Model Victims of Hate: Victim Blaming in the Context of Islamophobic Hate Crime

Abstract

Prior research has explored victim blaming in the context of hate, often depicting hate crime victims as relatively passive recipients of harassment and violence. In reality, victims often do engage with their perpetrators, and the present research explored the effect that victim behavior might have on observer reactions to Islamophobic hate crimes. Participants completed a measure of Islamophobia and read a scenario in which a White man verbally harassed a victim in the park before physically assaulting him. We manipulated both the victim’s identity (White or South Asian Muslim) and the victim’s response to the perpetrator’s verbal harassment (the victim either ignored the offensive comments, verbally reacted to them, or became physically confrontational). When the victim was portrayed as passive and nonresponding, the South Asian Muslim victim attracted lower victim blame, higher perpetrator blame, and increased certainty that the offense was a hate crime. As the victim’s behavior became more aggressive, victim blaming increased and perpetrator blaming decreased, but only for the South Asian Muslim victim. It appeared that observers scrutinized the behavior of the South Asian Muslim victim in a way they did not for the White victim, such that sympathy toward the Muslim hate crime victim was tied to his “good behavior.” We propose that observers hold expectations of the model hate crime victim, one who is a racialized, religious, or sexual minority who accepts harassment passively and with good behavior; deviation from this script results in a loss of sympathy and an increase in victim blaming. Finally, those higher in Islamophobia displayed reduced perpetrator blame, guilt, and sentences but greater victim blame when the crime targeted a South Asian Muslim as opposed to White victim.

Keywords

hate crime Muslim Islamophobia blame attribution victim blame

Hate crimes are those motivated by prejudice or antipathy toward a target victim’s group, typically on the basis of ethnicity, religion, or sexual orientation (Perry, 2001). They are often thought of as “message crimes” in that they are meant to harm not only the individual victim, but their entire community, by sending a message that they are disliked, unwanted, and unsafe (Cogan, 2002; Hanes & Machin, 2014). Some scholars have recommended the more general term, bias-motivated offense, to reflect the fact that hate crimes are those in which victims are selected due to their membership in a particular group (Chakraborti, 2010; Perry, 2001). Regardless, the presence of bias motivation in the commission of a crime is legally relevant in a number of jurisdictions, including the United States, Canada, the United Kingdom, and Australia. Typically, this takes the form of a sentencing enhancement, wherein evidence of bias motivation will extend the sentence otherwise available for a particular offense. One common justification provided for the sentencing enhancement is that hate crimes “hurt more” than comparable non-hate-based offenses (Iganski, 2001, p. 626). Indeed, accumulating empirical evidence confirms that bias-motivated offenses reflect greater brutality, physical injury, and profound psychological harm in relation to similar non-bias-motivated crimes (Herek, 2009; Iganski & Lagou, 2014; McDevitt, Balboni, Garcia, & Gu, 2001). Recently, Paterson, Walters, Brown, and Fearn, (2018) reported that victims of hate crime experienced increased feelings of anger, anxiety, vulnerability, isolation, and ongoing fear about their own security.

Despite the seriousness of hate crimes, their harmful impact on victims and communities, and the legislative recognition that hate crimes are morally serious, there is a dearth of psychological research investigating hate crimes (Nelson, Wooditch, Martin, Hummer, & Gabiddon, 2016; Perry, 2001). Moreover, little research attention has focused on how observers (hence jurors) interpret hate crimes against Muslim persons although anti-Muslim violence has risen steadily in recent years, as outlined more fully below. The purpose of the present research was to understand how observers might interpret an act of anti-Muslim violence, and particularly how attributions of blame and responsibility are made for these hate-based offenses.

Victim Blaming in the Context of Hate

Victims of all crimes may be deemed responsible for their own victimization, particularly when people believe in a just world wherein people get only what they deserve (e.g., Lerner, 1980). In some cases, perpetrators are excused for their criminal actions, whereas the victim is blamed for having provoked their own misfortune. Much of the literature exploring victim blaming has been conducted in the context of sexual assault, typically in an opposite-sex scenario with a female victim (Davies, 2002; Davies, Pollard, & Archer, 2006). There is some evidence to suggest that a model victim prototype exists within this offense category, such that greater sympathy is found for female victims who strongly resist their attacker, abstain from alcohol and substances, have limited sexual history with the perpetrator, report the assault immediately, and exhibit negative emotionality after the assault (e.g., Cohn, Dupuis, & Brown, 2009; Klippenstine & Schuller, 2012; Wenger & Bornstein, 2006). It is possible that a model victim stereotype exists for hate crimes as well, but has gone undetected due to the relatively limited research attention that this area has received in comparison with other forms of violence and crime (e.g., Nelson et al., 2016).

Alicke’s (2000) culpable control model of blaming provides a possible explanation for how observers might interpret and react to incidents of hate. This model identifies key factors associated with blame attributions in the context of harmful events. Critical to our understanding of hate crimes, Alicke proposed that observers scrutinize event information and assign blame to the person or persons who evoke the most negative reactions, or whose behavior “confirms the most unfavorable expectations” (p. 556). This model contemplates that observers make spontaneous emotional evaluations that are based on information pertaining to the actor’s intentions, behaviors, and consequences, but may also be based on extralegal factors such as the actor’s race, gender, or reputation. In other words, if the victim elicits a negative emotional reaction, those negative emotions may foster enhanced victim blaming (Alicke, Buckingham, Zell, & Davis, 2008; Cramer, Wakeman, Chandler, Mohr, & Griffin, 2013).

An emerging literature has looked specifically at victim blaming in the context of hate crimes, finding generally that the presence of hate motivation reduces victim blaming and increases perpetrator blame (e.g., Rayburn, Mendoza, & Davison, 2003; Saucier, Brown, Mitchell, & Cawman, 2006). Where hate crimes fit the stereotypical pattern of a violent assault by a White male against a racialized minority male, participants typically assign harsher sentences and higher ratings of guilt (Lyons, 2006; Marcus-Newhall, Blake, & Baumann, 2002; Saucier et al., 2006). Moreover, there is evidence to suggest that the specific group identity of the victim may not matter where the crime fits this general fact pattern, so long as the victim is a racial, religious, or sexual minority (Rayburn et al., 2003).

The existing literature on victim blaming within the context of hate crimes has not considered the potential role of victim behavior and preoffense interaction with the perpetrator. Rather, victims are typically depicted as a symbolic placeholder for a group identity. For example, Rayburn et al. (2003) depicted the victim as quietly walking home alone when attacked by two men shouting offensive slurs. Saucier and colleagues (Saucier et al., 2006; Saucier, Hockett, & Wallenberg, 2008) depicted interactions in which the perpetrator assaulted an individual while shouting slurs after only a brief verbal exchange. In another study, the victim merely said “hi” to the perpetrator in a bar and walked away, when the victim was followed and beaten (Plumm, Potter, & Terrance, 2015). Cramer, Nobles, Amacker, and Dovoedo (2013) employed a scenario in which a gay man was murdered in his own home by a coworker with whom he had no history of conflict, with the perpetrator expressing rage at the victim’s sexual orientation.

In reality, however, victims often do behave, speak, and react to offenders prior to the offense as is their right and prerogative (e.g., Poynting & Noble, 2004). The few studies that have humanized the victim by describing their behavior do indeed show an increase in victim blame. For example, Lyons (2006) found that hate crime perpetrators received higher blame ratings when the victim ignored an offensive comment but observed that perpetrator blame decreased when the victim made eye contact or spoke with the perpetrator. Plumm, Terrance, and Austin (2014) observed that perpetrators were blamed less for attacking a gay man or a Native American victim when that victim was actively marching in a group-related parade as opposed to merely watching it. Such findings suggest that hate crime victims may receive observer sympathy only when they behave within prescribed roles of model behavior.

The purpose of the present research was to explore how observers interpret and react to incidents of hate crime, and whether the tendency to engage in victim blaming is related to behavioral expectations of a model hate crime victim. Thus, we varied both the identity of the victim and his behavioral response to harassment to determine whether the influence of the victim’s behavior on observer reactions would depend upon the victim’s group identity.

A Focus on Islam

South Asian Muslims were chosen as the primary focus due to the recent increase of hate crimes targeting this community (e.g., Leber, 2017), and because this group has received relatively limited research attention in general. Following the Al-Qaeda terrorist attacks of September 11, 2001, in New York City, the United States saw a marked increase in hate crimes targeting Muslims and persons of Middle Eastern heritage (e.g., Cheng, Ickes, & Kenworthy, 2013; Disha, Cavendish, & King, 2011). These trends were observed not only in the United States, but in many other countries, including Australia (Poynting & Noble, 2004), the United Kingdom (Hanes & Machin, 2014), and Canada (Rousseau, Hassan, Moreau, & Thombs, 2011). This rise in anti-Muslim hate crime is generally believed to be related to the professed association with Islam by the 9/11 terrorist attackers (Byers & Jones, 2007; Nelson et al., 2016). In addition, anti-Muslim hate crimes in England, France, Canada, and the United States spiked in response to the November 13, 2015, terrorist attacks in Paris and the January 7, 2015, attacks on Charlie Hebdo, which were attributed to Islamic terrorists (Stack, 2016).

Similar attacks against Muslim persons and Eastern European immigrants increased in Britain following the vote to leave the European Union (e.g., Forster, 2016), and following the election of Donald Trump to the presidency of the United States (Wendling, 2016). The most recent estimates from Statistics Canada indicate that anti-Muslim hate crimes rose by 61% in 2015, compared with a 17% decrease in crimes targeting Jewish persons and a 9% decrease in hate crimes targeting sexual orientation (Leber, 2017). This increase in attacks on innocent Muslim persons for the crimes of unrelated terrorists who share only a nominal religious identity is a clear example of what has been termed vicarious retribution (Lickel, Miller, Stenstrom, Denson, & Schmader, 2006). The present research investigated whether anti-Muslim hate crimes might be viewed comparably with other forms of hate crime and explored the potential role of victim behavior in these reactions. How might a South Asian Muslim victim’s preoffense behavior be viewed in comparison with a White victim’s preoffense behavior? Are there indeed expectations for a model hate crime victim, and how might these influence observers’ perceptions of blame?

Pilot Study

Before exploring the impact of victim’s preoffense behavior and expectations of model victims, we felt it prudent to verify whether Muslim victims are indeed considered comparable with other hate crime victims, who may be viewed as more traditional targets of hate crime and who have been the focus of scholarly attention (i.e., Black and gay targets). As noted, Muslims are a relatively new target of hate and potentially occupy a unique position in North America due to the recent rise of terrorism attributed to Islamic extremists (Byers & Jones, 2007; Nelson et al., 2016). A pilot study was thus conducted as a preliminary step, comparing observer reactions to hate crimes targeting a victim depicted as either Black, gay, Muslim, or White (as a baseline comparison group), with a scenario comparable with those used in prior research on victim blaming in the context of hate (i.e., a relatively passive victim).

Two hundred twenty-two participants for the pilot study were recruited from a large Canadian university. Ten participants were dropped due to inattentive responding (n = 7) or poor English comprehension (n = 3), resulting in a final sample of 212 participants (105 men, 104 women, three undisclosed; M_age = 19.51 years, SD = 4.13). Participants read one of the four possible vignettes describing an assault committed by a White man against a male victim who was identified as either White, Black, Muslim, or gay. In the scenario, the victim was walking home from a community center when he was followed by the defendant. The victim was then attacked from behind, and witnesses reported that they overheard the defendant making “offensive comments and slurs” about the victim’s identity. All vignettes employed an identical script, differing only in the description and name of the victim, as well as his attire (e.g., varsity t-shirt and baseball cap for the White condition, a Black power t-shirt showing a raised fist for the Black condition, short-knitted skull cap, a long white robe, and a full beard for the Muslim condition, t-shirt with a rainbow emblem for the gay condition), and who they were meeting with (members of a study group, members of a Black students association, members of a Muslim students association, members of a gay and lesbian students association). As well, the victim claimed that the individual began taunting him, shouting what he believed to be offensive and insulting comments (again tailored to condition: uttering personal insults, uttering anti-Black comments, uttering offensive comments about Muslim persons, uttering offensive comments about gay persons). He told the man to “get lost,” but otherwise ignored him and continued walking on his way. The victim was then assaulted from behind and suffered moderate physical injuries. The assailant was apprehended by police the next day and charged with assault.

After reading the vignette, participants reported the degree to which they believed the event was a hate crime, and completed several measures assessing victim and perpetrator blame. The data were analyzed with univariate analyses of variance with victim identity as the independent variable. Crimes targeting a White victim were rated as less likely to be a hate crime (M = 4.66, SD = 1.62) than were crimes targeting a Muslim (M = 6.30, SD = 1.29), Black (M = 6.12, SD = 1.34), or gay victim, M = 6.44, SD = 1.01; F(3, 208) = 20.39, p < .0001, η² = .227. Post hoc analyses confirmed that the White control condition differed significantly from the minority victim conditions (all ps < .05), which did not differ from each other. Although victim blaming was low in all conditions, the Black (M = 2.11, SD = 0.86), gay (M = 1.97, SD = 0.91), and Muslim (M = 2.08, SD = 0.96) victims received less blame than did the White victim, M = 2.55, SD = 0.85, F(3, 208) = 4.41, p = .005, η² = .06. Again, all minority conditions differed from the White control, but did not differ from each other. Participants’ ratings of perpetrator blame were not influenced by the victim’s identity, but participants’ ratings of perpetrator blame were very high regardless of the victim’s identity, suggesting a possible ceiling effect related to the events depicted in the vignette.

The Present Research

The results of the pilot study indicate that Muslim victims are indeed viewed as comparable victims of hate crime, in much the same way as Black or gay victims. Consistent with prior literature examining reactions to hate crimes, the specific identity of the victim did not matter as much as the fact that the victim was a minority (e.g., Rayburn et al., 2003; Saucier et al., 2006). What is unclear is whether these conclusions may be restricted to circumstances in which a White male attacks a minority victim in the context of an unprovoked assault. The purpose of the present research was to explore what might occur when the victim is portrayed less passively. What might happen if the victim did not ignore the harassment, but actually defended himself or herself or engaged in verbal interaction with the perpetrator? Under the Culpable Control Model (Alicke, 2000), observers are thought to assign blame to persons who elicit the most unfavorable reaction or who confirm negative expectations. Thus, victims who elicit negative reactions may also attract increased blaming (Alicke et al., 2008; Cramer, Nobles, et al., 2013).

There is also evidence that prior biases can affect how observers react to hate crimes. For example, Saucier et al. (2008) found that those with higher levels of anti-Black bias gave lower sentences to Whites who attacked a Black victim and imposed harsher sentences against Blacks who attacked White victims. Similarly, Saucier, Hockett, Zanotti, and Heffel (2010) found that those with anti-Black attitudes recommended higher sentences for Black, as opposed to White, perpetrators who committed an aggravated assault. Finally, Plumm, Terrance, Henderson, and Ellingson (2010) found that those who were unsupportive of the gay community, in general, showed greater victim blaming in an antigay hate crime than did those more supportive of the gay community. An additional purpose of the current research was thus to explore the role of Islamophobic attitudes in predicting reactions to Islamophobic offenses.

How might observer reactions differ where the victim interacts with the perpetrator prior to the offense? We hypothesized that observers hold expectations for how an “appropriate” hate crime victim should behave. Victims who remain quiet and passive without emotional display were expected to receive the benefit of a victim halo, in which victim blaming would be low, perpetrator blaming would be high, and the crime would elicit negative emotional reactions from observers. The study was conducted to explore these possibilities in more depth. The identity of the victim was manipulated to be either White or South Asian Muslim, and his or her behavioral reaction to harassment was either passive, verbally responsive, or physically confrontational.

We hypothesized a main effect of victim identity, such that crimes targeting a South Asian Muslim victim would more likely be interpreted as a hate crime, would be considered more offensive, and would attract lower victim blame. We also hypothesized a main effect of victim behavior, such that as the victim’s reaction became more aggressive, participants would be less likely to interpret the crime as a hate crime and would impose greater victim blame. Finally, an interaction was predicted between victim identity and behavior, such that when the victim was Muslim and portrayed as passive (what we refer to as the “model” hate crime victim), a protective halo would emerge around the victim leading to reduced victim blame and increased perpetrator blame. When the Muslim victim broke out of the prescribed victim role and responded either verbally or physically, the halo effect was expected to dissipate. Finally, we hypothesized that victim identity would interact with group-based prejudice, such that those with more Islamophobic attitudes would show more victim blaming and less perpetrator blaming when the crime targeted a South Asian Muslim versus a White victim.

Method

Participants

Participants were recruited from a large Canadian university. After removing participants due to inattentive responding (n = 4) or poor comprehension of English (n = 3), the final sample consisted of 313 participants (155 men, 158 women) with an average age of 20.22 years (SD = 4.51). The sample showed a wide range of ethnic diversity, with 41.99% identifying as South Asian/Middle Eastern, 23.08% identifying as White, 18.59% identifying as East Asian, 9.94% identifying as Black, and 6.41% identifying as a different or mixed ethnicity. The sample also showed wide diversity in religious affiliation, with 32.26% identifying as Christian, 20.97% identifying as atheist/agnostic, 16.77% as Muslim,¹ 8.39% as Sikh, 8.39% as Hindu, 4.52% as Buddhist, 3.55% as Jewish, and 5.16% identifying with a different religious faith.

Materials

Vignettes

Participants were randomly assigned to read one of the six vignettes in this 2 (victim identity: South Asian Muslim vs. White) × 3 (victim reaction: no response, verbal response, physical confrontation) between-subjects factorial design. The vignette described a hypothetical set of events in which a White man was walking through a public park when he observed a young man, either White or South Asian Muslim (depending on condition) who appeared to be holding a demonstration with several friends. The defendant claimed that the group was too disruptive, shouting at them that if they disliked the neighborhood they should leave it, and that Toronto would be better off without “people like them.” The response of the victim then took one of the three forms: (a) he ignored the comment, (b) he responded with an angry verbal comeback, or (c) he responded with an angry verbal comeback and physically approached the defendant, shoving him backward. In all conditions, the defendant then struck the victim repeatedly and later claimed he was acting in self-defense. Please see the appendix section for stimulus materials.

Reactions to the offense

Participants were provided with the legal definition of a hate crime as used at the sentencing stage in Canada (s. 718.2(a)(i) of the Canadian Criminal Code). This provision states that a sentence should be increased where there is “evidence that the offence was motivated by bias, prejudice, or hate based on race, national or ethnic origin, language, colour, religion, sex, age, mental or physical disability, sexual orientation or any other similar factor.” Participants were then asked to rely on this definition to determine whether a hate crime had occurred (yes/no) and to report how certain they were of this decision on a 7-point scale (1 = not at all certain to 7 = completely certain). Guilty verdicts were then coded +1, and Not Guilty as −1. These verdicts were multiplied by the certainty score to form a continuous scalar measure that ranged from −7 (certain this was not a hate crime) to +7 (certain this was a hate crime).

Reactions to the targets

To assess both cognitive and affective dimensions of blaming, participants were asked to complete six items that assessed their overall emotional reaction to the victim (1 = very negative to 7 = very positive, reverse coded), the degree to which they felt sympathy for the victim (1 = not at all to 7 = completely, reverse coded), anger toward the victim (1 = not at all to 7 = completely), his or her responsibility for the assault (1 = not at all to 7 = completely), whether he or she provoked the defendant’s actions (1 = not at all to 7 = completely), and whether he or she did something to deserve the attack (1 = not at all to 7 = completely). All ratings were provided on 7-point scales, with higher scores reflecting greater victim blaming. These six items were summed and averaged to form a composite measure of victim blame (α = .85). Similarly, participants completed parallel ratings for the perpetrator: emotional reaction to the perpetrator, sympathy for the perpetrator (reverse coded), anger toward the perpetrator, his or her responsibility for the assault, degree to which he or she felt threatened (reverse coded), whether the events were attributable to his or her actions, and the unreasonableness of his or her behavior. These items were summed and averaged for a composite measure of perpetrator blame (α = .82). Note that the targets were identified only by their names and were not labeled as “victim” or “perpetrator” to avoid any unintended influence on ratings.

Islamophobia

Participants completed a shortened version of Imhoff and Recker’s (2012) Islamophobia scale (α = .70; e.g., “Islam is an archaic religion, unable to adjust to the present”). To reduce participant fatigue, we selected items that assessed participants’ views that Islam is an outdated, nonprogressive and violent religion. These items tapped into more overt Islamonegative attitudes, which were of most interest to the present research. Questions assessing more secular critiques, political opposition, or subtle aversion to the faith were excluded as it was unclear whether they tapped into Islamonegativity specifically or into more complex and fluctuating political attitudes.

Results

The impact of victim identity (Muslim vs. White), victim behavior (ignore comment, verbal response, or physical confrontation), and participant Islamophobia on our key dependent measures were examined by conducting analyses of variance of the two categorical factors (victim identity, victim reaction), and the one grand-mean-centered continuous factor (Islamophobia). The default analysis of covariance yields F ratios for the categorical factors and their interaction, as well as one for the covariate, but does not routinely output F ratios for the interactions involving the covariate. To obtain a complete factorial output, it is necessary to run a custom analysis that adds the relevant interactions between the continuous variable and the categorical effects as demonstrated by Gardner (2007, 2008). The custom analysis yields intercepts for each of the cells in the two by three table, referring to them as the expected cell means. Given that the continuous variable was grand-mean-centered, these intercepts correspond to the expected means for that cell. The analysis does not yield the expected slopes for each cell, but they can be calculated using the regression coefficients based on dummy coding.

Marginal values for both the intercepts and slopes can be computed as the unweighted mean values across each of the two categorical factors (Gardner, 2008). This data analytic strategy provides F values identical to those obtained through multiple regression with the continuous variable grand-mean centered, and effect coded vectors for the categorical factors. The results of the analysis of variance for each of the dependent measures are presented in Table1 and summarized in the following text below.

Table 1.

Main Effects and Interactions for Key Dependent Measures.

	df	F	p	η²_p
Victim blame
Identity	1	27.79	.001	.085
Reaction	2	32.29	.001	.177
Islamophobia	1	32.51	.001	.097
Islamophobia × Victim identity	1	7.71	.006	.025
Islamophobia × Victim reaction	2	0.46	.633	.003
Identity × Reaction	2	3.73	.025	.024
Victim Identity × Reaction × Islamophobia	2	1.79	.168	.012
Error	301
Perpetrator blame
Identity	1	7.69	.006	.025
Reaction	2	8.19	.001	.052
Islamophobia	1	19.02	.001	.059
Islamophobia × Victim identity	1	5.61	.018	.018
Islamophobia × Victim reaction	2	0.61	.543	.004
Identity × Reaction	2	3.44	.033	.022
Victim Identity × Reaction × Islamophobia	2	0.79	.454	.005
Error	301
Hate crime guilt (scalar measure)
Identity	1	48.03	.001	.138
Reaction	2	1.84	.161	.012
Islamophobia	1	0.82	.365	.003
Islamophobia × Victim identity	1	6.20	.013	.020
Islamophobia × Victim reaction	2	2.01	.136	.013
Identity × Reaction	2	1.31	.272	.009
Victim Identity × Reaction × Islamophobia	2	0.97	.381	.006
Error	301
Sentence
Identity	1	0.81	.369	.003
Reaction	2	4.43	.013	.029
Islamophobia	1	2.75	.098	.009
Islamophobia × Victim identity	1	10.93	.001	.035
Islamophobia × Victim reaction	2	1.41	.246	.009
Identity × Reaction	2	0.76	.467	.005
Victim Identity × Reaction × Islamophobia	2	0.35	.707	.002
Error	297

Note. Error degrees of freedom vary for sentences, as four participants failed to provide a sentence.

Victim Blame

As seen in Table 1, we obtained significant findings for our three main effects (victim identity, victim reaction, and Islamophobia), as well as the Islamophobia × victim identity interaction, and the victim identity × victim reaction interaction. In terms of the main effect of victim identity, F(1, 301) = 27.79, p = .001, victim blaming was lower for South Asian Muslim victims (M = 3.72, SD = 1.15) compared with White victims (M = 4.29, SD = 1.06). The main effect for victim reaction, F(2, 301) = 32.29, p = .001, revealed that victim blaming was lowest when there was no reaction (M = 3.44, SD = 1.16) and became progressively higher as the victim responded verbally to harassment (M = 4.06, SD = 1.07) and even further when the victim became physically confrontational (M = 4.51, SD = 0.89). Post hoc tests using a Bonferroni error correction revealed that all three behavioral conditions differed significantly from each other (all ps < .01). The main effect of Islamophobia, F(1, 301) = 32.51. p = .001, was also significant and is a test that the mean slope of victim blaming on Islamophobia (b = .261) differed significantly from 0, indicating that participants with higher levels of Islamophobia had higher victim blaming scores overall.

Focusing on the two significant interactions, the interaction of victim identity × victim reaction, F(2, 301) = 3.73, p = .025, is presented in Figure 1. Simple main effect analyses revealed that victim blaming was significantly lower for the South Asian Muslim victim than the White victim in the passive response, F(1, 301) = 28.54, p = .001, and verbal response conditions, F(1, 301) = 4.52, p = .03. In the physically confrontational condition, blaming did not differ between South Asian Muslim and White victims, F(1, 301) = 1.87, p = .17. The interaction of Islamophobia × victim identity was also significant, F(1, 301) = 7.71, p = .006, indicating that overall the slope of victim blame on Islamophobia was greater for South Asian Muslim victims (b = .388) than for White victims (b = .134). In other words, those higher in Islamophobia assigned more blame to South Asian Muslim victims than to White victims.

Figure 1.

Victim blame as a function of victim identity and victim behavioral reaction.

Perpetrator Blame

The results for perpetrator blame are a near mirror reflection of those obtained for victim blame. A main effect of victim identity was seen, F(1, 301) = 7.69, p = .006, wherein higher blame was assigned to the perpetrator who attacked a South Asian Muslim victim (M = 4.75, SD = 1.02) compared with a White victim (M = 4.46, SD = 0.99). A main effect of victim reaction emerged as well, F(2, 301) = 8.19, p = .001, wherein perpetrator blame was highest when the victim’s response was passive (M = 4.81, SD = 0.99) and became lower as the victim was verbally responsive (M = 4.70, SD = 1.07) or physically confrontational (M = 4.30, SD = 0.89). Post hoc analyses were performed using a Bonferroni error correction, which revealed that while the passive and physically confrontational conditions differed significantly from each other, the verbal reaction condition failed to differ from either of these two conditions. A main effect of Islamophobia, F(1, 301) = 19.02, p = .001, revealed that those higher in Islamophobia assigned lower blame for perpetrators overall (b = –.208), such that the slope of Islamophobia differed significantly from zero and suggesting that Islamophobia was associated with lower perpetrator blame overall.

The significant interaction between victim identity × victim reaction, F(2, 301) = 3.03, p = .033, is presented in Figure 2. Simple main effect analyses revealed that perpetrator blaming was significantly higher for the South Asian Muslim victim than the White victim in the passive response condition, F(1, 307) = 12.91, p < .001, but not in the verbal response, F(1, 307) = 0.73, p = .394, or physical confrontation condition, F (1, 307) = .003, p = .954. Again, perpetrator blame was not as strongly influenced by victim behavior when the victim was White, suggesting a greater scrutiny of the South Asian Muslim’s behavior. We also observed an interaction between Islamophobia and victim identity, F(1, 301) = 5.61, p = .018, indicating that the overall slope of perpetrator blame on Islamophobia was stronger in the Muslim victim condition (b = –.305) than in the White victim condition (b = –.090).

Figure 2.

Perpetrator blame as a function of victim identity and victim behavioral reaction.

Hate Crime Guilt

Victim identity emerged as the sole main effect predicting the scalar measure of hate crime guilt: Participants were more certain the event was a hate crime if the victim was a South Asian Muslim man (M = 0.50, SD = 5.34) than if he was White, M = −3.43, SD = 4.71; F(1, 301) = 48.03, p < .001. This main effect, however, was qualified by an interaction between Islamophobia and victim identity, F(1, 301) = 6.20, p = .013, wherein Islamophobia was more strongly and negatively associated with certainty of guilt in the South Asian Muslim victim condition (b = –.811) compared with the White victim condition (b = .378). That is, those higher in Islamophobia were less likely to interpret the anti-Muslim offense as hate based. No other main effects or interactions reached statistical significance.

Sentence

A main effect of victim behavior emerged for recommended sentence, F(2, 297) = 4.43, p = .013, such that harsher sentences were recommended for assaults against the passive victim (M = 1.60 years, SD = 1.33 years) compared with the verbally responsive victim (M = 1.23 years, SD = 1.26 years) and physically confrontational victim (M = 1.04 years, SD = 1.29 years). Post hoc analyses revealed that only the passive and physical confrontation conditions differed significantly from each other (p = .003). An interaction between Islamophobia and victim identity also emerged, F(1, 297) = 10.93, p = .001. Examination of the slopes revealed that Islamophobia was negatively associated with sentencing decisions in the South Asian Muslim condition (b = –.306), whereas it was only weakly and positively related to sentencing decisions in the White control condition (b = .102). That is, participants higher in Islamophobia imposed a lighter sentence on perpetrators who assaulted a South Asian Muslim victim. No other terms or interactions emerged as significant.

Discussion

The results of this research suggest that both victim identity and behavior are important factors influencing observer reactions to hate crime. Where the victim is depicted as a passive South Asian Muslim man who ignores harassment, victim blaming was lower and perpetrator blaming was higher than where the victim is a passive White man. Where the victim engaged with his harasser, either verbally or physically, these minority-protective responses dissipated and the minority victim was no longer viewed any differently than the White victim. With regard to blame evaluations, it appears that participants scrutinized the behavior of the South Asian Muslim victim to a much greater extent than the White victim.

In addition, a consistent interaction between observer Islamophobic attitudes and victim identity emerged for all key dependent measures. Those higher in Islamophobia showed higher victim blaming, lower perpetrator blaming, lower sentences, and reduced hate crime guilt ratings when the victim was depicted as a South Asian Muslim man as opposed to a White man. Determinations that the offense was hate motivated were related primarily to victim identity; victim behavioral reactions were unrelated to observer interpretation of the offense as hate based.

These findings provide important insight into observer reactions to hate crimes, particularly those targeting Muslim men. Our pilot research established that Muslim men were viewed comparably to other hate crime targets (i.e., Black or gay males), particularly in the context of a victim who ignores offensive comments and is assaulted by a clearly biased attacker. Our main study confirmed that anti-Muslim crimes were more likely to be interpreted as hate-based than those targeting a White victim, although those high in Islamophobia were less willing to interpret an anti-Muslim attack as a hate crime. In addition, our main study made the novel finding that victim blame and perpetrator blame are influenced by the victim’s behavioral reaction, but most particularly for a South Asian Muslim victim.

A large percentage of our participant sample identified as Muslim. As indicated in Note 1, we ran our analyses both with and without these participants included, observing similar but nonsignificant trends when the Muslim participants were excluded. This finding warrants some consideration. It is possible that excluding Muslim participants reduced the data to nonsignificance simply due to a reduction in statistical power resulting from the loss of 17% of the data. It is also possible that the Muslim participants were driving the effects we observed, a finding that was not hypothesized. Such an outcome might be explained as analogous to a “black sheep effect,” wherein observers view deviant ingroup members more negatively than outgroup members (Marques, Yzerbyt, & Leyens, 1988). Thus, Muslim participants theoretically might be showing more negative responses to the aggressive Muslim victim than to the White victim. This possibility can neither be verified nor ruled out based on the present data and will require additional research.

The present research has implications for the legal treatment of hate crimes, as well as lay reactions and victim willingness to report hate crimes to police. Hate crimes are consistently underreported in comparison with parallel, nonhate-based offenses, with estimates suggesting that only 20% to 30% of hate crimes are reported to police (Dauvergne & Brennan, 2011). McVeigh, Welch, and Bjarnason (2003) noted that the decision to report a hate crime to the police is based on several factors, including the willingness and ability of the victimized group to come forward, the resources and motivation of the police department to investigate hate crimes, and the existence of mandated hate crime data collection. Poynting and Noble (2004) documented the reluctance among Muslim persons to report hate crimes to the police out of concern that they will not be taken seriously, or due to their experiences with systemic racism and Islamophobia. The present research also illuminates on whether witnesses to hate crime will intervene or report the offense to police. If witnesses or bystanders are interpreting the offense differently based on their expectations of “true” victims of hate, they may be less likely to report offenses that deviate from their expectations. It is critical to understand whether prior interactions between victims and attackers further reduce the likelihood that such attacks are reported. The current results are an important first step toward understanding how observers interpret events as hate crimes as opposed to non-hate-based crimes, and the possibility that sympathy may be extended only to model victims who behave within a prescribed role.

One limitation of this research involves the use of a vignette and questionnaire method to assess reactions to hate crime. Reading about a violent hate crime lacks external validity in comparison with direct observation of the event itself or the experience of sitting on a jury. The use of an in-lab approach was preferred as a first step to isolate key variables of interest. Future work might include video reenactments of a hate crime, an audio recording, or a more courtlike setting with transcripts or video. In addition, the content of the vignette itself warrants examination. The vignette in the main study presented the victim as holding a demonstration to raise awareness for issues affecting his or her community. This may have presented the victim in a more positive and prosocial way and may have sensitized participants to racial or religious discrimination. If anything, however, this provided a more conservative test of our hypotheses and strengthens our conclusions. Presenting the victim in a less sympathetic context, perhaps showing them engaging in criminal behavior or presenting them in less flattering way might lead to more pronounced effects.

Another potential limitation of this study is the use of a university sample, which may be systematically different from the Canadian population to which we wish to generalize. With this in mind, we note that our sample showed wide diversity in ethnicity, race, and religious affiliation, with a nearly even representation of men and women. We believe that this diversity somewhat allays concerns about the representativeness of our student sample, although we do acknowledge that our sample may be younger and potentially more educated than the population in general. There is some evidence that university samples may differ from community samples on punitiveness, authoritarianism, blame attributions, and evidence comprehension (Hosch, Culhane, Tubb, & Granillo, 2011; Kerr & Bray, 2005; Weiner, Krauss, & Lieberman, 2011), although in a complex fashion that precludes clear conclusions. It is thus imperative that research employing more diverse and representative samples be conducted to ensure replicability of the present findings.

One possible explanation for these results is the activation of stereotypes of Muslim persons as violent and threatening (e.g., Poynting & Noble, 2004). That is, where the Muslim victim behaved in an aggressive way in reaction to harassment, participants may have interpreted this behavior as consistent with stereotypes of Muslim persons as threatening or aggressive. Future research should incorporate groups who do not share a common stereotypic representation for aggression or violence as well as those that do. Potentially, observers might be more likely to blame victims of hate where they engage in negative stereotype-consistent ways prior to the assault. Further work is needed to determine whether these results relate to aggression itself, aggression connected to Muslim victims specifically, negative stereotype-consistent actions, or some other mechanism. In addition, the present research referred to the Muslim victim’s ethnicity as South Asian. It is unclear whether or how this might have influenced reactions to the victim, and whether a Muslim victim who was identified as “Middle Eastern,” White, Black, or East Asian would have elicited similar responses from observers. There is also the distinction between subgroups of Muslim identities, which have been left unexplored here (e.g., Sunni vs. Shia), as well as the overly broad grouping of “White males.” Further research should tease apart the relative roles of religious and ethnic identity in observer reactions to anti-Muslim hate crime.

The present research provides a first step toward unraveling observer reactions to hate crime and suggests a more nuanced process may occur among observers to hate. It appears that observers express more sympathy and compassion to model victims of hate through reduced victim blaming, as well as a sense of justice through enhanced guilt rating of the perpetrator. This may be contingent, however, upon their performance of model victim behavior, including acceptance of racial or other harassment, a burden that no victim should have to bear.

Footnotes

Appendix

Declaration of Conflicting Interests

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

Funding

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

Notes

Author Biographies

Caroline Erentzen is a PhD candidate at York University, under the supervision of Dr. Regina Schuller. She completed bachelor’s and master’s degrees at the University of Western Ontario and a law degree from Queen’s University. Her research explores the way psychology can inform the law, with particular attention to hate crimes and lay expectations of model victims and perpetrators.

Regina A. Schuller is a professor of psychology at York University. She completed a BSc at the University of Toronto, a master’s and PhD in social psychology at the University of Western Ontario, and a postdoctoral fellowship at Northwestern University. Her research explores the intersection of psychology and law, including intimate partner violence, sexual violence, wrongful convictions, and jury racial bias.

Robert C. Gardner is a Professor Emeritus of psychology at the University of Western Ontario. He received his PhD at McGill University under the direction of Wallace E. Lambert, and has published extensively on statistical analysis, second language learning, ethnic attitudes, and ethnic stereotypes.

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