What exactly is a hate crime in the United States (US)? A review of hate crime in five US cities

Abstract

Purpose

The paper aims to provide a critical review of how variations in the conceptualization and contextualization of hate crime across US cities might impact how their individual law enforcement agencies collect hate crime data. Media reports and political discourses present hate crime as a prevalent problem in the USA. However, this representation of hate crime in the public sphere is not reflected in the relatively low national numbers of hate crimes published annually by the Federal Bureau of Investigation.

Design/methodology/approach

Drawing primarily on the national hate crime data for the period 2008–2018, this author conducted a secondary research study of the concept, context, extent and law enforcement collection of hate crime data in five cities in the USA.

Findings

This paper is a product of some of the findings of the study, which include the definition of hate crime at the federal, state and city levels and the contextualization of hate crimes at these levels. The findings show inconsistencies in how the five cities and associated law enforcement agencies conceptualize hate crime and in how they collect and report hate crime data at local and national levels.

Originality/value

Through its analysis of how five US cities and the associated law enforcement agencies interpret and respond to hate crime data collection, with recommendations of best practices for hate crime data collection by law enforcement agencies, the paper contributes to the academic and nonacademic debate on hate crime.

Citation

Kalunta-Crumpton, A. (2024), "What exactly is a hate crime in the United States (US)? A review of hate crime in five US cities", Safer Communities, Vol. 23 No. 3, pp. 207-218. https://doi.org/10.1108/SC-12-2023-0051

Introduction

The USA has a long history of hate-motivated acts of violence, dating back to the nation’s earliest days, as illustrated in the mob lynching of African Americans and other minority racial/ethnic groups by hate groups such as the Ku Klux Klan (see Gonzales-Day, 2006). In recent years, there have been several reminders of hate-motivated attacks since the 9/11 terrorist attacks on the World Trade Center and the Pentagon. These include the May 2022 mass shooting at a supermarket in Buffalo that took the lives of 10 people, all of whom were black [1], the August 2019 mass shooting at a Walmart in El Paso that targeted Hispanics and left 23 dead and 22 wounded [2], the October 2018 mass shooting at the Tree of Life synagogue in Pittsburgh that left 11 Jewish worshippers dead [3], the June 2016 mass shooting at a gay nightclub in Orlando that left 49 people dead and at least 53 injured [4] and the June 2015 mass shooting at an African American church in Charleston (North Carolina) that left 9 black worshippers dead [5].

Despite the longstanding existence of hate-related violence in the USA, it was not until 1992 that the national reporting of hate crime statistics started (see Nolan et al., 2002). The Federal Bureau of Investigation (FBI) was charged with the task of developing a national hate crime data collection program as part of the FBI Uniform Crime Reporting (UCR) program [6]. Every year, federal and state law enforcement agencies (LEAs) submit their hate crime data to the UCR program. Thereafter, the FBI will compile and publish the data in an annual Hate Crime Statistics report. These practices were formed on the back of the 1990 Hate Crime Statistics Act, which at the time specified race, ethnicity, religion and sexual orientation as the biases for which hate crime data were to be collected. Through subsequent amendments to the act, more biases, such as disability and gender, were added to the list of bias motivations (see FBI, 2020a, 2020b).

Today, national hate crime data are collected based on the following biases: disability, gender, gender identity, race/ethnicity/ancestry, religion and sexual orientation [7]. These biases are meaningful only when captured in already existing traditional criminal offenses against a person or a property. In other words, hate crime is not a standalone crime. Rather, a hate crime occurs when any of the above-mentioned biases is displayed in the perpetration of a traditional criminal offense. The FBI (2015a, 2015b, p. 2) describes this point thus:

Hate crimes are not separate, distinct crimes, but rather traditional offenses motivated by the offender’s bias. For example, an offender may commit arson because of his or her racial bias. It is, therefore, unnecessary to create a whole new crime category. To the contrary, hate crime data can be collected by merely capturing additional information about offenses already being reported to the FBI UCR Program.

In sum, a hate crime in the USA is a criminal offense that is motivated by the perpetrator’s bias (see FBI, 1999).

Although the interaction of these two key ingredients – criminal offense and bias motivation – offers a federal description of a hate crime in its basic form, it has not unified states and police areas into operating from a standard interpretation of hate crimes. The lack of consistency in how hate is defined and what constitutes a hate crime are instances of anomalies that can impact negatively on the recording and reporting of hate crimes by LEAs across states. With a national population estimate of over 330 million [8], the USA reports a relatively low number of hate crime incidents annually. The annual national number reflects the numbers of incidents that federal and state LEAs, primarily the latter, report to the UCR. Compared to their population size, some state LEAs report low numbers, some report relatively high numbers and some do not report at all. As the discussions below will demonstrate, the variations tend to allude to differences in how states or individual LEAs define and contextualize hate crimes and to the level of significance that individual states assign to the issue of hate crime.

This paper draws on some of the findings of a secondary research study of hate crimes in five US cities – Houston, Austin (both in State of Texas), Seattle (Washington State), Washington, DC (capital of the USA), and Woodbury (State of New Jersey) – conducted by this author in 2019–2020 [9]. The primary purpose of the study was to assess the extent of incidents of hate in the City of Houston [10] with a view to devise a best practice approach to tackling and ultimately eradicating hate-motivated victimizations in the city. Prior to the start of the study, the latest FBI hate crime data were for the year 2017, and the data showed that the city reported only eight hate crimes in 2017 (FBI, 2018a). With a population size of 2,338,235 in that year, the city’s hate crime figure translates into a hate crime rate of 0.34 per 100,000 population in 2017. In 2016, the number of hate crimes recorded for the City of Houston was also eight.

These findings motivated the research study. Considering the purpose of the study to also assess best practices for hate crime data collection, the other four US cities [11] mentioned above, which reported relatively high numbers of hate crime in 2017, were purposively selected to analyze hate crime data collection practices of their individual LEAs or police departments (PDs) relative to the City of Houston Police Department (HPD). Against the purpose of the study, 11 years (2008–2018) of secondary hate crime data for Houston, Austin, Seattle, Washington, DC, and Woodbury were primarily retrieved from the FBI UCR hate crime data set and were comparatively examined [12]. Hate crime data were collected by recording on Excel the number and types of hate crime incidents that each city PD reported to the FBI UCR annually, covering the period 2008–2018. As shown in Table 1 below, the data show trends of reported hate crime incidents relative to the population of each city over the 11-year period. In addition to providing estimates on the extent of hate crimes in the individual cities, the data lend themselves to a comparative analysis of best practice in law enforcement approach to hate crime data collection and reporting.

This paper starts with an examination of how the five cities define and report hate crimes in relation to the federal definition and reporting of hate crimes. Subsequently, the paper sheds light on some of the limitations, including legislative limitations, that impact hate crime data at the national, state and city levels. A review of the limitations reveals problematics in determining what constitutes a hate crime across the country, and this situation is reflected in the varying levels of significance that individual LEAs attach to the problem. To conclude, the paper offers a few key recommendations on best practices for collecting and reporting hate crime data by LEAs.

Hate crime: concept and context

The FBI (2015a, 2015b, p. 9) issued a standard definition of hate crime, a term that the organization uses interchangeably with bias crime:

Bias Crime– A committed criminal offense that is motivated, in whole or in part, by the offender’s bias(es) against a race, religion, disability, sexual orientation, or ethnicity, gender, or gender identity; also known as Hate Crime.

This definition is aimed at attaining consensus in the interpretation of hate crime to guide individual LEAs toward a uniform hate crime data collection and reporting process. Criminal offenses that qualify for a hate crime are those that are listed under the three traditional crime categories: crimes against persons [13], crimes against property [14] and crimes against society [15]. Thus, in collecting their annual hate crime data for submission to the FBI UCR program, individual LEAs are tasked with determining if hate or bias triggered the perpetration of a criminal offense listed in any of the three crime categories.

Based on the annual hate crime data published by the FBI UCR for the period 2008–2018, the five cities under study reported annual hate crimes to the FBI UCR program. This suggests that the hate crime data that were collected by their respective PDs aligned with the FBI-approved bias motivations. Notwithstanding that, these cities’ PDs were also guided by their jurisdictional or state definitions of hate crime, which, for the most part, extended the scope of the federal definition to incorporate additional hate-motivated biases or situations. In the State of Texas, home to Houston and Austin, hate crime is defined thus:

The Texas Hate Crimes Act, Chapter 411.046 of the Texas Government Code, defines hate crimes as crimes that are motivated by prejudice, hatred, or advocacy of violence including, but not limited to, incidents for which statistics are or were kept under Public Law 101-275 (the Federal Hate Crimes Statistics Act). The federal law further defines Hate Crime as crimes that manifest evidence of prejudice based on race, ethnicity, sexual orientation, religion, disability, gender and gender identity. [Texas Department of Public Safety (TDPS) (no date)].

Not only has Texas added “advocacy of violence” to its interpretation of what motivates a hate crime, but it is also flexible regarding social groups that qualify as targets of a hate crime, beyond those allowed under the federal mandate. This is illustrated in the definition of hate crime used by the Austin Police Department (APD), wherein additional protected social groups, such as a “judge” and a “peace officer,” are incorporated. The APD’s interpretation of a hate crime reads:

An intentional criminal act committed in whole or in part because of a bias or prejudice against a person or group's (Tex. Code of Crim. Pro. art. 42.014): (a) Disability (b) Gender (c) National origin or ancestry (d) Race, ethnicity or color (e) Religion (f) Sexual orientation (g) Age (h) Peace Officer (i) Judge.[Austin Police Department (2020), p. 424].

It is unknown to this author if the APD collects data on hate crimes against peace officers and judges or age-based hate crimes. If the APD does, the data would probably serve internal (city or state) purposes only since the agency’s hate crime data submission to the FBI subscribed to the latter’s list of bias motivations. Unlike the APD, the HPD does not seem to have a hate crime definition that is different from the FBI definition. Rather, the agency adheres to the federal definition of hate crime (HPD, 2023), which requires a hate incident to qualify as a hate crime when a criminal offense “committed against a person or property” is wholly or partly motivated by the “offender’s bias against a race, religion, disability, sexual orientation, ethnicity, gender, or gender identity.” How the HPD’s conceptualization of hate crime might influence the agency’s hate crime data collection/reporting is unknown to this author.

However, as shown in Table 1 below, the relatively low prevalence rates for Austin and Houston raise critical questions regarding the actual extent of hate crimes in these cities. Based on the APD annual hate crime data for the period 2008–2018, the City of Austin shows instances of hate crime prevalence rates that are higher than those reported for Houston by the HPD and lower than those reported for Seattle, Woodbury and Washington, DC, by their respective PDs. Why would the most populous cities – Houston and Austin – report levels of hate crimes that are far lower than those reported by the least populous cities? Seattle, Washington, DC, and Woodbury, with populations lower than the populations of Houston and Austin, respectively, show prevalence rates of hate crimes that are consistently higher than the rates for Houston and Austin.

For example, in 2016 and 2017, when Houston had its largest populations of 2,334,348 and 2,338,235, respectively, the city recorded its lowest numbers of hate crimes in both years at a prevalence rate of 0.34 per 100,000 population, respectively. Austin had its lowest reported hate crime number of 4 in 2013 and in 2014. With a relatively higher population size in 2014, Austin had a hate crime prevalence rate of 0.44 per 100,000 population for that year. For Seattle, the lowest number of hate crimes was recorded in 2011, during which the city had a prevalence rate of 1.94 per 100,000 population. In 2009, Washington, DC, reported its lowest number of hate crimes, and the figure translated to a prevalence rate of 5.67 per 100,000 population. Woodbury reported its lowest number of hate crimes in 2010, and the prevalence rate was 19.01 per 100,000 population.

The variations in hate crime figures between the five cities are striking when prevalence rate is derived from the highest number of hate crimes reported in 2008–2018. Houston had its highest prevalence rate in 2008 at 1.25 per 100,000 population, and in the same year Austin recorded one of its highest rates [16] at 2.52 per 100,000 population. For the remaining three cities, their highest rates per 100,000 population were as follows: Seattle (39.22 in 2018), Washington, DC (27.62 in 2018), and Woobury [17] (330.99 in 2017). Why these cities report high numbers of hate crimes is a question that is as important as the question regarding why Houston and Austin report relatively small numbers of hate crimes.

The Seattle Police Department (SPD) has hate crime data collection procedures that are not only guided by the federal definition of hate crime but also by the state (Washington) and city (Seattle) definitions of hate crime. In addition to the statuses protected under the federal definition of hate crime, there are other statuses that the City of Seattle protect [18]. They are: homelessness, marital status, age, parental status and political ideology. Alongside the term hate crime, the SPD uses the terms bias crime and malicious harassment. These three terms are used interchangeably [19]. However, malicious harassment is used as the statutory term for crimes that come under bias or hate crime [20]. In the Seattle Police Department Manual [21] (Seattle Police Department, 2020, no pagination), hate crime or malicious harassment is defined thus:

A person is guilty of a ‘hate crime offense’ (per RCW 9A.36.080) or ‘malicious harassment’ (per SMC 12A.06.115) if, because of his or her perception of another person’s:

– race, color, religion, ancestry, national origin, gender, sexual orientation, gender expression or identity, or mental, physical, or sensory disabilities (felony)

– homelessness, marital status, political ideology, age, or parental status (misdemeanor),

he or she maliciously and intentionally commits at least one of the following acts:

– causes physical injury to another person.

– causes physical damage to or destruction of the property of another person.

– by threat, places another person in reasonable fear of harm to his or her person or property or to the person or property of a third person.

Like the SPD, the Metropolitan Police Department (MPD) [for Washington, DC] operates on hate crime data collection policies and practices that protect statuses beyond those prescribed by the FBI. This is captured in how hate crime is defined in Washington, DC (Metropolitan Police Department, 2019, p. 42):

Under the Bias-Related Crime Act of 1989 (D.C. Official Code § 22-3700 et. seq.), A hate crime is a criminal act that demonstrates an accused’s prejudice based on the actual or perceived race, color, religion, national origin, sex, age, marital status, personal appearance, sexual orientation, gender identity or expression, family responsibility, homelessness, physical disability, matriculation, or political affiliation of a victim.

The extension of the definition of hate crime beyond the status parameter set by the FBI may have an impact on the way the SPD and the MPD approach their hate crime data collection/reporting, in that their extensive coverage of hate crime bias motivations seems to suggest that these PDs give priority to the problem of hate-motivated victimization.

Despite the differences in prevalence rates across the five cities, they share some similarities in their reporting of hate crimes according to bias motivations. In the 11-year period, race/ethnicity/ancestry is the number one single-bias motivating factor for hate crimes in the cities, except for Washington, DC, where race/ethnicity/ancestry is the second bias motivation for hate crimes (see Table 2 below). In second place across the four cities is sexual orientation (first place in Washington, DC). While religion bias is in third place for Houston, Austin, Seattle and Woodbury, gender identity is the third highest reported bias for Washington, DC.

The three main bias motivations shown in Table 2 are somewhat replicated at the federal level. The federal hate crime data are a total of hate crimes reported by individual LEAs to the FBI UCR during the 11-year period. Nationally, the most common single-bias motivating factor for a hate crime in 2008–2018 is race/ethnicity/ancestry. In second place is either religion or sexual orientation, depending on the year. However, overall, religion bias is more likely than sexual orientation bias to motivate a hate crime (see FBI, 2009, 2010, 2011, 2012, 2013, 2014, 2015b, 2016, 2017, 2018a, 2019).

It is also worth noting that, at the national level, the total number of hate crimes annually was quite low relative to the annual population coverage. The national figure for single-bias hate crimes was at its lowest in 2014 (a total of 5,479, and a national population coverage of 297,926,030) and at its highest in 2008 (a total of 7,783, and a national population coverage of 306,874,326). These figures represent a national hate crime rate of 1.84 per 100,000 population in 2014 and 2.89 per 100,000 population in 2008 (FBI, 2009, 2010, 2011, 2012, 2013, 2014, 2015b, 2016, 2017, 2018a, 2019). As demonstrated in the immediate section below, data from the National Crime Victimization Survey (NCVS [22]) show that the FBI data underreport the extent of hate crime nationally. In the 11-year period, the national number of hate crimes decreased by 9% in 2018. Overall, the national figures seem to suggest that hate crime is not a significant problem in the USA, or that the reported hate crimes for the years under study underestimate the actual numbers of hate crimes for those years. This dilemma, which is demonstrated in the dubious variations in hate crime numbers reported by the five cities, is explored in the next section below.

Limitations of hate crime data

This author starts this section with a question that she raised in the preceding section, which is: why would the most populous cities – Houston and Austin – report levels of hate crimes that are far lower than those reported by the least populous cities? At a basic level, the answer to the question points to one of two explanations. It is either that Houston and Austin have insignificant problems with hate crimes or that hate crimes in these cities are underreported or under recorded. While the former viewpoint is difficult to establish, the latter is a claim that has found support in a critique of the UCR as a source of crime data, especially when compared to crime victimization data gathered from the NCVS. Victim underreporting of crime is among the limitations of the UCR as a source of crime data (see Mosher et al., 2011; Pezzella et al., 2019; Gerstenfeld, 2011; Perry, 2001, 2003).

The NCVS supplements the UCR as a source of hate crime information in that it captures victimizations that may not be reported to the police or may not qualify as a hate crime by FBI standards. Hate crime victimization data from the NCVS have consistently revealed public underreporting of hate-motivated victimizations to LEAs and, by extension, the UCR. For example, findings from a recent NCVS show that:

On average, US. residents experienced approximately 246,900 hate crime victimizations each year between 2005 and 2019. The number of hate crimes ranged from about 173,600 to 305,390 during this period. The number of total, violent, and property hate crime victimizations did not change significantly from 2005 to 2019 (Kena and Thompson, 2021, p. 3).

The findings also show that there was a significant victim underreporting of hate crimes to police. For violent hate crime alone, roughly 42% of victimizations during 2015–2019 were not reported to police. Some of the reasons for nonreporting of hate-motivated victimizations to police resemble reasons for nonreporting of crimes in general. Based on the NCVS findings regarding nonreporting of violent hate crime victimizations (Kena and Thompson, 2021, p. 6), reasons include a decision to deal with the victimization “another way, such as privately or through a non-law enforcement official,” belief “that police could not or would not do anything to help,” belief “that the crime was not important enough to report to police,” reporting would have been “too inconvenient,” or fear of reprisal. A variety of situational and social context factors, individually or interrelatedly, affect the likelihood of the public not reporting crimes to the police (see Goudriaan et al., 2004).

Not all hate-motivated victimizations reported to the police are recorded as a hate crime. An incident reported to a LEA must rise to the level of a criminal offense, and the LEA must also establish hate or bias as the motivation for the crime. In other words, there is the additional burden of proof of hate or bias that is required of LEAs to decide that a criminal activity was hate/bias-motivated. However, identifying a hate crime is not a straightforward task, principally because of the challenges in establishing hate or bias motivations. This problem is acknowledged by the FBI (2018b, p. 1) in the following statement:

Because motivation is subjective, it is sometimes difficult to know with certainty whether a crime resulted from the offender’s bias. Moreover, the presence of bias alone does not necessarily mean that a crime can be considered a hate crime. Only when a law enforcement investigation reveals sufficient evidence to lead a reasonable and prudent person to conclude that the offender’s actions were motivated, in whole or in part, by his or her bias, should an agency report an incident as a hate crime.

Thus, the relatively low numbers of hate crimes reported for Houston and Austin for the period 2008–2018 may also be attributed to nonrecording or under recording by the HPD and the APD due to difficulties in identifying hate or bias as the motivation for committing a crime.

To exacerbate the problems of nonreporting or nonrecording is the fact that there is no federal mandate on states to submit hate crime data, or data pertaining to other crimes, to the FBI UCR program, which means that the participation of states in this program is optional. It should not be surprising, therefore, if there are LEAs in individual states that report low numbers, zero numbers or do not report at all. In the case of Houston, there is evidence from community-based organizations to suggest that hate crime data reported by the HPD underrepresents the extent of hate crimes against certain groups in the city, namely, the LGBTQ [23] community and the Jewish community. Data from the Montrose Center [24] show that, for some of the years between 2008 and 2018, the HPD hate crime data on the LGBTQ community in Houston seemed to have underestimated the actual numbers of hate crimes against this group (see Kalunta-Crumpton, 2020). Likewise, it seems likely that the extent of hate crimes against the Jewish community in Houston is underrepresented, considering that Anti-Defamation League (ADL) has shown that the numbers of anti-Semitic victimizations alone tend to exceed the entire number of religion-motivated hate crimes reported by the HPD (Kalunta-Crumpton, 2020).

However, community-based organizations, such as ADL and the Montrose Center, hold broader interpretations of what constitutes hate-motivated victimization. Unlike the FBI, which limits hate crimes to incidents that rise to the level of an existing criminal offense, the Montrose Center and ADL include criminal and noncriminal incidents in their respective definitions of hate-motivated victimization. For example, in reference to the LGBTQ community, the National Coalition of Anti-Violence Programs (NCAVP) [25] (2013, pp. 11–13) acknowledges this all-inclusive approach when it states that acts of anti-LGBTQ hate violence:

[…] include but are not limited to “hate crimes,” a legal definition which refers to acts determined by law to be a crime [….] However, many acts of hate violence, such as hate speech, are not illegal, but may still have serious and traumatic impacts on the individuals who survive them, as well as their friends, families, and communities [….].

Similarly, ADL has noted that “not every anti-Semitic incident tracked by ADL constitutes a hate crime; many incidents include non-criminal acts” (cited in Kalunta-Crumpton, 2020, p. 32, HEAT Map™ | ADL).

The comprehensive approach that ADL and the Montrose Center adopt in their data collection of hate incidents does make the FBI approach seem like a limitation, in that the latter automatically excludes all hate-motivated incidents that do not involve the commission of a traditional criminal offense. With this restriction, victimization experiences of “non-criminal” hate-motivated incidents appear to be minimized, and this is likely to have a negative effect on public reporting of hate incidents, considering that victims are less likely to report if they think their victimization will not be considered a crime. Further, the task of differentiating between incidents that qualify as a hate crime and those that do not may be complicated for law enforcement officers who must assess motive to determine whether bias or hate triggered the criminal act. Because such assessment has elements of subjectivity, what constitutes a criminal hate-motivated victimization in one jurisdiction may be a noncriminal hate-motivated victimization in another jurisdiction, resulting in the nonrecording of the incident in the latter jurisdiction.

Of all the five cities, only SPD collects data on noncriminal hate incidents, in addition to data on hate crimes that the department submits to the FBI UCR program. As Tables 1 and 2 (above) show, the SPD reports relatively high numbers of hate crimes, and the information derives from a data set specifically tailored to the FBI requirements. For its internal use, the SPD has separate data sets that collect data on hate crimes (statutorily termed malicious harassment) and data on noncriminal incidents under two categories: crime with criminal elements and bias incident. Crime with criminal elements is defined as “An event in which a crime is committed that is not bias-based and during the incident the suspect uses derogatory language directed at the victim’s protected status or group,” while bias incident is defined as:

Offensive derogatory comments directed at a person’s sexual orientation, race, or other protected status which cause fear and/or concern in the targeted community during a non-criminal incident (Seattle Police Department, 2020).

Data for hate crimes and noncriminal hate incidents are combined to produce the total numbers of hate-motivated victimizations that the SPD records annually for its internal use. These numbers exceed the numbers that the agency reports to the FBI UCR. For example, in 2018, when the FBI UCR hate crime figure for Seattle was 291, the SPD internal records reported 523 criminal and noncriminal hate-motivated victimizations (see Kalunta-Crumpton, 2020). Further, because the SPD uses differing data sets and data collection requirements for the respective FBI UCR and SPD data, the SPD internal data for malicious harassment, a term used interchangeably with hate crime, are inconsistent with SPD hate crime data submitted to the FBI UCR. Using 2018 as an example (see Table 1 above), the 291 hate crimes that the SPD reported to the FBI UCR exceeded the number of malicious harassments (125) recorded by the SPD for its internal use (see Kalunta-Crumpton, 2020).

Such numerical variations are found in the MPD (Washington, DC) internal hate crime data versus the data the agency report to the FBI UCR. Like the SPD’s compliance with Seattle statute on hate crime, the MPD is guided by hate crime definitions and practices that comply with the Washington, DC, statute, including the interchangeable use of the terms hate crime and bias-related crime. In effect, the internal MPD hate crime figures are likely to differ from figures the FBI UCR receives from the MPD (see Metropolitan Police Department, 2012, 2019). The hate crime data for the period 2008–2018 illustrate this point in that the annual figures that the MPD recorded for its internal use over the 11-year period do not match the annual figures that the agency reported to the FBI UCR for that period (see Kalunta-Crumpton, 2020). Except for the year 2014, the MPD’s internal hate crime numbers for the other years were slightly higher than the numbers reported to the FBI UCR. For example, in 2008 and 2018, the figures the MPD submitted to the FBI UCR were 36 and 194, respectively (see Table 1 above). Contrastingly, the MPD internal database recorded 39 hate crimes in 2008 and 205 hate crimes in 2018 (see Kalunta-Crumpton, 2020).

Such discrepancies in hate crime numbers speak to how differences in definitions or interpretations of hate crimes can influence what and how data are collected or reported, particularly when states are not mandated to report hate crime data to the FBI UCR. As already illustrated, definitions of hate crime vary across states and jurisdictions. Thus, jurisdictions such as the APD, SPD and MPD may extend the scope of hate criminal offense or include bias motivations beyond the six federally mandated biases. While such police departmental practices may be tailored to internal departmental interest, they nevertheless speak to the wider implications of such discretionary practices on police data collection and reporting to the FBI UCR.

Concluding recommendations

The voluntariness in hate crime reporting that states enjoy is reflected in other forms of discretion that they exercise toward hate crime, which include how they define hate crime and what type of data they collect or report. Apparently, the annual national hate crime statistics published in the FBI UCR underrepresent the extent of hate crimes in the country. And as it seems, certain jurisdictions, such as Seattle and Washington, DC, make the most contributions to the annual national hate crime numbers. Considering the efforts that the SPD and the MPD (and to an extent the APD) make to address hate-motivated victimization in their respective cities of Seattle, Washington, DC, and Austin, it is unsurprising that the agencies recorded relatively high numbers of victimizations in 2008–2018.

Both the MPD and the SPD have community outreach programs that are dedicated to hate crime. This community-based approach aligns with the knowledge that most crimes that are known to the police are reported by members of the public, including crime victims. Given the fundamental role that the public plays in crime control through the reporting of crimes to law enforcement, public reporting of hate-motivated victimizations is crucial to hate crime data collection. The Special Liaison Branch of the MPD adopts a community policing approach. It has units whose primary responsibility is to provide outreach to historically underserved communities, such as the Deaf and Hard of Hearing, interfaith, LGBTQ+, African, Asian and Latino communities. Members of these respective communities sometimes notify the Special Liaison Branch of possible hate/bias-related crimes in their community (see Kalunta-Crumpton, 2020). Similarly, the SPD has the Safe Place program, an initiative that was created to focus specifically on addressing hate/bias crimes against the LGBTQ community. Having learned from the SPD Safe Place program, the APD has established its own Safe Place program to assist victims of hate crimes (Kalunta-Crumpton, 2020).

These examples of community outreach, which may have contributed to the relatively high numbers of hate-motivated victimizations that these PDs have reported over the years, are worth emulating by other LEAs. However, such initiative may not be on the radar of any LEA who minimizes the seriousness of hate crime, including its definition and the expected role of the LEA in hate crime data collection. After all, hate crime data submission to the FBI UCR is voluntary. Perhaps, to begin to address the inconsistencies in state participation in the FBI UCR program, there is the need for a national legislative mandate requiring all states to participate in an annual hate crime data reporting, including zero hate crime, to the program. As an incentive to states to take part in this venture, the federal government should assist states with resources, including funding and training.

Considering the ambiguity that the interpretation of hate crime attracts, it is advisable for both federal and state governments to expand the scope of hate-motivated victimization to include noncriminal activities. This way, LEAs will collect data on all alleged hate-motivated victimizations, regardless of whether they meet the federal definition of a hate crime, which currently restricts LEAs to specific hateful behaviors and bias motivations. As already noted, the SPD offers a promising model for data collection on criminal and noncriminal hate-motivated victimization. A record of both criminal and noncriminal victimizations has several benefits. These include increased level of public trust in the LEA for taking all hate/bias-related matters seriously, increased public reporting of hate incidents and the collection of useful information that would help LEAs identify priority areas for community outreach and hate crime prevention initiatives.

In addition to an all-inclusive approach to the collection of data on hate-motivated victimization, there is the need for a standard definition of hate crime to be universally embraced across the states. Despite the existence of a federal definition of hate crime, there are states and jurisdictions that have adopted a hate crime definition that somewhat deviates, in language or scope, from the federal definition. This point is illustrated in the definition of hate crime by the APD, SPD and MPD, each of which has its own specific definition. Against the negative implications of definitional variations for hate crime data collection across LEAs, definitional consistency seems imperative.

Table 1

Number of FBI UCR hate crimes, and city population – Houston, Austin, Seattle, Washington, DC, and Woodbury, 2008–2018

Year	Number of hate crimes and city population
	Houston	Austin	Seattle	Wash. D.C	Woodbury
2008	28 (2,238,895)	19 (753,535)	21 (598,077)	36 (591,833)	12 (10,433)
2009	14 (2,273,771)	11 (768,970)	14 (602,531)	34 (599,657)	3 (10,467)
2010	13 (2,280,859)	5 (796,310)	15 (620,195)	57 (601,723)	2 (10,527)
2011	13 (2,143,628)	5 (807,022)	12 (618,209)	79 (617,996)	7 (10,208)
2012	13 (2,177,273)	6 (832, 901)	85 (626,865)	71 (632,323)	4 (10,251)
2013	13 (2,180,606)	4 (859,180)	89 (642,814)	70 (646,449)	5 (10,073)
2014	16 (2,219,933)	4 (903,924)	107 (663,410)	68 (658,893)	15 (10,071)
2015	27 (2,275,221)	13 (938,728)	83 (683,700)	64 (672,228)	7 (9,961)
2016	8 (2,334,348)	19 (956, 911)	118 (700,313)	104 (681,170)	11 (9,937)
2017	8 (2, 338,235)	18 (971,949)	234 (721,365)	169 (693,972)	33 (9,970)
2018	25 (2,296,862)	19 (919,709)	291 (742,759)	194 (702,455)	16 (9,746)

Source:

Created by author based on figures derived from FBI (2009, 2010, 2011, 2012, 2013, 2014, 2015b, 2016, 2017, 2018a, 2019)

Table 2

City and numbers of bias motivations,^a 2008–2018

City	BIAS motivations
	Race/ethnicity/ ancestry	Religion	Sexual orientation	Gender	Gender identity	Disability	Total
Houston	82	27	61	1	7	0	178
Austin	67	13	37	0	5	1	123
Seattle	592	140	279	9	39	10	1,069
Wash. DC	341	73	425	1	102	4	946
Woodbury	98	3	12	0	0	2	115
Total	1,180	256	814	11	153	17	2,431

Note:

^aGender and gender identity categories did not exist in FBI UCR Hate Crime Statistics from 2008 to 2012. They were introduced in 2013

Source: created by author based on figures derived from FBI (2009, 2010, 2011, 2012, 2013, 2014, 2015b, 2016, 2017, 2018a, 2019)

Notes

1. In total, 13 people were shot, of whom 11 were Black. See https://buffalonews.com/news/local/complete-coverage-10-killed-3-wounded-in-mass-shooting-at-buffalo-supermarket/collection_e8c7df32-d402-11ec-9ebc-e39ca6890844.html

2. See www.justice.gov/opa/pr/texas-man-pleads-guilty-90-federal-hate-crimes-and-firearms-violations-august-2019-mass

3. See www.adl.org/resources/tools-and-strategies/shooting-pittsburgh-synagogue

4. See www.nydailynews.com/news/crime/nydn-news-crime-deadly-mass-shooting-orlando-florida-1-2670541-photogallery.html

5. See www.justice.gov/opa/pr/justice-department-announces-multi-million-dollar-civil-settlement-principle-mother-emanuel

6. The FBI UCR program reports national crime data. Law enforcement agencies may report crimes, including hate crimes, to their state UCR program, which will in turn report the data to the FBI UCR program. For additional information about the UCR, see www.fbi.gov/services/cjis/ucr

7. The FBI also collects hate crime statistics involving bias by and against juveniles.

8. See www.census.gov/quickfacts/US

9. The study, which was purposed to study hate crimes and hate incidents in the City of Houston, was commissioned by Houston Coalition Against Hate, a nonprofit organization based in Houston, Texas.

10. Fourth largest city in the USA.

11. Austin, Seattle (Washington State), Washington, DC (capital of the USA), and Woodbury (State of New Jersey).

12. In addition, data compiled by police departments for Austin, Houston, Seattle and Washington DC, and two Houston community-based organizations were collected and compared with the FBI data.

13. Murder and non-negligent manslaughter, rape, aggravated assault, simple assault, intimidation, human trafficking, other.

14. Robbery, burglary, larceny-theft, motor vehicle theft, arson, destruction/damage/vandalism, other.

15. Drug and narcotic offenses, Gambling offenses, Prostitution offenses, Weapon law violations.

16. Austin reported 19 hate crime incidents in 2008, 2016 and 2018, respectively.

17. Other than data published by the FBI, there was no additional information about Woodbury from the city’s PD.

18. Only the biases that meet the federal definition of hate crime are submitted to the FBI UCR. Data on other biases are for state and city use.

19. see www.seattle.gov/police/need-help/crimes-against-persons/hate-crimes-and-bias-crimes

20. see www.seattle.gov/spd-safe-place/understanding-hate-crimes

21. At the time of research, the latest revision was dated 04/01/2020. There is a 2023 version at: https://public.powerdms.com/Sea4550/tree/documents/2042773

22. The NCVS is one of the two major sources of nationally compiled crime data; the other is the FBI UCR. While the UCR system collects information on offenses and offenders based on the voluntary reporting of crime data from state and local LEAs to the FBI, the NCVS is a self-report victimization survey of a sample of households and people about their experiences of crime victimization. The NCVS is administered by the US Bureau of Census on behalf of the Bureau of Justice Statistics (BJS). The BJS is housed in the Department of Justice (for more information about the NCVS, visit www.bjs.gov). Hate crime was recognized in the NCVS in 2000 when questions were included in the survey to detect hate crime victims (Harlow, 2005). Unlike the UCR, the NCVS hate crime data are currently published at the national level only; hate crime data at the lower-level geography, such as the state and city levels, are not published or may not be available.

23. Lesbian, Gay, Bisexual, Transgender, Queer

24. A Houston-based community organization that collects statistical data on victimizations against the LGBTQ community.

25. Collates and publishes annual reports of national information on hate violence against LGBTQ communities based on data collected by local member organizations in different parts of the US. The Montrose Center is a member organization of the NCAVP.