationally, through an in-depth examination of reporting methods in eight police departments across the country. They collected information on the departmental culture around bias-crime reporting, examined the department’s infrastructure for reporting, and reviewed records to identify potential errors in the reporting process. They found that some departments defined bias crime as involving only the most-serious crime types (murder, aggravated assault), so officers in these departments may not properly recognize these incidents because they do not perceive less-serious crime types as potentially biased. Specifically, when youths committed less-serious crimes with bias indicators, responding officers were inclined to believe these were merely “kids’ pranks,” and this interfered with their inclination to ask appropriate questions that might have revealed a bias motivation. When officers do not think of youth as capable of committing bias crimes, they are less likely to conduct a full investigation either at the time of the offense or during subsequent investigations (McDevitt et al., 2012; Levin et al., 2007). This study illustrates the importance of ensuring that data (especially those collected by law enforcement) are gathered in a consistent, accurate manner, so that examination of those data provides a reliable account of what youth hate crime perpetration and victimization looks like. This can ensure that efforts to address youth hate crime (either through prevention programming or police interventions) are focused on the issues that could lead to a reduction in youth hate crime occurrences. 

Third, information on the pathways to hate crime perpetration is also needed. There is a lack of longitudinal data on what leads youths to commit hate crimes (including risk factors that influence the commission of a hate crime) that would be important in prevention and response efforts. There also is little research focusing on youth disengagement, from hate groups or some general hate crime offending. 

Fourth, there is a lack of rigorous research evaluating interventions to prevent and reduce youth hate crime perpetration and victimization in the United States. Other countries, especially Germany and Sweden, have rigorously evaluated and sustained programs that rehabilitate youths who committed hate crimes and help them disengage from hate groups (i.e., EXIT Sweden, Abschied von Hass und Gewalt or “Taking Responsibility—Breaking Away From Hate and Violence”; Iganski, 2012). Their applicability to the United States youth population could be further explored.

Fifth, additional research is needed to explore the connection between exposure to hate online and actual recruitment and perpetration of hate crimes and/or bias incidents. While several studies have examined youths’ risk of exposure to hate speech and hate materials online (Costello et al., 2020; Harriman et al., 2020), there has not been much research on the extent to which exposure leads to antisocial behavior, such as committing hate crimes. As previously mentioned, several studies have shown a relationship between the increase in online hate speech on Twitter and in-person hate crimes (Williams et al., 2020; Relia et al., 2019; Chan, Ghose, and Seamans, 2016). Research specifically focused on youth is needed in the area, along with an examination of other social media platforms popular with youth (i.e., TikTok).

Hate crimes are traditional crimes (assault, vandalism, etc.) motivated by bias against others because of their actual or perceived race, ethnicity, sexual orientation, gender, gender identity, religion, or disability. Compared with traditional crimes, the impact of hate crimes may not be experienced by only the victim but also by other members of the community to which the victim belongs (Freilich and Chermak, 2013). 

According to the 2020 data from the FBI’s UCR, juveniles accounted for 10.9 percent of hate crime perpetrators and 9.4 percent of hate crime victims. Though these rates have been declining for juveniles, specific data on the characteristics of youths who commit hate crimes and the specific types of hate crimes they commit (i.e., violent versus property hate crimes) are not currently available. This information could better inform efforts to prevent or reduce the occurrence of hate crimes perpetrated or experienced by youth.

Research has examined the methods hate groups use to recruit youth to their causes. Earlier research showed that hate groups would rely on in-person methods, such as disseminating informational flyers at schools or concerts, to recruit youth (Blazak, 2001). More-recent research suggests that hate groups use online methods, such as creating webpages targeted at youths (including young kids), hosting “white power” music on websites, and developing video games to appeal to youth (Borgeson and Valeri, 2004; Lennings et al., 2010; Cohen–Almagor, 2018). Several studies have shown that between 40 percent and 60 percent of youths may be exposed to hate speech and other hate materials online (Hawdon, Oksanen, and Räsänen, 2014; Harriman et al., 2020; Costello et al., 2020).

Further, several studies have illustrated the negative impact that hate crime and bias-based victimization can make on youth, such as increased symptoms of trauma, higher risks for substance use, and higher rates of mental health issues (Sinclair et al., 2012; Tucker et al., 2016; Jones et al., 2018). However, there has been less research focused on how to help youths cope with these issues.

While there are several federal and state-level initiatives focused on reducing hate crimes (some with specific concentration on youth hate crimes), rigorous research (such as randomized controlled trials or quasi-experimental designs) has not been conducted to test the impact of these efforts. Although some rigorous studies have been conducted on interventions that concentrate on issues related to hate crime and bias incident perpetration and victimization (Schultz, Barr, and Selman, 2001; Aber, Brown, and Jones, 2003), many of these studies do not measure the impact on outcome measures of hate, racism, discrimination, and other related outcomes. Bullying and cyberbullying prevention programs may be types of intervention that can focus on reducing behaviors related to hate crimes and bias incidents; however, these programs will need to include specific components that concentrate on those behaviors.

Overall, there are several gaps in the current literature on youth and hate crimes that should be addressed, such as the pathways youths take to hate crime perpetration, and the connection between exposure to online hate speech and hate materials and actual recruitment and perpetration of hate crimes and bias incidents. A great deal of research has focused on hate crimes in general. But more research is needed with attention to youths’ involvement in hate crimes.

Aber, J.L., Brown, J.L., and Jones, S.M. 2003. Developmental trajectories toward violence in middle childhood: Course, demographic differences, and response to school-based intervention. Developmental Psychology 39(2):324–348.

Alongi, B. 2017. The negative ramifications of hate crime legislation: It’s time to reevaluate whether hate crime laws are beneficial to society. Pace Law Review 37(1):326–351.

Arbeit, M.R., Burnham, S.L., de Four, D., and Cronk, H. 2020. Youth practitioners can counter facism: What we know and what we need. Journal of Youth Development 15(5):37–67.

Basol, M., Roozenbeek, J., and van der Linden, S. 2020. Good news about bad news: Gamified inoculation boosts confidence and cognitive immunity against fake news. Journal of Cognition 3(1):2:1–9.

Berlet, C., and Lyons, M.N. 2000. Right-Wing Populism in America: Too Close for Comfort. New York, NY: Guilford Press.

Bernatzky, C., Costello, M., and Hawdon, J. 2021. Who produces online hate? An examination of the effects of self-control, social structure, and social learning. American Journal of Criminal Justice, published online January 7, 2021. https://link.springer.com/article/10.1007/s12103-020-09597-3

Blazak, R. 2001. White boys to terrorist men: Target recruitment of Nazi skinheads. American Behavioral Scientist 44(6):982–1000.

Borgeson, K., and Valeri, R. 2004. Faces of hate. Journal of Applied Sociology/Sociological Practice 21(2)/6(2):99–111.

Braddock, K. 2019. Vaccinating against hate: Using attitudinal inoculation to confer resistance to persuasion by extremist propaganda. Terrorism and Political Violence 33:1–23.

Breen, G.M., and Matusitz, J. 2009. Preventing youths from joining gangs: How to apply inoculation theory. Journal of Applied Security Research 4(1–2):109–128.

(BJA) Bureau of Justice Assistance. 2021. Programs That Address Hate Crimes. Washington, DC: U.S. Department of Justice (USDOJ), Office of Justice Programs (OJP), BJA.

Carthy, S.L., Doody, C.B., Cox, K., O’Hora, D., and Sarma, K.M. 2020. Counternarratives for the prevention of violent radicalisation: A systematic review of targeted interventions. Campbell Systematic Reviews 16(3):1–37.

Chan, J., Ghose, A., and Seamans, R. 2016. The Internet and racial hate crime: Offline spillovers from online access. MIS Quarterly 40(2):381–403.

Cinelli, M., Pelicon, A., Mozetič, I., Quattrociocchi, W., Novak, P.K., and Zollo, F. 2021. Dynamics of online hate and misinformation. Scientific Reports 11(1):1–12.

Cohen–Almagor, R. 2018. Taking North American white supremacist groups seriously: The scope and challenge of hate speech on the Internet. International Journal for Crime, Justice and Social Democracy 7(2):38–57.

(COPS Office) Community-Oriented Policing Services Office. n.d. Hate Crime Resources. Washington, DC: USDOJ, COPS Office. https://cops.usdoj.gov/hatecrimeresources.

(CRS) Community Relations Services. n.d. City–Site Problem Identification and Resolution of Issues Together (City–SPIRIT). Washington, DC: USDOJ. https://www.justice.gov/crs/our-work/facilitation/city-spirit.

Costello, M., Barrett–Fox, R., Bernatzky, C., Hawdown, J., and Mendes, K. 2020. Predictors of viewing online extremism among America’s youth. Youth & Society 52(5):710–727.

COVID-19 Hate Crimes Act. (2021). https://www.congress.gov/bill/117th-congress/senate-bill/937/text

Dee, T.S., and Penner, E.K. 2017. The causal effects of cultural relevance: Evidence from an ethnic studies curriculum. American Educational Research Journal 54(1):127–166.

Del Vicarioa, M., Bessib, A., Zolloa, F., Petronic, F., Scalaa, A., Caldarellia, G., Stanleye, H.E., and Quattrociocchia, W. 2016. The spreading of misinformation online. Proceedings of the National Academy of Sciences 113(3):554–559.

Douglas, K.M., McGarty, C., Bliuc, A. and Lala, G. 2005. Understanding cyberhate: Social competition and social creativity in online white supremacist groups. Social Science Computer Review 23(1):68–76.

Duncan, D.T., and Hatzenbuchler, M.L. 2014. Lesbian, gay, bisexual, and transgender hate crimes and suicidality among a population-based sample of sexual-minority adolescents in Boston. American Journal of Public Health 104(2):272–278.

Englander, E. 2007. Is bullying a junior hate crime? Implications for interventions. American Behavioral Scientist 51(2):205–212.

(FBI) Federal Bureau of Investigation. 2013. The nation’s two crime measures. In Crime in the United States 2013. Washington, DC: U.S. Department of Justice. Retrieved November 12, 2021 on the web: https://ucr.fbi.gov/crime-in-the-u.s/2013/crime-in-the-u.s.-2013/resource-pages/nations-two-crime-measures/nations_two_crime_measures

(FBI) Federal Bureau of Investigation. 2013a. Table 1. Incidents, offenses, victims, and known offenders by bias motivation, 2013. In Hate Crime Statistics Annual Reports. Washington, DC: USDOJ, FBI. 
https://ucr.fbi.gov/hate-crime/2013/tables/1tabledatadecpdf/table_1_incidents_offenses_victims_and_known_offenders_by_bias_motivation_2013.xls.

(FBI) Federal Bureau of Investigation. 2013b. Table 7. Victims, offense type by bias motivation, 2013. In Hate Crime Statistics Annual Reports. Washington, DC: USDOJ, FBI. https://ucr.fbi.gov/hate-crime/2013/tables/7tabledatadecpdf

(FBI) Federal Bureau of Investigation. 2013c. Table 9. Known offender’s race, ethnicity, and age, 2013. In Hate Crime Statistics Annual Reports. Washington, DC: USDOJ, FBI. https://ucr.fbi.gov/hate-crime/2013/tables/9tabledatadecpdf/table_9_known_offenders_known_offenders_race_2013.xls.

(FBI) Federal Bureau of Investigation. 2019a. Table 14. Hate crime zero data submitted, per quarter, by state and agency, 2019. In Hate Crime Statistics Annual Reports. Washington, DC: USDOJ, FBI. https://ucr.fbi.gov/hate-crime/2019/tables/table-14-data-declaration

(FBI) Federal Bureau of Investigation. 2019b. Hate crime by jurisdiction. In Hate Crime Statistics Annual Reports. Washington, DC: USDOJ, FBI. https://ucr.fbi.gov/hate-crime/2019/topic-pages/jurisdiction

(FBI) Federal Bureau of Investigation. 2020a. Table 1. Incidents, offenses, victims, and known offenders by bias motivation, 2020. In Hate Crime Statistics Annual Reports. Washington, DC: USDOJ, FBI. https://crime-data-explorer.fr.cloud.gov/pages/downloads.

(FBI) Federal Bureau of Investigation. 2020b. Table 7. Victims, offense type by bias motivation, 2020. In Hate Crime Statistics Annual Reports. Washington, DC: USDOJ, FBI. https://crime-data-explorer.fr.cloud.gov/pages/downloads.

(FBI) Federal Bureau of Investigation. 2020c. Table 9. Known offender’s race, ethnicity, and age, 2020. In Hate Crime Statistics Annual Reports. Washington, DC: USDOJ, FBI. https://crime-data-explorer.fr.cloud.gov/pages/downloads.

(FBI) Federal Bureau of Investigation. 2020d. Table 14. Hate crime zero data submitted per quarter by state, federal, and agency, 2020. In Hate Crime Statistics Annual Reports. Washington, DC: USDOJ, FBI. https://crime-data-explorer.fr.cloud.gov/pages/downloads.

Foxman, A., and Wolf, C. 2013. Viral Hate: Containing Its Spread on the Internet. New York, NY: Palgrave MacMillan.

Freilich, J.D., and Chermak, S.M. 2013. Problem-Oriented Guides for Police. Problem-Specific Guides, series no. 72. Washington, DC: Center for Problem-Oriented Policing.

Futrell, R., Simi, P., and Gottschalk, S. 2006. Understanding music in movements: The white power music scene. Sociological Quarterly 47(2):275–304.

Gaffney, H., Ttofi, M.M., and Farrington, D.P. 2019. Evaluating the effectiveness of school-bullying prevention programs: An updated meta-analytical review. Aggression and Violent Behavior 45:111–133.

Galán, C.A., Stoke, L.R., Szoko, N., Adebe, K.Z., and Culyba, A.J. 2021. Exploration of experiences and perpetration of identity-based bullying among adolescents by race/ethnicity and other marginalized identities. JAMA Network Open 4(7):e2116364.

Garcia, L., and McDevitt, J. 1999. The Psychological and Behavioral Effects of Bias and Nonbias Motivated Assault. Washington, DC: USDOJ, OJP, National Institute of Justice (NIJ).

Garland, J. 2012. Difficulties in defining hate crime victimization. International Review of Victimology 18(1):25–37.

Garrard, W.M., and Lipsey, M.W. 2007. Conflict resolution education and antisocial behavior in U.S. schools: A meta-analysis. Conflict Resolution Quarterly 25(1):9–38.

(GAO) Government Accountability Office. 2021. K–12 Education: Students’ Experiences With Bullying, Hate Speech, Hate Crimes, and Victimization in Schools. Report to the Chairman, Committee on Education and Labor, House of Representatives. Washington, D.C.: GAO.

Graham, R. 2016. Interideological mingling: White extremist ideology entering the mainstream on Twitter. Sociological Spectrum 36(1):24–36.

Haider–Markel, D.P. 2002. Regulating hate: State and local influences on hate crime law enforcement. State Politics & Policy Quarterly 2(2):126–160.

Hall, N. 2013. Hate Crime. Abington, Oxfordshire, England: Routledge.

Harriman, N., Shortland, N., Su, M., Cote, T., Testa, M.A., and Savoia, E. 2020. Youth exposure to hate in the online space: An exploratory analysis. International Journal of Environmental Research and Public Health 17:8531.

Hawdon, J., Oksanen, A. and Räsänen, P. 2014. Victims of online groups: American youth’s exposure to online hate speech. In The Causes and Consequences of Group Violence: From Bullies to Terrorists, edited by J. Hawdon, J. Ryan, and M. Lucht. Lanham, MD: Rowman & Littlefield, pp. 165–182.

Herek, G.M., Gillis, J.R., and Cogan, J.C. 1999. Psychological sequelae of hate crime victimization among lesbian, gay, and bisexual adults. Journal of Consulting and Clinical Psychology 67(6):945–951.

Iganski, P. Hate crimes hurt more. American Behavioral Scientist 45(4):626–38.

Iganski, P. 2012. Hate Crime: Taking Stock—Programmes for Offenders of Hate. South Belfast, Northern Ireland: European Union’s Programme for Peace and Reconciliation.

Iganski P., and Smith, D. 2011. Rehabilitation of Hate Crime Offenders: Research Report. Edinburgh, Scotland: Scotland Equality and Human Rights Commission.

(IACP) International Association of Chiefs of Police. n.d. Responding to Hate Crimes: A Police Officer’s Guide to Investigation and Prevention. Alexandria, VA. https://www.theiacp.org/resources/responding-to-hate-crimes-a-police-officers-guide-to-investigation-and-prevention.

Jacobs, J.B., and Potter, K. 1998. Hate Crimes: Criminal Law & Identity Politics. Oxford, England: Oxford University Press on Demand.

James, N., and Hanson, E.J. 2021. Federal Data on Hate Crimes in the United States. Washington, DC: Congressional Research Service.

Jones, L.M., Mitchell, K.J., Turner, H.A., and Ybarra, M.L. 2018. Characteristics of bias-based harassment incidents reported by a national sample of U.S. adolescents. Journal of Adolescence 65:50–60.

Jones, L.M., Turner, H.A., Mitchell, K.J., Hamby, S., Cuevas, C., and Farrell, A., 2019. A Comprehensive Measure of Youth Experiences With Bias Victimization: Findings From the Youth Bias Victimization Questionnaire. Washington, DC: U.S Department of Justice, OJP, NIJ.

Kena, G., and Thompson, A. 2021. Hate Crime Victimization, 2005–2019. Washington, DC: USDOJ, OJP, Bureau of Justice Statistics (BJS).

Kercher, G.A., Nolasco, C., and Wu, L. 2008. Hate Crimes. Houston, TX: Sam Houston State University, Criminal Justice Center, Crime Victims’ Institute, pp. 16–21.

Killion, V.L. 2019. Terrorism, Violent Extremism, and the Internet: Free Speech Considerations. Washington, DC: Congressional Research Service.

Kilvington, D. 2021. The virtual stages of hate: Using Goffman’s work to conceptualise the motivations for online hate. Media, Culture & Society 43(2):256–272.

Kiska, R. 2012. Hate speech: A comparison between the European court of human rights and the United States Supreme Court jurisprudence. Regent University Law Review 25:107–151.

Lee, E., and Leets, L. 2002. Persuasive storytelling by hate groups online. American Behavioral Scientist 45(6):927–957.

Leets, L. 2002. Experiencing hate speech: Perceptions and responses to antisemitism and antigay speech. Journal of Social Issues 58(2):341–361.

Lennings, C.J., Amon, K.L., Brummert, H., and Lennings, N.J. 2010. Grooming for terror: The Internet and young people. Psychiatry, Psychology and Law 17:3:424–437.

Levin, B., and Amster, S. 2007. Making hate history: Hate crime and policing in America’s most diverse city. American Behavioral Scientist 51(2):319–338.

Levin, J., Rabrenovic, G., Ferraro, V., Doran, T., and Methe, D. 2007. When a crime committed by a teenager becomes a hate crime: Results from two studies. American Behavioral Scientist 51(2):246–257.

Lewis, R. 2018. Alternative Influence: Broadcasting the Reactionary Right on YouTube. New York, NY: Data & Society Research Institute.

Maertens, R., Roozenbeek, J. Basol, M., and van der Linden, S. 2020. Long-term effectiveness of inoculation against misinformation: Three longitudinal experiments. Journal of Experimental Psychology Applied 27(1):1–16.

Martell, C.C. 2018. Teaching race in U.S. history: Examining culturally relevant pedagogy in a multicultural urban high school. Journal of Education 198(1):63–77.

Matthew Shepard and James Byrd Jr. Hate Crimes Prevention Act. (2009). https://www.justice.gov/crt/matthew-shepard-and-james-byrd-jr-hate-crimes-prevention-act-2009-0

Mason, G. 2005. Hate crime and the image of the stranger. British Journal of Criminology 45:837–59.

Masucci, M., and Langton, L. 2017. Hate Crime Victimization, 2004–15: Special Report. Washington, DC: USDOJ, OJP, BJS.

McDevitt, J., Balboni, J.M., Bennett, S., and Weiss, J.C. 2012. Improving the quality and accuracy of bias crime statistics nationally: An assessment of the first 10 years of bias crime data collection. In Hate and Bias Crime, edited by S. Orchowsky and L. Walbolt. Abington, Oxfordshire, England: Routledge, pp. 95–108.

McDevitt, J., Cronin, S., Balboni, J.M., and Farrell, A. 2002. Bridging the Information Disconnect in National Bias Crime Reporting: Final report. Washington, DC: USDOJ, OJP, BJS.

McGuire, W.J. 1961a. The effectiveness of supportive and refutational defenses in immunizing and restoring beliefs against persuasion. Sociometry 24:184–197.

McGuire, W.J. 1961b. Resistance to persuasion conferred by active and passive prior refutation of the same and alternative counterarguments. Journal of Abnormal Psychology 63:326–332.

Mendez, J.J., Bauman, S., Sulkowski, M.L., Davis, S., and Nixon, C. 2016. Racially focused peer victimization: Prevalence, psychosocial impacts, and the influence of coping strategies. Psychology of Violence 6(1):103–111.

Mitchell, K.J., Jones, L.M., Turner, H.A., Hamby, S., Farrell, A., Cuevas, C., and Daly, B. 2020. Exposure to multiple forms of bias victimization on youth and young adults: Relationships with trauma symptomatology and social support. Journal of Youth and Adolescence 49:1961–1975.

Movement Enhancement Project. 2021. Policy Spotlight: Hate Crime Laws. Boulder, CO: Movement Enhancement Project.

Nolan III, J.J., McDevitt, J., Cronin, S., and Farrell, A. 2004. Learning to see hate crimes: A framework for understanding and clarifying ambiguities in bias crime classification. Criminal Justice Studies 17(1):91–105.

(OJJDP) Office of Juvenile Justice and Delinquency Prevention. n.d.a. National Crime Victimization Survey. In Compendium of National Juvenile Justice Datasets. Washington, DC: USDOJ, OJP, OJJDP. https://www.ojjdp.gov/ojstatbb/compendium/asp/Compendium.asp?selData=7

(OJJDP) Office of Juvenile Justice and Delinquency Prevention. n.d.b. Preventing Youth Hate Crimes & Identity-Based Bullying Initiative. Washington, DC: USDOJ, OJP, OJJDP.  https://ojjdp.ojp.gov/programs/preventing-youth-hate-crimes-bullying-initiative

Office of the Maine Attorney General. n.d. Civil Rights in Schools. Augusta, ME: Office of the Maine Attorney General. https://www.maine.gov/ag/civil_rights/index.shtml.

Paterson, J., Walters, M.A., and Brown, R. 2019. The short- and longer-term impacts of hate crimes experienced directly, indirectly, and through the media. Personality and Social Psychology Bulletin 45(7):994–1010.

Paz, M.A., Montero–Díaz, J., and Moreno–Delgado, A. 2020. Hate speech: A systematized review. SAGE Open:1–12.

Pezella, F.S., Fetzer, M.D., and Keller, T. 2019. The dark figure of hate crime underreporting. American Behavior Scientist, online first. https://www.semanticscholar.org/paper/The-Dark-Figure-of-Hate-Crime-Underreporting-Pezzella-Fetzer/b7f102e0ee55a03a5e680c9233b3d7459e441fd5

Polanin, J.R., Espelage, D.L., and Pigott, T.D. 2012. A meta-analysis of school-based bullying prevention programs’ effects on bystander intervention behavior. School Psychology Review 41(1):47–65.

Price, M., Polk, W., Hill, N.E., Liang, B., and Perella, J. 2019. The intersectionality of identity-based victimization in adolescence: A person-centered examination of mental health and academic achievement in a U.S. high school. Journal of Adolescence 76:185–196.

Puzzanchera, C. 2020. The Decline in Arrests of Juveniles Continued Through 2019. Washington, DC: USDOJ, OJP, OJJDP.

Rabrenovic, G. 2007. Responding to hate violence: New challenges and solutions. American Behavioral Scientist 51(2):143–148.

Regional Education Laboratory Northeast & Islands. 2020. What Evidence-Based Curriculum for Schools Exists to Combat Racism? Washington, DC: U.S. Department of Education, Institutes for Education Science. https://ies.ed.gov/ncee/edlabs/regions/northeast/AskAREL/Response/152.

Relia, K., Li, Z., Cook, S.H., and Chunara, R. 2019. Race, Ethnicity, and National Origin–Based Discrimination in Social Media and Hate Crimes Across 100 U.S. Cities. New York, NY: New York University.

Russell, S.T., Sinclair, K.O., Poteat, V.P., and Koenig, B.W. 2012. Adolescent health and harassment based on discriminatory bias. American Journal of Public Health 102(3):493–495.

Schafer, J.A. 2002. Spinning the web of hate: Web-based hate propagation by extremist organizations. Journal of Criminal Justice and Popular Culture 9(2):69–88.

Schultz, L.H., Barr, D.J., and Selman, R.L. 2001. The value of a developmental approach to evaluating character development programmes: An outcome study of Facing History and Ourselves. Journal of Moral Education 30(1):4–27.

Schweppe, J. 2021. What is a hate crime? Cogent Social Sciences 7(1):1–15.

Sinclair, K.O., Bauman, S., Poteat, V.P., Koenig, B., and Russell, S.T. 2012. Cyber and bias-based harassment: Associations with academic, substance use, and mental health problems. Journal of Adolescent Health 50:521–523.

Southern Poverty Law Center. n.d. Frequently Asked Questions About Hate Groups. Montgomery, AL: Southern Poverty Law Center. https://www.splcenter.org/20200318/frequently-asked-questions-about-hate-groups#hate%20group.

Steinberg, A., Brooks, J., and Remtulla, T. 2003. Youth hate crimes: Identification, prevention, and intervention. American Journal of Psychiatry 160(5):979–989.

Tucker, J.S., Ewing, B.A., Espelage, D.L., Green Jr., H.D., la Haye, K., and Pollard, M.S. 2016. Longitudinal associations of homophobic name-calling victimization with psychological distress and alcohol use during adolescence. Journal of Adolescent Health 59(1):110–115.

(USDHHS) U.S. Department of Health and Human Services. n.d. stopbullying.gov. Washington, DC: stopbullying.gov.

(USDOJ) U.S. Department of Justice. n.d.a. 2020 Hate Crime Statistics Released. Washington, DC: USDOJ. https://www.justice.gov/hatecrimes/facts-and-statistics

(USDOJ) U.S. Department of Justice. n.d.b. Civil Rights Division. Washington, DC: USDOJ. https://www.justice.gov/crt

(USDOJ) U.S. Department of Justice. n.d.c. Community Relations Service. Washington, DC: USDOJ. https://www.justice.gov/crs

(USDOJ) U.S. Department of Justice. n.d.d. Federal Laws and Statutes. Washington, DC: USDOJ. https://www.justice.gov/hatecrimes/laws-and-policies

(USDOJ) U.S. Department of Justice. n.d.e. Hate Crimes Data: Using Data to Address the Threat. Washington, DC: USDOJ. https://www.justice.gov/hatecrimes/spotlight/hate-crimes-data

(USDOJ) U.S. Department of Justice. n.d.f. Learn About Hate Crimes. Washington, DC: USDOJ.  https://www.justice.gov/hatecrimes/learn-about-hate-crimes/chart.

Wachs, S., Wright, M.F., and Vazsonyi, A.T. 2019. Understanding the overlap between cyberbullying and cyberhate perpetration: Moderating effects of toxic online disinhibition. Criminal Behavior and Mental Health 29:179–188.

Wang, K., Chen, Y., Zhang, J., and Oudekerk, B.A. 2020. Indicators of School Crime and Safety: 2019. Washington, DC: U.S. Department of Education, Institute of Education Sciences.

Wessler, S. 2000. Promising practices against hate crimes: Five state and local demonstration projects. Hate Crime Series No. 2. Washington, DC: USDOJ, OJP, BJA.

Williams, M.L., Burnap, P., Javed, A., Liu, H., and Ozalp, S. 2020. Hate in the machine: Anti-Black and anti-Muslim social media posts as predictors of offline racially and religiously aggravated crime. British Journal of Criminology 60(1):93–117.

Wong, J.S. 2009. No Bullies Allowed: Understanding Peer Victimization, the Impacts on Delinquency, and the Effectiveness of Prevention Programs. Dissertation submitted to the Pardee RAND Graduate School. Santa Monica, CA.

Woo, B., Pitner, R., and Wilson, B. 2021. White college students’ racial prejudice and perceptions of racial hate crime. Journal of Interpersonal Violence, published online first. https://journals.sagepub.com/doi/abs/10.1177/08862605211062987

Suggested Reference: Development Services Group, Inc. 2022. “Hate Crimes and Youth.” Literature review. Washington, DC: Office of Juvenile Justice and Delinquency Prevention. https://ojjdp.ojp.gov/model-programs-guide/literature-reviews/hate-crimes-and-youth

Prepared by Development Services Group, Inc., under Contract Number: 47QRAA20D002V.