Hate Crime Victimization and Weapon Use

Abstract

Prior research has suggested that hate crimes hurt more, in that they are more physically severe than other crimes. A separate body of research has focused on the role of weapons in exacerbating violence; yet, no research has considered the role of weapon use in bias crime victimization. Following this, this research examines the relationship between weapon use, bias motivation, and victimization in the United States. On one hand, weapons may play an important role in hate crime by exacerbating violence. On the other hand, weapons may be unnecessary for facilitating hate crime violence, given the animus associated with bias motivation. Using data from the National Incident-Based Reporting System, we find that bias crimes are both (a) less likely than nonbias crimes to involve weapons and (b) more likely than nonbias crimes to involve serious or lethal victim injury. These patterns are particularly pronounced for antisexual orientation hate crimes.

Keywords

hate crime bias crime violence victimization weapon use

A number of scholars have argued that hate crimes, which are crimes motivated by bias toward the characteristics of the victim (i.e., race, religion, sex, sexual orientation, disability, etc.), are more severe than other crimes; in other words, hate crimes “hurt more” (Iganski, 2001; Lantz & Kim, 2019). In general, scholars have pointed to three ways in which hate crimes hurt more than other crimes. First, hate crimes have a more significant impact on the community than other crimes. Put another way, hate crimes often function as a message crime, in that they are intended to convey a threatening message to a victim group, resulting in a broader community impact (Perry & Alvi, 2012). Second, hate crimes have more negative psychological and emotional effects on victims than other crimes (Herek et al., 1997). Finally, research has indicated that hate crimes are more physically severe than other crimes (Messner et al., 2004; Pezzella & Fetzer, 2017). Masucci and Langton (2017), for example, found that while approximately 90% of all hate victimizations involved physical violence (i.e., aggravated assault, simple assault, robbery, rape, or sexual assault), violence was only present in about 25% of reported nonhate crime victimizations.

One reason that hate crimes are more physically traumatic than other crimes may be that the animus behind the offense increases the brutality of bias-motivated violence (J. Levin & McDevitt, 1993). Other research, however, has noted that weapon use plays an important role in exacerbating the severity of violent victimization by facilitating increased injury and making violence easier (Wells & Horney, 2002). Indeed, while prior research has largely neglected to consider the role that weapon use may play in bias crime relative to other crimes, recent policy conversations seem to imply that weapons—and firearms in particular—may be colloquially assumed to be an important factor in such violence. More specifically, recent proposed legislation like the Disarm Hate Act has attempted to enact legislation that would prohibit individuals who have been convicted of misdemeanor hate crimes from purchasing or possessing firearms (Stockler, 2019). The legislation has been vocally opposed by those who argue that the legislation would violate the Second Amendment by expanding disarmament to misdemeanor conviction. While such legal ramifications and debates are beyond the scope of the current research, these policy efforts speak to the important need to understand what role weapons may play in hate crime violence; extant research, however, provides little empirical basis on which to structure an informed debate regarding such policy efforts.

Following this, the present research posits that it is important to consider the role that weapon use plays in hate crime and victimization. Based on prior research, the current study posits that hate crime weapon use may function in one of two ways. On one hand, given that hate crimes are often more physically severe than other crimes, and weapons relate to more severe physical trauma, it is possible that weapons play an integral role in hate crime severity. On the other hand, however, it is also possible that weapons are not a necessary component for hate-motivated violence, given that hate crimes already involve significant animus and bias toward the victim, a factor which may itself increase offense brutality. That is, weapons may play either (a) a substantial role in the increased severity of physical violence associated with hate crimes or (b) a less significant role in hate crime violence, given a willingness among those who commit hate crimes to inflict serious violence without the assistance of a weapon. Yet, despite these differential possibilities, very little research has explicitly considered the role that weapons play in hate crime violence and victimization, compared with other violent offending.

Literature Review

Prior research has consistently demonstrated hate crimes to be quantitatively and qualitatively more severe (i.e., violent) than other types of nonbias crimes (Harlow, 2005; Lantz & Kim, 2019; B. Levin, 1999; J. Levin & McDevitt, 1993; Messner et al., 2004; Perry, 2001; Pezzella & Fetzer, 2017; Strom, 2001; Weisburd & Levin, 1993). Strom (2001), for example, examined National Incident-Based Reporting System (NIBRS) data on aggravated assaults and found that 60% of bias crimes resulted in serious injury to the victim. Harlow (2005) similarly found that 84% of hate crimes in the National Crime Victimization Survey (NCVS) involved violent offenses while only 23% of nonhate crimes involved a violent offense, indicating that hate crimes are more than 3 times more likely than nonbias crimes to involve a violent offense. Likewise, a study by Pezzella and Fetzer (2017) indicated that the odds of severe physical injury in hate-related assaults were 23% greater than in nonbias assaults. Perry (2001) also found that victims characterized their injuries as “fairly serious” or “very serious” in 14% of bias crimes, compared with just 8% of nonbias crimes. Taken together, hate crimes have consistently been found to be associated with higher rates of physical violence than nonbias crimes.

Explanations for Increased Physical Trauma

One potential explanation for the increased severity of violence associated with hate crime may be the bias motivation, or inherent animus, involved in the offense. This animus may, in turn, translate to increased brutality and more severe physical trauma. J. Levin and McDevitt (1993), for example, posited that those who commit hate-motivated crime are more violent than those who commit other crimes because of the hateful views that drive their offending. Messner and colleagues (2004) also argued that those who engage in hate crime might have stronger violent and antisocial tendencies than others because they commit violence without victim provocation, producing excessively brutal outcomes. Other research has noted the role that group threat might play in hate crime offending (Blalock, 1967; Blumer, 1958). In this vein, Perry (2001) argued that the purpose of hate crimes was to “do difference” and subordinate and intimidate a victim, a motivation that may also suggest increased brutality. In this context, hate-motivated violence reflects power dynamics within a society, wherein the dominant group seeks to preserve their privileged position by targeting the more vulnerable groups through hate crime victimization. In other words, hate crimes function to punish victims for their identity (Perry, 2001). Hate crimes are thus the extension of cultural values of domination and subordination, which may extend to increased physical domination during an offense. Prior research has, for example, found that when individuals view themselves as the member of a superior in-group, they may experience both decreased guilt for their aggressive behavior and decreased empathy for their victims (Haslam et al., 2007). Taken together, this research suggests that the motivation behind bias crimes may itself be responsible for the use of more extreme or excessive violence, thereby leading to more serious victim injuries (Lantz & Kim, 2019).

At the same time, other research has suggested that weapons may play an important role in facilitating and exacerbating the physical trauma associated with violence. In general, research has indicated that, when weapons are used, injuries to the victim tend to be more severe than when weapons are not used, in part because weapons make violence easier (e.g., Wells & Horney, 2002). In this context, weapons, and guns in particular, allow individuals to detach themselves and increase emotional distance from a victim, thereby exacerbating violence (Braga et al., 2020; Wells & Horney, 2002). Emmert et al. (2018), for example, found that when an individual was in possession of a weapon during an incident, the victim tended to suffer more severe physical consequences, compared with situations where the individual did not possess a weapon. Following this, it is also possible that weapon use may play an important role in the severity of hate-motivated violence, compared with other violence. Examining this possibility is especially important given recent policy efforts attempting to prohibit individuals who have been convicted of misdemeanor hate crimes from purchasing or possessing firearms (Stockler, 2019), thereby implicitly assuming that guns play an important role in such violence. Existing research, however, provides little empirical basis on which to base such assumptions, thereby limiting our ability to structure an informed debate regarding such hate crime policy efforts.

Differences by Bias Type

While a number of researchers have argued that bias crimes are more severe than nonbias crimes, there is also reason to suspect that there is variability in the severity of violence involved for some hate crimes, compared with other hate crimes. There is substantial evidence indicating that sexual orientation hate crimes, in particular, exhibit more severe violence than other types of hate crimes (Comstock, 1991; Dunbar, 2006; Stacey, 2011; Stotzer, 2012). Despite the fact that gay and bisexual individuals compose only an estimated 3.5% of the population, sexual orientation–based hate crimes make up approximately 30% of reported hate crimes each year (Gates, 2014; Stotzer, 2012).¹ Stotzer (2012) similarly found, using Uniform Crime Report (UCR) data from 2001 to 2010, that, on average, lesbians, gay men, and bisexuals reported being victims of hate-motivated crimes against persons at rates approximately double those among Black and Jewish people. More importantly, Comstock (1991) found that injuries in sexual orientation–based hate crimes are often more severe than other crimes, resulting in excruciatingly painful lacerations, head injuries, puncture wounds, and chest wounds. Dunbar (2006) also found that sexual orientation hate crimes evidenced more serious violence than other types of hate crimes, including racial/ethnic and religious hate crimes. His research noted that aggressive tactics, such as assault and sexual assault, were frequently observed among sexual orientation–based hate crimes. Most recently, Lantz and Kim (2019) found that antisexual orientation bias crimes were roughly 53% more likely than nonbias crimes to involve serious victim injury. They also found that sexual orientation hate crimes were more severe than other hate crimes, and that such differences could not be explained by factors otherwise associated with increased violence, like the involvement of multiple perpetrators.

Prior research suggests that sexual orientation hate crimes are typically more violent and severe in nature for several reasons. Herek (1990) contends that heterosexism, or stigmatization of homosexuals, is responsible for antigay violence. In other words, homosexuals are stigmatized by heterosexuals for violating traditional gender norms, and those people who engage in sexual orientation–based hate crimes may feel the need to severely punish those that violate traditional masculinity and femininity because of their perception that homosexuality is socially and personally threatening (Berrill, 1990). Other research suggests antigay violence is an assertion of masculinity and provides an outlet for prejudiced individuals to attack homosexuals whom they view as socially deviant (Bufkin, 1999; Gruenewald & Allison, 2018; Perry, 2001). Taken together, those who commit antisexual orientation hate crime intend to “send a message to victims of these crimes that they are different or less than human” (Lantz & Kim, 2019, pp. 450–451; see also Posselt, 2017). Following this, the extreme animus associated with sexual orientation hate crimes suggests physical severity of violence may be particularly strong for such crimes, even in comparison with other hate crimes.

Current Study

The current research examines the role of weapon use in hate crime violence, focusing on the relationship between weapon use and victim injury, and drawing comparisons between bias crimes and nonbias crimes. To that end, and drawing from prior research, we investigate two competing hypotheses regarding the role that weapons might play in violent hate crime victimization. On one hand, prior research indicates both that hate crimes are more physically severe than other crimes (e.g., J. Levin & McDevitt, 1993) and that weapons facilitate physical severity (e.g., Emmert et al., 2018). Following this, weapons may play a particularly prominent role in bias crime victimization, compared with nonbias victimization (Hypothesis 1). On the other hand, previous studies have also suggested that the bias motivation underlying hate crime offending may itself be associated with increased animus and, therefore, more severe physical injury. As such, weapons may actually play a less prominent role in bias crime victimization, compared with nonbias victimization (Hypothesis 2). Taken together, the current research asks the following questions: Are hate crimes more physically severe because they are more likely to involve weapon use? Or, are hate crimes more severe because other processes render weapons unnecessary for inflicting serious violence on a victim? Finally, prior research has indicated that sexual orientation hate crimes are particularly violent, even in comparison with other hate crimes (e.g., Stacey, 2011). Following this, we expect the observed relationships between hate crime offending and weapon use to be particularly strong for such crimes (Hypothesis 3).

Method

Data

The present research uses data from the NIBRS, which provides detailed incident-level data on bias-motivated offending and other violence, weapon use, and severity of victim injury (Federal Bureau of Investigation [FBI], 2018). More specifically, we use data on all violent crimes (i.e., assault, robbery, sexual assault, homicide), from the offender, offense, and victim data segments.² Because of our focus on hate crimes, which are relatively uncommon, we use multiple years of data (2010–2016), resulting in 10,993 violent bias-motivated crimes.³ Because of the very large sample of nonbias-motivated crimes, we follow Lyons and Roberts (2014) and select a random sample of nonbias crimes equal to 5 times the number of bias crimes (N = 54,965; see also Lantz & Kim, 2019). This sampling strategy reduces the likelihood of incorrectly rejecting the null hypothesis (i.e., Type I error) as a result of inflated statistical power.⁴ As such, the total sample includes a total of 65,958 incidents; after listwise deletion of missing data, the final sample is comprised of 54,649 total violent crimes, 8,019 of which are bias-motivated.⁵

It is important to note that the NIBRS data do not currently include all agencies and jurisdictions in the United States. According to the FBI, about 46% of agencies nationwide participate in submitting incident-based data to the FBI, thus limiting their generalizability to some extent. That said, prior research has indicated that the NIBRS data are especially reliable for certain offenses, including aggravated assault and other serious violence (Addington, 2008). NIBRS is also the only national-level data containing incident-level information on bias and nonbias crime, variation in nonlethal and lethal injury, and a sufficient number of bias crimes necessary to facilitate comparisons with nonbias crimes; as such, the data represent an excellent source of information for the current analysis.

Measures

The current research uses two primary dependent measures: victim injury and weapon use. First, we create a single dichotomous measure indicating whether the victim was seriously injured or killed. An incident is coded as involving serious injury if any victim suffered from broken bones, internal injury, loss of teeth, severe lacerations, unconsciousness, or other major injuries. If the victim was not injured or only suffered a minor injury, the incident is coded as not involving a serious injury. Because homicides represent only a small fraction of offenses (<0.4%), yet are theoretically important for our research question, we combine such offenses with those involving serious injury, creating one single outcome measure indicating whether the victim was seriously injured or killed (1 = yes). We also note that the functional difference between incidents involving serious injury (i.e., internal bleeding) and death may just as likely be the result of other differences (e.g., proximity to emergency medical care) as it is to be the result of differences in the intent of those committing the crime. Second, weapon use is coded as a dichotomous measure indicating whether any weapon, including an automatic weapon, handgun, rifle, shotgun, other firearm, knife or cutting instrument, blunt object, motor vehicle, poison, explosive, and incendiary device, was used in the course of an incident. Following prior research, other incidents, including those involving hands and feet, are coded as not involving a weapon (Cunningham & Vandiver, 2018). Because of the nature of the analyses, weapon is used as both a dependent and independent measure.

Our second primary independent measure is whether an incident was motivated by bias (i.e., a hate crime). Bias motivation is measured using a dichotomous measure indicating whether the incident was motivated by bias or not (1 = yes). In the final stage of the research, in which we focus on differences between bias motivation, we also create a dummy measure indicating whether the offense was motivated by antisexual orientation bias (1 = yes), compared with other bias types (i.e., antiracial, antireligious, antiethnicity, or antidisability).⁶ In the later stages of the analysis, we introduce an additional interaction measure between the dichotomous bias motivation measure and weapon use to assess whether the relationship between bias and serious injury varies according to whether the incident involved a weapon.

The final analyses also include a number of additional control measures. First, because recent research has indicated that co-offending is related to both hate crime offending and severity of violence (Lantz & Kim, 2019), we elect not to exclude such cases from the analyses; instead, we control for whether or not an incident involved multiple individuals committing the crime (1 = yes). Because of the relationship between group and gang activity, we also include a dummy measure indicating whether any of the offenses were known to involve gang activity (1 = yes). Second, the analysis includes control measures for the sex, age, and race of all individuals involved in the incident (i.e., both alleged offenders and victims). The same coding scheme is used for both offenders and victims; because we include incidents involving multiple offenders or victims in the analyses, most of these measures are represented using proportion measures, rather than traditional dummy measures (see Lantz, 2020a, for a similar approach). Age is coded as the mean of all offenders and of all victims. Sex is coded into a proportion measure indicating the proportion of offenders or victims who were male, relative to female. A similar coding scheme was used for the coding of race, which is coded into three measures: proportion White, Black, and Other race; proportion White is used as the comparison group.⁷ Because whether a victim and offender know each other likely affects the degree of violence used during an offense (Heller et al., 1982; Lantz, 2021), we also included a dummy measure indicating whether any of the victims knew those who committed the crime. Finally, because alcohol and drug use may also facilitate violence (Laufer et al., 2006), we include a dummy measure for alcohol use (1 = yes) and drug use (1 = yes) during any offense.⁸

Analytic Strategy

The current study examines the relationship between weapon use, bias motivation, and severity of violence (i.e., victim injury) in three steps. First, we examine differences in weapon use and injury at the bivariate level. Second, we present a series of logistic regression models in which we attempt to disentangle the relationship between bias motivation, weapon use, and injury. To do so, we estimate the relationship between bias motivation and weapon use (Model 1), as well as the overall influence of bias motivation and weapon use on victim injury (Model 2). Third, we introduce an interaction term between weapon use and bias motivation to disentangle the joint influence of both characteristics on serious victim injury (Model 3). Together, these three models test the joint relationship between bias motivation, weapon use, and victim injury, speaking directly to each of our countervailing hypotheses (i.e., Hypotheses 1 and 2). Fourth, we limit the sample to hate crimes, and examine the same relationships, with a special focus on the role of weapon use for those hate crimes motivated by sexual orientation (Models 4 and 5; Hypothesis 3). Finally, we conclude by presenting sensitivity analyses in which we examine the differences between general weapon use and firearm use specifically; because results are similar for each, and general weapon use is more common than firearm use, we present results from the former models.

Results

Descriptive statistics for both the full sample and bias crime sample are presented in Table 1. Because we effectively oversample bias crimes, relative to other crimes, roughly 14.7% of the sample involves bias-motivated offenses. It is also important to note that the proportion of incidents involving serious or lethal injury is higher in the hate crime sample than in the full sample (.065 vs. .049). Weapon use is also slightly more common in the bias crime sample, compared with the full sample, at the bivariate level.

Table 1:

Descriptive Statistics

Measure	Full sample		Bias crimes		Non-bias crimes
Measure	M	SD ^a	M	SD	M	SD
Bias	0.147	—	1.000	—	0.000	—
Weapon	0.166	—	0.184	—	0.163	—
Minor injury	0.383	—	0.293	—	0.399	—
Serious/lethal injury	0.049	—	0.065	—	0.046	—
Offender characteristics
Multiple offenders	0.155	—	0.218		0.145	—
Age	31.884	13.150	32.062	14.205	31.853	12.960
Male	0.759	0.412	0.814	0.372	0.749	0.417
Black	0.355	0.474	0.282	0.440	0.368	0.478
Other race	0.019	0.133	0.025	0.152	0.018	0.129
Victim characteristics
Number of victims	1.244	0.610	1.367	0.818	1.223	0.563
Age	31.870	14.268	31.957	14.271	31.854	14.267
Male	0.435	0.475	0.658	0.449	0.397	0.469
Black	0.309	0.457	0.386	0.471	0.296	0.453
Other race	0.020	0.138	0.037	0.183	0.017	0.129
Stranger	0.203	—	0.416	—	0.166	—
Other characteristics
Alcohol	0.128	—	0.164	—	0.122	—
Drug use	0.022	—	0.025	—	0.021	—
Gang	0.005	—	0.015	—	0.003	—
N	54,649		8,019		46,630

Note. Victim/offender age, sex, and race represent proportion measures. SD = standard deviation; N = number of observations.

SDs omitted for dichotomous measures.

These relationships are examined in a multivariate framework in Table 2 using the full sample of both bias and nonbias crimes. Model 1 presents the results from a logistic regression analysis wherein weapon use is regressed on bias motivation as well as a number of additional covariate control measures. Importantly, after controlling for a number of incident characteristics, the results indicate that bias crimes are significantly less likely than nonbias crimes to involve weapon use, such that the odds of weapon use are decreased by roughly 27.3% when crime is motivated by bias (odds ratio [OR] = .727, p < .001), in comparison with those that are not motivated by bias.

Table 2:

Likelihood of Weapon Use and Serious Lethal Injury for Bias and Nonbias Crimes (N = 54,649)

Measure	Model 1: Weapon use			Model 2: Serious/lethal injury			Model 3: Serious/lethal injury with interaction
Measure	OR	p value	95% CI	OR	p value	95% CI	OR	p value	95% CI
Bias	0.727	***	[0.679, 0.778]	1.146	*	[1.028, 1.278]	1.364	***	[1.180, 1.576]
Offender characteristics
Multiple offenders	1.201	***	[1.129, 1.277]	1.508	***	[1.361, 1.670]	1.504	***	[1.358, 1.665]
Age	1.003	*	[1.001, 1.005]	0.996	*	[0.993, 1.000]	0.996	*	[0.993, 1.000]
Male	1.113	***	[1.049, 1.180]	1.858	***	[1.650, 2.091]	1.860	***	[1.652, 2.094]
Black	1.249	***	[1.175, 1.328]	1.296	***	[1.168, 1.437]	1.282	***	[1.156, 1.423]
Other race	1.140		[0.944, 1.377]	1.307		[0.966, 1.767]	1.312		[0.971, 1.773]
Victim characteristics
Number	1.498	***	[1.448, 1.550]	0.940	*	[0.887, 0.996]	0.941	*	[0.888, 0.997]
Age	1.004	***	[1.002, 1.006]	1.000		[0.997, 1.003]	1.000		[0.997, 1.003]
Male	2.113	***	[2.007, 2.226]	1.749	***	[1.595, 1.918]	1.735	***	[1.582, 1.903]
Black	1.397	***	[1.313, 1.486]	0.903		[0.812, 1.003]	0.907		[0.816, 1.008]
Other race	1.301	**	[1.091, 1.552]	0.938		[0.696, 1.265]	0.934		[0.693, 1.257]
Stranger	1.915	***	[1.814, 2.022]	0.968		[0.880, 1.066]	0.966		[0.878, 1.063]
Other characteristics
Alcohol	0.957		[0.891, 1.029]	1.647	***	[1.475, 1.838]	1.652	***	[1.480, 1.844]
Drug use	1.590	***	[1.377, 1.835]	1.330	*	[1.060, 1.668]	1.331	*	[1.061, 1.669]
Gang	1.518	**	[1.137, 2.027]	1.535	*	[1.028, 2.292]	1.558	*	[1.047, 2.319]
Weapon use
Weapon				6.316	***	[5.807, 6.868]	6.776	***	[6.172, 7.439]
Bias × Weapon							0.700	**	[0.569, 0.859]

Note. OR = odds ratio; CI = confidence interval.

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

Next, Model 2 presents results from a logistic regression analysis wherein serious victim injury is regressed on bias motivation and weapon use. The results indicate that both bias motivation and weapon use are significantly associated with an increased likelihood of serious or lethal victim injury. More specifically, compared with nonbias crimes, bias crimes are associated with roughly a 14.6% increase in the odds of serious victim injury (OR = 1.146, p = .014), net of controls. The results also indicate a very strong relationship between weapon use and serious victim injury more generally, such that incidents involving weapon use are much more likely than incidents that do not involve weapon use to involve serious injury (OR = 6.316, p < .001). Model 3 presents this same logistic regression model with the addition of an interaction term between weapon use and bias. Results indicate that this interaction term is significant and negative (OR = 0.700, p = .001), suggesting that the relationship between weapon use and victim injury varies significantly according to whether a violent incident is motivated by bias, and that this relationship is, in fact, weaker for bias crimes, compared with nonbias crimes. These results are presented graphically in Figure 1.

Figure 1:

Predicted Probability of Serious/Lethal Victim Injury by Bias and Weapon Use

There are three important patterns to note in Figure 1. First, there is a substantial overall weapon effect, in that incidents that involve weapon use are substantially more likely than those that do not involve weapons to result in serious or lethal victim injury. Second, among those incidents that do not involve weapons, bias motivation is associated with an increased likelihood of serious injury. Returning to Model 3 in Table 2, the conditional effect of bias motivation supports this assertion. When a weapon is not involved, compared with nonbias crimes, bias crimes are associated with a 36.4% increase in the odds of serious victim injury (OR = 1.364, p < .001). Finally, while bias crimes not involving weapons are more likely than other crimes not involving weapons to involve serious injury, weapons have a relative equalizing effect on this relationship, such that weapons have a greater impact on victim injury among nonbias crimes than bias crimes. In other words, weapons matter more for nonbias crimes than for bias crimes, suggesting support for the hypothesis that weapons play a less prominent role in such crimes (Hypothesis 2).

Next, Table 3 presents an examination of these same relationships, focusing on differences between antisexual orientation hate crimes and other hate crimes. Model 4, in which weapon use is regressed on antisexual orientation bias and a number of controls, indicates that such hate crimes are significantly less likely to involve weapon use, even in comparison with other hate crimes (OR = 0.794, p = .004). Furthermore, Model 5 indicates that, in comparison with other hate crimes, antisexual orientation hate crimes are much more likely to involve serious injury. Put another way, net of controls, antisexual orientation hate crimes are associated with a 54.7% increase in the odds of serious injury relative to other hate crimes. Results to this point indicate that bias crimes have an elevated risk of injury despite a decreased likelihood of weapon use generally, suggesting support for the hypothesis that these relationships would be stronger for such crimes (Hypothesis 3). Taken together, the results presented in Table 3 indicate that these patterns are especially strong among antisexual orientation hate crimes, even compared with other hate crimes.⁹

Table 3:

Likelihood of Weapon Use and Serious Lethal Injury for Bias Crimes Only (N = 8,019)

Measure	Model 4: Weapon use			Model 5: Serious/lethal injury
Measure	OR	p value	95% CI	OR	p value	95% CI
Antisexual orientation	0.794	**	[0.679, 0.927]	1.547	***	[1.248, 1.918]
Offender characteristics
Multiple offenders	1.208	**	[1.049, 1.391]	1.855	***	[1.508, 2.280]
Age	1.008	**	[1.003, 1.012]	0.987	**	[0.979, 0.995]
Male	1.156		[0.971, 1.377]	2.159	***	[1.508, 3.091]
Black	0.989		[0.861, 1.137]	1.526	***	[1.237, 1.883]
Other race	1.397		[0.974, 2.005]	1.346		[0.775, 2.339]
Victim characteristics
Number	1.315	***	[1.236, 1.400]	1.071		[0.970, 1.183]
Age	0.995	*	[0.991, 1.000]	1.006		[0.999, 1.014]
Male	1.566	***	[1.354, 1.813]	1.430	**	[1.104, 1.851]
Black	1.246	**	[1.098, 1.413]	0.654	***	[0.528, 0.808]
Other race	1.015		[0.732, 1.406]	0.722		[0.413, 1.260]
Stranger	1.482	***	[1.319, 1.666]	1.459	***	[1.207, 1.764]
Other characteristics
Alcohol	1.124		[0.965, 1.309]	1.675	***	[1.329, 2.110]
Drug use	1.516	*	[1.092, 2.103]	0.958		[0.563, 1.629]
Gang	1.583	*	[1.056, 2.372]	1.815	*	[1.069, 3.082]
Weapon				4.839	***	[3.997, 5.858]

Note. OR = odds ratio; CI = confidence interval.

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

Finally, while all weapons have the potential to distance individuals who commit a crime from the violence in which they are participating, prior research suggests that these effects are likely particularly pronounced for firearms (e.g., Wells & Horney, 2002). Recent legislative efforts, moreover, have largely focused specifically on preventing access to firearms. As such, we also conducted sensitivity analyses wherein we examined the relationships observed here for firearms specifically rather than weapons generally. Results were substantively and statistically similar. They are, in fact, even more pronounced: Bias-motivated crimes are much less likely than nonbias crimes to involve firearm use, such that hate crimes, compared with other crimes, are associated with a 63% decrease in the odds of firearm use, net of controls (OR = 0.375, p < .001). Firearm use is also significantly and positively associated with serious injury (OR = 2.396, p < .001). Finally, there is a significant negative interaction effect between bias and firearm use, suggesting that the effect of firearms is again weaker for hate crimes, compared with other crimes (OR = 0.662, p = .043). Because these relationships are similar, and general weapon use is more common than firearm use, we elected to present the results examining general weapon effects.

Discussion

Prior research has consistently found that hate crimes are more physically severe than other types of crimes, and that weapon use plays an important role in facilitating and exacerbating the physical severity of violent victimization (e.g., Emmert et al., 2018; Pezzella & Fetzer, 2017). Yet, prior research has neglected to consider the role that weapons may play in the physical severity of hate crime victimization, especially in comparison with nonbias crimes. This omission is especially important given recent policy conversations regarding restricting access to weapons for those individuals who have previously been convicted of committing hate crimes. Following this, the current research adds to prior hate crime research by exploring the role of weapon use in hate crime violence.

The results suggest four important findings. First, our results indicate that those who engage in hate crimes are significantly less likely to use a weapon than those who engage in other crimes. Second, our results indicate that controlling for weapon use, bias crimes are more likely to involve serious or lethal injury. Third, we observe a significant interaction between weapon use and bias motivation, indicating that weapon use has a smaller effect for hate crimes than other crimes. Put simply, weapon use matters less for hate crimes, compared with other crimes. Finally, we found that these patterns are particularly strong for hate crimes motivated by antisexual orientation bias.

These findings suggest that exploring the mechanisms facilitating severe violence without a weapon may provide insight into the etiology of hate crime violence. We posit that one important mechanism behind the observed relationships may be the dehumanization of hate crime victims, a process by which those who commit hate crimes strip victims of their human qualities and assign them to a subhuman status (Hagan & Rymond-Richmond, 2008; Haslam et al., 2007). Other research has noted that hate crimes function to “punish victims for their individual or collective performance of identity,” or rather for being members of groups that potential aggressors perceive as inferior or different (Perry, 2001, p. 55). Our findings suggest that it is possible that dehumanization may be “disengaging moral self-sanctions” in individuals who commit hate crimes, facilitating increased violent behavior (Haslam et al., 2007, p. 410; see also Byers et al., 1999). The disengagement of self-sanctions and accompanying relaxed moral boundaries may be allowing individuals who commit hate crimes to punish victims—who they view as inferior—with severe physical violence, even without the aid of a weapon. In addition, these dehumanization processes may vary between hate crimes. Antisexual orientation hate crimes were particularly violent and particularly unlikely to involve weapons, suggesting that dehumanization could be playing a crucial role in permitting the varying levels of violence commonly observed between types of hate crime offenses.

It is also possible that the explanation for the increased severity associated with hate crime, even when a weapon is not involved, may be partially attributable to differential motivations for nonbias crimes, compared with bias crimes. Most violent hate crime involves a desire by those who commit them to exercise power and control (Perry, 2001), a desire that is likely realized by causing injury and fear to the victim, with or without a weapon. There is significantly more variation, however, in motivations for nonbias violence. In other words, while many instances of nonbias crime are also likely to be expressive in nature, it is also likely that nonbias crime is more frequently instrumental in nature. As such, nonbias violence may involve a number of motivations other than causing harm to a victim, as is the case, for example, when an individual commits a robbery to obtain money or other goods.

Finally, it is possible that hate crimes may be more spontaneous in nature than other crimes, thus decreasing the possibility that the perpetrators have a weapon at the time of the offense. J. Levin and McDevitt’s (1993) typology of people who commit hate crimes, for example, posits that the majority of hate crimes are thrill-seeking in nature, such that they typically involve young groups of peers who are seeking excitement and “who regard hatred as cool.” Such crime is less likely to be premeditated and therefore may not offer the chance for individuals to bring a weapon to use during the offense. That said, it is important to note that those hate crimes which fit the thrill-seeking typology are typically committed by young people in groups, characteristics which we control for in the current research, and are typically less violent in nature than other hate crime types (e.g., mission). Thus, while this explanation does not necessarily explain why individuals who commit hate crime would subsequently be more likely to injure victims than those who commit other crimes, it does provide one potential explanation for the observed weapon effects.

Returning to our results more generally, we also found that the relationships we observe are particularly strong for hate crimes motivated by antisexual orientation bias. More specifically, we found that antisexual orientation hate crimes are significantly less likely to involve weapon use, even in comparison with other hate crimes. That said, and despite this decreased weapon use, antisexual orientation hate crimes are also associated with a 54.7% increase in the odds of serious or lethal injury relative to other hate crimes. In other words, individuals who commit antisexual orientation hate crimes are significantly less likely to use a weapon than those individuals who commit other hate crimes but are still more likely to inflict serious victim injury.

Some recent research by Levy and Levy (2017) found evidence that policies which exacerbate legal inequalities increase hate crimes directed at gay and lesbian victims, while those that extend legal equality reduce these hate crimes. While their research examined hate crime frequency, it is reasonable to expect that such patterns may extend to severity as well. Following this, it may be important to consider the trends that we observe within this broader context. More specifically, the data used for the current analysis span a period of time in which policy changes affecting the LGBTQ (lesbian, gay, bisexual, transgender, and queer or questioning) community were largely becoming more inclusive (i.e., 2010–2016); our results still, however, indicate that hate crimes targeting victims based on their sexual orientation often involve excessive brutality. The Trump administration, however, which began shortly after the time period examined here, has reversed many of the policies and protections extended to the LGBTQ community during the Obama administration (Berg & Syed, 2019). When taken together, the patterns observed by Levy and Levy (2017) and in the current research suggest that these policy changes may have serious consequences for antisexual orientation hate crime frequency and severity. As such, future research using more recent data should consider whether such hate crimes have become more frequent or more severe given recent policy changes which might serve to legitimate animus toward this population.

Taken together, our research indicates that individuals who commit hate crimes use weapons less frequently than those who commit other crimes, a finding that may have theoretical implications for understanding violent offending more generally, both bias-motivated and otherwise. Wells and Horney (2002) found that “guns do not require sustained [physical and psychological] effort; thus, persons would be able to do more damage to victims if they instead had a gun” (p. 266). In other words, in many cases, weapons serve to facilitate violence. Our findings, however, indicate that this may not be true for all violent offending, especially if alternative mechanisms—like animus toward the victim—otherwise exacerbate the severity of violence. Individuals who engage in hate crimes are more willing than others to use their own bodies to inflict serious victim injury without a weapon, indicating that weapons are not a necessary component of hate crime violence.

Thus, these findings imply that empirical attention to the motivation behind hate crime offending may shed important insight into offending behavior and victimization outcomes. More specifically, these results indicate that the nature of hate crime violence may be etiologically distinct from other types of violence, thereby suggesting that a promising avenue for future research may be understanding why hate crimes are different. Some research has emphasized that paying further attention to the prejudicial motivation involved in hate crimes—and how this motivation structures differences and similarities between hate crimes and other crimes—is important (Gladfelter et al., 2017), and this study lends support to that argument. The evidence from this study, in particular, suggests that attending to the bias motivation behind the incident might hold particular promise in explaining why hate crimes may be different from other crimes.

These results also have important policy implications. If bias and animus are indeed driving factors behind the high levels of hate crime violence, then policy initiatives aimed at preventing and unlearning prejudice might be particularly promising avenues for reducing hate crime violence. For example, Gaias et al. (2018) found that young children’s exposure to diverse environments and materials (e.g., multicultural books) in preschool was associated with an increased likelihood of having cross-race friends in first grade, which was then associated with an increased likelihood of cross-race friendships and decreased racial bias in third grade. In terms of preventing future hate crimes, schools could focus on increasing and fostering diverse early school environments and education. Other research suggests that diverse educational programs can also effectively target older students (e.g., Gonzalez et al., 2017). Together, this research suggests that diverse educational programs may be an important step toward reducing prejudice, thus affecting hate crime violence. Therefore, policies geared toward individuals who have committed hate crimes in the form of educational forums could “promote appreciation for diversity, friendships with out-group members, and insight into one’s own prejudice and stereotypes” (Rudman et al., 2001, p. 866). Future research should explore the impact of programs like these for unlearning prejudice, as well as their direct implications for hate crime offending.

The results presented here may also be particularly important to consider in the context of low hate crime victim reporting rates (Zaykowski, 2010). Recent research has indicated that victim reporting in the United States, compared with other countries, is both low and decreasing (Myers & Lantz, 2020). Others have noted that LGBT victims may be especially unlikely to engage with and cooperate with police (Lantz, 2020b). Our research suggests that individuals who commit hate crimes are willing to inflict serious injury without a weapon, especially toward victims of antisexual orientation hate crimes, which may be indicative of particularly high levels of animosity toward victims. Following this, one especially salient reason for low victim reporting may be a fear of retaliation or physical retribution. These results suggest that policy approaches which reduce victim fear of retaliation, like the implementation of third-party reporting centers, might be beneficial. Such centers are places, typically unaffiliated with the police, where hate crime victims can report crimes to trained individuals—anonymously if they so choose—thus reducing the risk of retaliation. These centers can be effective given proper implementation (Wong et al., 2019), but their effectiveness has not been closely examined in the United States.

Our findings also have potential implications for future hate crime legislation. Recent legislation, for example, has attempted to prevent individuals previously convicted of hate crime offenses from having access to weapons. The recently proposed Disarm Hate Act, for example, would enact legislation that would prohibit individuals who have been convicted of misdemeanor hate crimes from purchasing or possessing firearms. This legislation colloquially assumes guns to be an important factor in hate crime violence, but previous research has not considered this relationship in depth. Our results suggest that such legislation may indeed have an impact, but that reducing gun access will likely not be enough to substantially reduce hate crime violence. Of course, given the demonstrated direct effect of weapons on serious injury in this research, legislation of this nature is a step in the right direction: Individuals who have weapons when committing a hate crime are still more likely to hurt victims than those who do not. Moreover, even if guns and other weapons are not essential components of hate crime violence on average, it is possible that such legislation might be effective in reducing the most heinous hate crimes involving firearms, like the 2015 Charleston Church Shooting or the 2019 El Paso Shooting. That said, our results indicate that the average person who commits a hate crime is more willing than others to inflict serious injury even without the aid of a weapon. Thus, from a policy perspective, these results indicate that it may be just as important, if not more important, to focus on the underlying bias behind the offense. In addition to focusing on weapon use, future policy initiatives should aim to better understand and target the mechanisms behind hate crime offending (i.e., bias) as well.

The current study is, of course, not without limitations. First, we cannot explicitly measure the mechanisms responsible for the relationships observed here. While we suggest various mechanisms, like dehumanization, we cannot explicitly measure such processes. Future research should examine weapon effects and hate victimization among other data sources (e.g., Ruback et al., 2018) to directly assess these mechanisms. Second, the current research uses official data to examine the relationship between bias motivation, weapon use, and severity of violence. As such, it is possible that the hate crimes that are included in this sample are those that fit more stereotypical perceptions of hate crimes (Lantz et al., 2019). In other words, police officers often perceive “true” hate crimes as involving violence (Craig & Waldo, 1996; Lyons, 2008). However, not all hate crimes are physically violent; instead, harassment, threats, and vandalism are frequently reported as hate crimes as well (Barnes & Ephross, 1994). Given, however, that the focus of this research is on the most serious hate crimes—those involving weapon use and serious injury—and serious crimes are especially likely to come to the attention of the police (Skogan, 1984; Xie & Baumer, 2019), we think our estimates unlikely to be seriously affected by these limitations.

Conclusion

To this point, research has not explicitly considered the role that weapon use plays in hate crime violence and victimization, despite policy efforts intended to address weapon use during hate crime offenses. The current study attempts to address this gap in the literature by assessing how bias motivation might affect offending behavior, and how the use of a weapon might interact with this behavior. A fair bit of research has examined whether hate crimes are more severe; this research has, however, largely neglected to address why hate crimes are more severe than other types of nonbias crimes. This study finds that hate crimes are less likely to involve weapon use but still more likely than other crimes to involve serious injury; this is especially true for antisexual orientation hate crimes. We suggest that the dehumanization of hate crime victims, among other mechanisms, might be one factor behind these trends. By understanding the mechanisms behind hate crime offending, as this research aims to do, we may be better able to move toward accurately explaining and effectively countering hate crime violence.

Footnotes

The authors would like to thank Beth Huebner, Robert Morgan, Marin Wenger, and the anonymous reviewers for their helpful comments on this and earlier drafts of this research.

ORCID iDs

Zachary T. Malcom

Brendan Lantz

Notes

Zachary T. Malcom is a graduate research assistant in the College of Criminology and Criminal Justice at Florida State University. His research interests focus on hate crime, violence, race and crime, and victimization.

Brendan Lantz is an assistant professor of criminology and criminal justice, and director of the Hate Crime Research and Policy Institute at Florida State University. His research interests focus on hate crime, violence, victimization, race and crime, and co-offending. His work has appeared in a number of research outlets, including Journal of Research in Crime and Delinquency, Justice Quarterly, British Journal of Criminology, Criminology & Public Policy, Psychology of Violence, Aggressive Behavior, Journal of Interpersonal Violence, Criminal Justice and Behavior, Journal of Experimental Criminology, and Crime & Delinquency.

References

Addington

L. A.

(2006). Using National Incident-Based Reporting System murder data to evaluate clearance predictors: A research note. Homicide Studies, 10, 140–152. https://doi.org/10.1177/1088767905285439

Addington

L. A.

(2008). Assessing the extent of nonresponse bias on NIBRS estimates of violent crime. Journal of Contemporary Criminal Justice, 24, 32–49. https://doi.org//10.1177/1043986207312936

Allison

(2002). Missing data. SAGE.

Barnes

Ephross

P. H.

(1994). The impact of hate violence on victims: Emotional and behavioral responses to attacks. Social Work, 39, 247–251. https://doi.org/10.1093/sw/39.3.247

Berg

Syed

(2019, November 22). Under trump, LGBTQ progress is being reversed in plain sight. ProPublica. https://projects.propublica.org/graphics/lgbtq-rights-rollback

Berrill

K. T.

(1990). Anti-gay violence and victimization in the United States: An overview. Journal of Interpersonal Violence, 5, 274–294. https://doi.org/10.1177/088626090005003003

Blalock

H. M.

(1967). Toward a theory of minority-group relations. Wiley.

Blumer

(1958). Race prejudice as a sense of group position. Pacific Sociological Review, 1, 3–7. https://doi.org/10.2307/1388607

Braga

A. A.

Griffiths

Sheppard

Douglas

(2020). Firearm instrumentality: Do guns make violent situations more lethal? Annual Review of Criminology. Advance online publication. https://doi.org/10.1146/annurev-criminol-061020-021528

10.

Bufkin

(1999). Bias crime as gendered behavior. Social Justice, 26, 155–170.

11.

Byers

Crider

B. W.

Biggers

G. K.

(1999). Bias crime motivation: A study of hate crime and offender neutralization techniques used against the Amish. Journal of Contemporary Criminal Justice, 15, 78–96. https://doi.org/10.1177/1043986299015001006

12.

Comstock

G. D.

(1991). Violence against lesbians and gay men. Columbia University Press.

13.

Craig

K. M.

Waldo

C. R.

(1996). “So, what’s a hate crime anyway?” Young adults’ perceptions of hate crimes, victims, and perpetrators. Law and Human Behavior, 20, 113–129. https://doi.org/10.1007/BF01499350

14.

Cunningham

S. N.

Vandiver

D. M.

(2018). Solo and multi-offenders who commit stranger kidnapping: An assessment of factors that correlate with violent events. Journal of Interpersonal Violence, 33, 3459–3479. https://doi.org/10.1177/0886260516635320

15.

Disarm Hate Act, H. R. 2708, 116th Congress. (2019). www.congress.gov/bill/116th-congress/house-bill/2708

16.

Dunbar

(2006). Race, gender, and sexual orientation in hate crime victimization: Identity politics or identity risk? Violence and Victims, 21, 323–337. https://doi.org/10.1891/vivi.21.3.323

17.

Emmert

A. D.

Hall

G. P.

Lizotte

A. J.

(2018). Do weapons facilitate adolescent delinquency? An examination of weapon carrying and delinquency among adolescents. Crime & Delinquency, 64, 342–362. https://doi.org/10.1177/0011128717714466

18.

Federal Bureau of Investigation. (2018). Uniform crime reporting program data: National Incident-Based Reporting System, 2016. Inter-university Consortium for Political and Social Research. https://doi.org/10.3886/ICPSR37065.v2

19.

Gaias

L. M.

Gal

D. E.

Abry

Taylor

Granger

K. L.

(2018). Diversity exposure in preschool: Longitudinal implications for cross-race friendships and racial bias. Journal of Applied Developmental Psychology, 59, 5–15. https://doi.org/10.1016/j.appdev.2018.02.005

20.

Gates

G. J.

(2014). LGBT demographics: Comparisons among population-based surveys. The Williams Institute.

21.

Gladfelter

A. S.

Lantz

Ruback

R. B.

(2017). The complexity of hate crime and bias activity: Variation across contexts and types of bias. Justice Quarterly, 34, 55–83. https://doi.org/10.1080/07418825.2015.1096952

22.

Gonzalez

A. M.

Dunlop

W. L.

Baron

A. S.

(2017). Malleability of implicit associations across development. Developmental Science, 20, 1–13. https://doi.org/10.1111/desc.12481

23.

Gruenewald

Allison

(2018). Examining differences in bias homicide across victim groups. Crime & Delinquency, 64, 316–341. https://doi.org/10.1177/0011128717715735

24.

Hagan

Rymond-Richmond

(2008). The collective dynamics of racial dehumanization and genocidal victimization in Darfur. American Sociological Review, 73, 875–902. https://doi.org/10.1177/000312240807300601

25.

Harlow

C. W.

(2005). Hate crime reported by victims and police. U.S. Department of Justice, Office of Justice Programs, Bureau of Justice Statistics.

26.

Haslam

Loughnan

Reynolds

Wilson

(2007). Dehumanization: A new perspective. Social and Personality Psychology Compass, 1, 409–422. https://doi.org/10.1111/j.1751-9004.2007.00030.x

27.

Heller

M. S.

Ehrluch

S. M.

Lester

(1982). Victim-offender relationships and severity of victim injury. The Journal of Social Psychology, 120, 229–234. https://doi.org/10.1080/00224545.1983.9713216

28.

Herek

G. M.

(1990). The context of anti-gay violence: Notes on cultural and psychological heterosexism. Journal of Interpersonal Violence, 5, 316–333. https://doi.org/10.1177/088626090005003006

29.

Herek

G. M.

Gillis

J. R.

Cogan

J. C.

Glunt

E. K.

(1997). Hate crime victimization among lesbian, gay, and bisexual adults: Prevalence, psychological correlates, and methodological issues. Journal of Interpersonal Violence, 12, 195–215. https://doi.org/10.1177/088626097012002003

30.

Iganski

(2001). Hate crimes hurt more. American Behavioral Scientist, 45, 626–638. https://doi.org/10.1177/0002764201045004006

31.

Lantz

(2021). The consequences of crime in company: Co-offending, victim-offender relationship, and quality of violence. Journal of Interpersonal Violence, 36(7-8), NP4363–NP4388. https://doi.org/10.1177/0886260518786497

32.

Lantz

(2020a). Co-offending group composition and violence: The impact of sex, age, and group size on co-offending violence. Crime & Delinquency, 66, 93–122. https://doi.org/10.1177/0011128719834564

33.

Lantz

(2020b). Victim, police, and prosecutorial responses to same-sex intimate partner violence: A comparative approach. Journal of Contemporary Criminal Justice, 36, 206–227. https://doi.org/10.1177/1043986219894429

34.

Lantz

Gladfelter

A. S.

Ruback

R. B.

(2019). Stereotypical hate crimes and criminal justice processing: A multi-dataset comparison of bias crime arrest patterns by offender and victim race. Justice Quarterly, 36, 193–224. https://doi.org/10.1080/07418825.2017.1399211

35.

Lantz

Kim

(2019). Hate crimes hurt more, but so do co-offenders: Separating the influence of co-offending and bias on hate-motivated physical injury. Criminal Justice and Behavior, 46, 437–456. https://doi.org/10.1177/0093854818810314

36.

Lantz

Wenger

M. R.

(2020). Analyzing the NIBRS data: The impact of the number of records used per segment. American Journal of Criminal Justice, 45, 349–362. https://doi.org/10.1007/s12103-019-09513-4

37.

Laufer

Harel

Molcho

(2006). Daring, substance use, and involvement in violence among school children: Exploring a path model. Journal of School Violence, 5, 71–88. https://doi.org/10.1300/J202v05n03_06

38.

Levin

(1999). Hate crimes: Worse by definition. Journal of Contemporary Criminal Justice, 15, 6–21. https://doi.org/10.1177/1043986299015001002

39.

Levin

McDevitt

(1993). The rising tide of bigotry and bloodshed: Hate crimes. Plenum Press.

40.

Levy

B. L.

Levy

D. L.

(2017). When love meets hate: The relationship between state policies on gay and lesbian rights and hate crime incidence. Social Science Research, 61, 142–159. https://doi.org/10.1016/j.ssresearch.2016.06.008

41.

Lyons

C. J.

(2008). Individual perceptions and the social construction of hate crimes: A factorial survey. The Social Science Journal, 45, 107–131. https://doi.org/10.1016/j.soscij.2007.12.013

42.

Lyons

C. J.

Roberts

(2014). The difference “hate” makes in clearing crime: An event history analysis of incident factors. Journal of Contemporary Criminal Justice, 30, 268–289. https://doi.org/10.1177/1043986214536663

43.

Masucci

Langton

(2017). Hate crime victimization, 2004-2015. U.S. Department of Justice, Office of Justice Programs, Bureau of Justice Statistics.

44.

Messner

S. F.

McHugh

Felson

R. B.

(2004). Distinctive characteristics of assaults motivated by bias. Criminology, 42, 585–618. https://doi.org/10.1111/j.1745-9125.2004.tb00530.x

45.

Myers

Lantz

(2020). Reporting racist hate crime victimization to the police in the United States and United Kingdom: A cross-national comparison. The British Journal of Criminology, 60, 1034–1055. https://doi.org/10.1093/bjc/azaa008

46.

Perry

(2001). In the name of hate: Understanding hate crimes. Psychology Press.

47.

Perry

Alvi

(2012). “We are all vulnerable”: The in terrorem effects of hate crimes. International Review of Victimology, 18, 57–71. https://doi.org/10.1177/0269758011422475

48.

Pezzella

F. S.

Fetzer

M. D.

(2017). The likelihood of injury among bias crimes: An analysis of general and specific bias types. Journal of Interpersonal Violence, 32, 703–729. https://doi.org/10.1177/0886260515586374

49.

Posselt

(2017). Can hatred speak? On the linguistic dimensions of hate crime. Linguistik Online, 82, 5–25. https://doi.org/10.13092/lo.82.3712

50.

Ruback

R. B.

Gladfelter

A. S.

Lantz

(2018). Hate crime victimization data in Pennsylvania: A useful complement to the Uniform Crime Reports. Violence and Victims, 33, 330–350. https://doi.org/10.1891/0886-6708.v33.i2.173

51.

Rudman

L. A.

Ashmore

R. D.

Gary

M. L.

(2001). “Unlearning” automatic biases: The malleability of implicit prejudice and stereotypes. Journal of Personality and Social Psychology, 81, 856–858. https://doi.org/10.1037/0022-3514.81.5.856

52.

Skogan

W. G.

(1984). Reporting crimes to the police: The status of world research. Journal of Research in Crime and Delinquency, 21, 113–137. https://doi.org/10.1177/0022427884021002003

53.

Stacey

(2011). Distinctive characteristics of sexual orientation bias crimes. Journal of Interpersonal Violence, 26, 3013–3032. https://doi.org/10.1177/0886260510390950

54.

Stockler

(2019, September 11). House committee passes bill barring hate crimes convicts from owning firearms. Newsweek. https://www.newsweek.com/gun-control-hate-crimes-house-bill-1458826

55.

Stotzer

R. L.

(2012). Comparison of hate crime rates across protected and unprotected groups—An update. The Williams Institute.

56.

Strom

(2001). Hate crimes reported in NIBRS, 1997-99. U.S. Department of Justice, Office of Justice Programs, Bureau of Justice Statistics.

57.

Weisburd

S. B.

Levin

(1993). On the basis of sex: Recognizing gender-based bias crimes. Stanford Law & Policy Review, 5, 21–47.

58.

Wells

Horney

(2002). Weapon effects and individual intent to do harm: Influences on the escalation of violence. Criminology, 40, 265–296. https://doi.org/10.1111/j.1745-9125.2002.tb00957.x

59.

Wong

Christmann

Rogerson

Monk

(2019). Reality versus rhetoric: Assessing the efficacy of third-party hate crime reporting centres. International Review of Victimology, 26, 79–95. https://doi.org/10.1177/0269758019837798

60.

Xie

Baumer

E. P.

(2019). Crime victims’ decisions to call the police: Past research and new directions. Annual Review of Criminology, 2, 217–240. https://doi.org/10.1146/annurev-criminol-011518-024748

61.

Zaykowski

(2010). Racial disparities in hate crime reporting. Violence and Victims, 25, 378–394. https://doi.org/10.1891/0886-6708.25.3.378