Anti-Asian Xenophobia,Hate Crime Victimization,and Fear of Victimization During the COVID-19 Pandemic

Abstract

While the World Health Organization advised against referring to COVID-19 using racial overtones, as the COVID-19 pandemic spread, many disparagingly called it the “Wuhan virus,” the “Chinese virus,” and other terms. In this context, the FBI warned police agencies about an expected increase in anti-Asian hate crimes during the early months of the pandemic. But, while some researchers and media outlets discussed these potential increases at length, very few studies have been able to directly assess the nature of anti-Asian hate and bias victimization during the pandemic. Following this, the current study directly examines variation in anti-Asian bias and victimization in the United States during the COVID-19 pandemic. Specifically, this research presents results from two studies using a survey of 3,163 non-Asian and 575 Asian American and Pacific Islander respondents, respectively. The first study examines the prevalence of anti-Asian xenophobia among the non-Asian sample and assesses differences in these prejudicial attitudes across respondent characteristics, while the second study examines variation in experiences with bias during the pandemic among the Asian sample. The results illustrate the ubiquity of anti-Asian sentiment, suggesting that those who indicate greater fear of the pandemic report more prejudicial attitudes, as well as important racial differences in these patterns. The results also demonstrate the extent to which the pandemic has impacted individual experiences with anti-Asian bias victimization, such that more than one-third of Asian respondents report bias victimization during the pandemic, and more than half of Asian respondents report that they know someone who has been victimized. These patterns have important implications for addressing COVID-19-related hate crime moving forward.

Keywords

hate crimes violence exposure victimization fear of victimization COVID-19

In early January 2020, Chinese scientists identified a pneumonia-like disease—believed to have originated in China—now identified as COVID-19 (Wang et al., 2020). In the weeks that followed, the World Health Organization (WHO) declared the disease a “public health emergency of international concern.” On March 11, 2020 this designation was upgraded to a global pandemic (Centers for Disease Control and Prevention (CDC), 2020). Two days later, on March 13, the United States (U.S.) followed suit and similarly declared COVID-19 a national emergency. Importantly, in choosing the name for this disease, the WHO followed their guidelines for best practices in naming infectious diseases, which state that disease names should not include geographic locations; people’s names; species/class of animal or food; cultural, population, industry, occupational references; or terms that incite undue fear (World Health Organization (WHO), 2015a). The primary intention of these guidelines is to “avoid causing offence to any cultural, social, national, regional, professional or ethnic groups” (World Health Organization (WHO), 2015a, p. 1), as disease names can lead to negative consequences, including “backlash against members of particular religious or ethnic communities” (World Health Organization (WHO), 2015b).

Many people, however—including prominent political figures and former President Donald Trump himself—disparagingly referred to the disease as the “Wuhan virus,” the “Chinese virus,” and even the “Kung Flu.” As Lee and Yadav (2020, p. 17) observed, “in one fell swoop, the coronavirus—and Trump’s blithe description of it—reanimated a century-old racist trope that Asian Americans are vectors of filth and disease.” Recognizing the potential impact of this rhetoric on an interpersonal level, the Federal Bureau of Investigation (FBI) issued a warning to law enforcement agencies around the country regarding an increase in hate crimes, which are criminal offenses against a person or property motivated in whole or in part by an offender’s bias, against Asians and Asian Americans (Margolin, 2020). Following this, many scholars have discussed these potential increases in both prejudice and bias-motivated crime (e.g., Gover et al., 2020; Tessler et al., 2020). Congress even recently responded to these incidents by passing the COVID-19 Hate Crimes Act, which was intended to increase oversight and resources for preventing and responding to hate crimes during the pandemic. Yet, while such dialogue is important, to date there has been very little systematic, descriptive examination of the nature of anti-Asian prejudice and bias victimization during the COVID-19 pandemic. Following this, the primary goal of the current research is to descriptively examine the nature of discrimination experiences, hate crime victimization, and fear of victimization among Asian and Asian American survey respondents in the United States during the COVID-19 pandemic.

Anti-Asian Prejudice and Bias Crime

As the COVID-19 pandemic spread, so did fear, xenophobia, and bias crimes directed at Asian Americans. High-profile anti-Asian incidents have been documented in major news outlets and media publications (e.g., Wong, 2020). In Texas, for example, a man stabbed a Burmese American family because he thought they were Chinese and infecting people with the coronavirus. In New York, there were several such instances documented, including one incident in which a man poured acid on an Asian woman and another incident in which a Korean woman was punched in the face (Lee & Yadav, 2020).

Research has found that these individual incidents are likely indicative of more general trends as well. Scholars have noted, for example, significant increases in Sinophobic slurs (e.g., Lu & Sheng, 2020), and general anti-Asian prejudice (e.g., Bartos et al., 2021; Chen et al., 2020; Clissold et al., 2020). Lu and Sheng (2020), for example, found that tweets containing anti-Asian slurs significantly increased in geographic areas immediately following the first local COVID-19 diagnosis. They attributed these findings to the threat of infection and the association of the Asian population with the pandemic. Others have discussed the potential for increased hate crime victimization during the COVID-19 pandemic as well (Gover et al., 2020; Tessler et al., 2020). In support of these assertions, Asian American organizations like the ‘Stop AAPI Hate’ forum have recorded hundreds of instances of anti-Asian prejudice and abuse during the pandemic (Jeung & Nham, 2020). These incidents ranged in nature from non-criminal incidents, like the boycotting of Asian restaurants, to verbal and physical assaults of Asian Americans in public places. Ren and Feagin (2021) also documented that at least 82 incidents were directly tied to face masks—wherein Asian individuals were variably attacked either for wearing a mask (interpreted as a sign of underlying disease) or for not wearing a mask (or for lacking a potential barrier to the potential underlying disease), depending on the situation—demonstrating the symbolic link between victimization and the threat of disease.

Racialized Disease Threat

Unfortunately, this is not the first global health crisis tied to increased prejudice and bias toward minority groups. As Gover et al. (2020, p. 6) poignantly noted, “eruptions of xenophobia have historically followed close on the heels of pandemics.” Indeed, there is a long history linking the spread of disease to prejudice and xenophobia (Clissold et al., 2020; Lee, 2019); historically, minority groups have frequently been erroneously blamed for spreading germs or disease, as majority groups perceive them as sick or unhygienic (Taylor, 2019). As early as the 14th century, Jewish citizens were blamed for the spread of the bubonic plague (Markel, 1999). More recently, the Ebola virus was linked to increases in anti-African racism in Europe (Prati & Pietrantoni, 2016). In the comparatively brief history of the US, there are also numerous such examples: Irish Catholic immigrants have been blamed for cholera, Jewish immigrants have been scapegoated for tuberculosis, and Italian immigrants have been blamed for polio (Cohn, 2012; Gover et al., 2020; McKiven, 2007).

The Asian population has, in particular, been a frequent target of disease-related prejudice (Dolmage, 2018; Tessler et al., 2020). Researchers have long noted that those from the West have historically labeled those from non-Western parts of the world as foreign, contagious, and infectious (Clissold et al., 2020; White, 2020). Indeed, the current stigmatization of the Asian population is situated within a longstanding history of racist tropes linking Asians to stereotypes of disease, like the “Yellow Peril” myth propagated during the 19^th century (Molina, 2006; Mudambi, 2019; Power, 1995). The Chinese Exclusion Act of 1882, for example, was created in response to a smallpox outbreak in San Francisco, and provided for the forced vaccination of Chinese residents (Kil, 2012). In the early 1900s, officials similarly quarantined and burned down Chinatown neighborhoods in response to bubonic plague outbreaks (Barde, 2004; Mohr, 2004; Power, 1995). The bubonic plague itself was also framed as a racialized disease which could infect Asians, but to which white people were immune (Randall, 2019; Tessler et al., 2020). More recently, after the 2002 SARS outbreak, at least one study found that UK-based discourse implied that Asian citizens were more susceptible than British citizens to the disease (Washer, 2004; see also Eichelberger (2007).

Scholars have proposed several explanations for the link between disease outbreaks and the exacerbation of prejudice and biased behavior. Some research has suggested, for example, that these relationships are driven by fear, wherein individuals respond to the threat of disease by “othering” that threat (Reny & Barreto, 2020). The perpetration of hate crime, in particular, is frequently used to “do difference” or “other” potential hate crime victims. This literature, largely informed by Perry (2001), posits that hate crimes extend marginalization against those who are perceived as different. More specifically, hate crimes reflect societal power dynamics, wherein the dominant group seeks to preserve their privileged position by targeting the “other” through hate crime. This research has also suggested that the state may exacerbate this bias by enabling a divisive political environment through the use of inflammatory rhetoric, like that espoused by Trump (Koopmans & Olzak, 2004; Piatkowska & Lantz, 2021). Other research has similarly pointed to the role of scapegoating, where individuals make sense of the disease by assigning responsibility and blame for the threat to the “other” (Nelkin & Gilman, 1988).

Considering the COVID-19 pandemic more specifically, Tessler et al. (2020) suggested that hate incidents—both criminal and non-criminal—directed at the Asian American population are reflective of racialized color lines which place the Asian population outside the boundaries of whiteness. More specifically, in drawing from Perry’s (2001) research, they note that Asian Americans are perceived by many as “perpetual foreigners,” such that those with a phenotypical Asian ethnic appearance are perceived to be foreign, regardless of their actual immigrant status (see also, Ancheta, 2006; Tuan, 1998). These negative stereotypes have been exacerbated during the COVID-19 pandemic, as both the disease and Asian Americans are perceived as foreign and thus as threatening (Tessler et al., 2020). Considered within the context of “doing difference,” a white man who victimizes an Asian American because of bias motivations related to the pandemic, may view himself as defending the color line by fighting against someone they view as related to the disease, and thus implicitly fighting the disease itself (Perry, 2001). Regardless, research has consistently demonstrated that when a disease begins to spread in large proportions, individual reactions to this disease threat are often rooted in prejudice and stigma.

Yet, the nature of the COVID-19 pandemic is unprecedented in both magnitude and scope. The resulting racialized disease threat associated with the pandemic is thus likely to be particularly salient, and prior research has shown that more salient threats of infectious disease are associated with greater levels of xenophobia (Faulkner et al., 2004). Following this, it is important that researchers focus on how the pandemic has impacted discrimination and hate crime directed at the Asian population in the U.S. But, while a few researchers have discussed these potential increases in hate crimes at length (Gover et al., 2020; Tessler et al., 2020), very few existing studies have been able to directly assess the nature of anti-Asian hate and bias victimization during the pandemic (see Ren & Feagin, 2021 for an exception). Examining and describing these impacts is the focus of the present research.

Current Research

To more directly assess the nature of Anti-Asian prejudice and bias victimization during the COVID-19 pandemic, the present research entails a detailed examination of experiences with discrimination and bias—both criminal and non-criminal—among Asian and Asian American individuals in the U.S. during the pandemic. To do so, we use data collected via an opt-in web-based survey administered in May 2020 to a sample of 4188 people throughout the country. The sample was generated and administered using Prime Panels by CloudResearch, a research firm with access to a pool of more than 50 million participants worldwide across dozens of research platforms. Using this pool of participants, CloudResearch works with researchers to arrange inclusion criteria, and only those who satisfy criteria are able to participate. CloudResearch then contacts participants via email based on their profiles, and participants are compensated in line with the platform through which they accessed the survey. The sample was designed to be broadly representative of the U.S. population in terms of race/ethnicity and gender. Specifically, to generate a sample that mirrored the U.S. population in terms of race/ethnicity, we employed a targeted quota sampling approach using the American Community Survey (ACS) 2014–2018 5-year estimates of the U.S. racial composition to establish quotas. We further oversampled an additional 300 non-Hispanic Asian, 300 non-Hispanic Black, and 300 Hispanic respondents to be sure the sample sizes of these groups were sufficiently large enough for group-specific analyses. For the current study, the overall survey sample is divided into two subsamples—non-Asian respondents (N = 3163) and Asian and Asian American respondents (N = 575)—and two studies are conducted.¹ Study 1 examines various indicators of anti-Asian xenophobia among non-Asian respondents, with a particular focus on individual variation in xenophobic attitudes. Study 2 focuses only on the subsample of Asian/Asian American respondents and examines experiences with discrimination, bias crime, and fear of bias crime.

With these unique data, this study adds to existing research in three important ways. First, and most importantly, this research extends our understanding of the relationship between the COVID-19 pandemic and bias directed toward the Asian population by allowing for a descriptive assessment of this bias. Second, one of the most substantial barriers to complete hate crime data is victim underreporting (Lantz et al., 2019); by collecting information directly from respondents, this research includes information from those incidents which were not reported to the police. Finally, this survey also collected information on non-criminal bias incidents. This inclusion is particularly advantageous given that prior research has indicated that such events, although not criminal, are related to bias crime and can still negatively impact victims (Gladfelter et al., 2017; Iganski, 2001; Levin & McDevitt, 2002).

Study 1: Anti-Asian Xenophobia/Prejudice

Procedures

Data for Study 1 of this research utilizes the 3613 non-Asian respondents in the survey sample. Approximately 60% of this non-Asian sample identifies as non-Hispanic white, 19.4% identifies as non-Hispanic Black, 18.6% identifies as Hispanic (of any race), and just over 2% identifies as another race. The procedure for coding racial identification is described in detail below.

Our primary variables of interest in Study 1 represent indicators of anti-Asian xenophobia adapted from Van der Veer et al. (2013). Specifically, respondents were asked to report their level of agreement with nine statements aimed at revealing anti-Asian sentiment: “Asian immigration in this country is out of control;” “Asian immigrants cause increase in crimes;” “Asian immigrants take jobs from people who are here already;” “Interacting with Asian immigrants makes me uneasy;” “I worry that Asian immigrants may spread unusual diseases;” “I am afraid that in case of war or political tension, Asian immigrants will be loyal to their own country of origin;” “With increased Asian immigration I fear that our way of life will change for the worse;” “I doubt that Asian immigrants will put the interest of this country first;” and “I am afraid that our own culture will be lost with increases in Asian immigration.” For each statement, respondents were given a 5-point Likert scale ranging from strongly disagree to strongly agree. For the current study we recoded each item into a binary variable equal to 0 if the respondent reported either strongly disagreeing, disagreeing, or feeling neutral about the corresponding statement, and equal to 1 if the respondent reported either agreeing or strongly agreeing.²

Other analytic variables for Study 1 include race/ethnicity, perceived risk of COVID-19 to the respondent, and perceived risk of COVID-19 to the U.S. Because prejudicial attitudes are inherently situated within racialized power structures (see Perry, 2001), and the pooling of different racial groups (e.g., combining White and Black respondents) would likely hide important variation in anti-Asian prejudicial attitudes, we disaggregate analyses by race/ethnicity. Race/ethnicity is based on three survey questions. The first asked respondents whether they are of Spanish, Latino, or Hispanic origin. Respondents were then separately asked which racial category describes their race, with the option to select all that apply. Finally, those respondents who selected more than one racial category were given the option to specify which one racial category they identify with most. Given Study 1’s focus on non-Asian/Pacific Islander respondents, all respondents who indicated Asian or Native Hawaiian/Pacific Islander were removed from the sample. Next, all remaining respondents who answered “yes” to the question of Spanish, Latino, or Hispanic origin were coded as Hispanic. Finally, all remaining respondents were coded according to the racial category with which they identified with most. This coding resulted in a sample of 2148 white respondents, 694 Black respondents, 665 Hispanic respondents, and 73 respondents of another race.

Perceived risk of COVID-19 to the self was based on a question asking respondents what level of threat they think COVID-19 poses to them or their family. Response categories included very low, low, moderate, high, and very high. We coded the measure into a binary variable equal to 0 if the respondent indicated very low, low, or moderate risk and equal to 1 if the respondent indicated high or very high risk. Perceived risk of COVID-19 to the U.S. was based on a similar question asking respondents what level of threat they think COVID-19 poses to the country as a whole. Response categories for this question were the same as for perceived risk to self and we similarly coded the measure into a binary variable equal to 1 if the respondent indicated high or very high risk to the country and equal to 0 if the respondent indicated very low, low, or moderate risk to the country. Interestingly, while only about 44.3% of respondents indicated that COVID-19 poses a high or very high risk to themselves or their family, greater than 70% of respondents indicated that COVID-19 posed a high or very high risk to the country as a whole.

Analytic Plan

The goal of Study 1 is to document the extent of anti-Asian xenophobia by race/ethnicity and perceived risk of COVID-19. Therefore, we first split the sample by racial/ethnic group and examine the percentage of respondents in each racial/ethnic category who agree or strongly agree with each indicator of anti-Asian xenophobia. We then use t-tests to examine racial differences in these patterns. Next, we split the sample by perceived risk of COVID-19, first by perceived risk to self (high vs. low) and then by perceived risk to the U.S. (high vs. low), and again examine the percentage of respondents in each group who agree with each anti-Asian statement. Again, we use t-tests to determine whether these percentages significantly differ. Listwise deletion is used for each bivariate comparison.

Results

Results of Study 1 are shown in Table 1. Focusing first on anti-Asian xenophobia by race/ethnicity, we note that the statement with the highest level of agreement among all racial/ethnic groups is “I doubt that Asian immigrants will put the interest of this country first.” Specifically, 18.6% of white, 16.2% of Black, 13.4% of Hispanic, and 15.1% of other race respondents agree with this statement. Among white, Black, and other race respondents, the statement with the lowest level of agreement is “interacting with Asian immigrants makes me uneasy” (8.5%, 9.1%, and 2.8%, respectively). However, among Hispanic respondents, the statement that “Asian immigrants increase crime” has the lowest level of agreement (5.6%).

Table 1.

Anti-Asian Xenophobia by Race/Ethnicity and Perceived Risk of Coronavirus among Non-Asian Respondents.

	Differences in Anti-Asian Xenophobia by Race/Ethnicity											Differences by Perceived Risk of COVID-19
	White		Black			Hispanic			Other Race			Self: High		Self: Low			U.S.: High		U.S.: Low
	N	%	N	%	Sig.^a	N	%	Sig.^a	N	%	Sig.^a	N	%	N	%	Sig.^b	N	%	N	%	Sig.^b
Asian immigration is out of control	2145	13.9	690	10.6	*	663	8.7	***	73	11.0		1590	14.4	2006	10.5	***	2489	12.1	1056	12.5
Asian immigrants increase crime	2145	8.6	691	9.3		663	5.6	*	71	5.6		1591	10.2	2004	6.4	***		8.2	1055	7.2
Asian immigrants take jobs	2141	18.5	690	13.5	**	662	10.6	***	73	12.3		1589	16.7	2002	15.3		2485	15.3	1055	17.1
Interacting with Asian immigrants makes me uneasy	2142	8.5	690	9.1		662	7.3		72	2.8	†	1587	10.8	2004	6.3	***	2486	8.6	1055	7.3
I worry that Asian immigrants spread unusual diseases	2141	13.8	689	12.2		658	11.1	†	73	12.3		1583	15.0	2003	11.3	**	2482	13.6	1053	11.1	*
Asian immigrants will be loyal to country of origin	2144	18.1	691	16.2		663	12.5	**	73	15.1		1593	18.1	2003	15.3	*	2491	16.7	1054	16.1
With increased Asian immigration, our way of life will change for worse	2143	12.7	689	10.2	†	664	8.4	**	73	6.8		1591	13.5	2003	9.5	***	2489	11.3	1054	10.7
I doubt that Asian immigrants will put interest of this country first	2141	18.6	691	16.2		664	13.4	**	73	15.1		1591	18.0	2003	16.4		2488	16.5	1055	17.8
I am afraid that our culture will be lost with increases in Asian immigration	2142	13.9	690	11.2	†	661	8.6	***	73	4.1	*	1587	13.9	2004	10.8	**	2485	12.2	1055	11.8

†p < .10; *p < .05; **p < .01; ***p < .001.

Notes: Sig. = Significance; N = sample size upon which the percentage is based; U.S. = United States

^aSignificance indicates that percentage of corresponding racial group experiencing victimization type is significantly different from percentage of white respondents experiencing the same victimization type.

^bSignificance indicates that percentage of respondents who believe Coronavirus poses high risk experiencing victimization type is significantly different from percentage of who believe Coronavirus poses low risk experiencing the same victimization type.

When looking at differences in anti-Asian xenophobia by race/ethnicity, we see that the greatest differences in agreement are between white and Hispanic respondents, with white respondents agreeing at significantly higher levels than Hispanic respondents for every statement except one.³ Interestingly, however, there are very few differences in the prevalence of agreement between white and either Black or other race respondents. The only significant differences found between agreement of white and Black respondents are for “Asian immigration is out of control,” “Asian immigrants take jobs from people who are already here,” “with increased Asian immigration, I fear that our way of life will change for the worse,” and “I am afraid that our own culture will be lost with increases in Asian immigration,” with white respondents reporting higher levels of agreement in each case. The only significant differences between white and other race respondents are for agreement that “interacting with Asian immigrants makes me uneasy” and “I am afraid that our own culture will be lost with increases in Asian immigration.”

Further, given our interest in the COVID-19 pandemic, we draw attention to the anti-Asian statement regarding disease, in particular: “I worry that Asian immigrants may spread unusual diseases.” Interestingly, there is very little racial difference in agreement with this statement, with 13.8% of white, 12.2% of Black, 11.1% of Hispanic, and 12.3% of other race respondents agreeing. The difference between Hispanic and white respondents is marginally significant (p = .068), but still very small.

Turning to agreement with statements of anti-Asian xenophobia by perceived risk of COVID-19, we note that level of agreement is greater among respondents who perceive the risk of COVID-19 to themselves or their families to be high than among those who perceive this risk to be low for every statement except two (“Asian immigrants take jobs from people who are here already” and “I doubt that Asian immigrants will put the interest of this country first”). Focusing on the question regarding disease, in particular, 15% of respondents who believe the risk of COVID-19 to themselves or their families is high agree that they “worry that Asian immigrants spread unusual diseases,” compared to only 11.3% of respondents who believe the risk to themselves or their families is low. Interestingly, the only significant difference in level of agreement between those who perceive that the risk of COVID-19 to the U.S. as a whole is high and those that perceive this risk as low is for the statement about disease. There are no significant differences in agreement with any of the other anti-Asian xenophobia statements based on whether the respondent views the risk of COVID-19 to the U.S. to be high or low.

Study 2: Anti-Asian Discrimination and Hate Crime Victimization

Procedures

This research follows recent calls for purposeful sampling of Asian respondents during the COVID-19 pandemic (e.g., Chen et al., 2020). As such, data for Study 2 come from the 575 Asian or Native Hawaiian/Pacific Islander. The majority of respondents self-report as Asian (n = 552), but we include the additional 23 Native Hawaiian or Pacific Islanders as well for inclusivity.⁴

Experiences with bias victimization, both criminal and non-criminal, during the COVID-19 pandemic represent our primary variables of interest for Study 2. The survey asked respondents how often they had experienced each of 12 types of victimization during the past 1–2 months due to their race/ethnicity.⁵ The indicators of non-criminal bias included: “had verbal insults directed at you,” “been refused services in a bar, restaurant, club, or similar establishment,” “been refused services in a hotel, motel, or similar establishment,” “been refused other services or accommodations,” and “experienced other discrimination.” The indicators of criminal bias victimization (i.e., hate crimes) included: “been threatened with physical violence,” “had your personal property damaged or destroyed,” “had objects thrown at you,” “been chased or followed,” “been spat upon,” “been punched, hit, kicked, or beaten,” and “been assaulted or wounded with a weapon.” Original response categories for these indicators were “never,” “once,” or “twice or more.” We recoded each victimization indicator into binary variables equal to 1 if the respondent did experience that victimization type and equal to 0 if the respondent did not experience that victimization type during the prior 1–2 months.

Additionally, we created measures representing whether the respondent experienced any bias victimization (equal to 1 if the respondent experienced at least one of the 12 victimization types and 0 otherwise), any non-criminal bias victimization (equal to 1 if the respondent experienced at least one of the five non-criminal victimization types and 0 otherwise), and any criminal bias victimization (equal to 1 if the respondent experienced at least one of the seven criminal victimization types and 0 otherwise). To capture fear of victimization, we also asked respondents whether “the possibility of harassment or violence because of your race/ethnicity has affected in any way how you yourself act or behave.” This variable is equal to 1 if the respondent answered “yes,” and equal to 0 if the respondent answered “no.” Finally, we asked how many people they know personally who have been verbally harassed, threatened with violence, or physically attacked because of their race/ethnicity. We coded this as a binary variable equal to 1 if the respondent indicated “one,” “two or three,” or “more than three” people, and equal to 0 if the respondent indicated “none.” Given that COVID-19 was declared a pandemic by the WHO on March 11, 2020 and a national emergency by former President Trump on March 13, 2020, administering the survey in May 2020 resulted in a recall-period during a 1–2-month period in which the pandemic was central in Americans’ minds. Additionally, at this time, concern about the virus and its origins were especially high.

Respondent characteristics used in Study 2 include foreign-born status and several pandemic-specific questions. Foreign-born status comes from a question asking respondents whether they were born in the U.S. or in another country. Those respondents who selected the U.S. as their birth-country were coded as native-born and those respondents who selected “other country” were coded as foreign-born. Given prior research indicating the potentially important role of mask wearing (Ren & Feagin, 2021), social distancing practices, and essential worker status in predicting COVID-19 related bias victimization (see Wenger & Lantz, 2022a, 2022b), we also examine differences across these pandemic-specific factors. To measure essential worker status, we asked respondents whether they were considered an essential worker or not at the time of the survey.⁶ Those that responded “yes” are coded as 1 and those that responded “no” are coded as 0. To capture frequency of mask wearing we asked respondents how often they wear facial masks or other personal protective equipment (PPE) when they leave the home. Our mask-wearing variable is equal to 1 for respondents who reported “always” wearing a mask or other PPE, and equal to 0 for respondents who reported “sometimes, but not all of the time” or “never.” Extent of social distancing was measured by asking respondents to describe their current behavior regarding socializing with people outside of their household. Respondents are coded as 1 on our total social distancing measure if they indicated either “I am not socializing with friends and family in person, but I am socializing with friends or family virtually” or “I am not socializing with friends and family in person or virtually,” and coded as 0 if they indicated at least some in-person socializing (“I am continuing to socialize in public places as often as I did before the pandemic began,” “I am continuing to socialize in public places, but slightly less than before,” or “I am not socializing in public places, but I am socializing with friends or family in my home or their homes”). Finally, employment status during the pandemic is based on a question asking respondents about their current employment status. Respondents are coded as “still employed” if they were employed and working the same way they did before the pandemic; respondents are coded as “remote employed” if they were employed, but working remotely during the pandemic; respondents were coded as “still unemployed” if they were unemployed and were already unemployed prior to the pandemic; and finally, respondents were coded as “pandemic unemployed” if they were unemployed because they lost their job during the pandemic.

Analytic Plan

We begin Study 2 by examining the overall percentage of respondents who reported having experienced each type of bias victimization/fear of victimization and knowing others who have experienced of bias victimization. We then split the sample into native-born and foreign-born respondents to examine the percentage of respondents in each group that experienced each victimization type. Additionally, we use t-tests to examine whether the percentage of respondents in each group are significantly different.

We then examine associations between bias victimization and our pandemic-specific measures (see Ren & Feagin, 2021). To do so, we compare essential workers to non-essential workers; respondents who always wear a mask outside of the home to respondents who do not always wear a mask; respondents who practice total social distancing to those who do not; and respondents who are still employed as they were prior to the pandemic, who are still employed but working remotely, and who are unemployed and were so before the pandemic to those who became unemployed during the pandemic. We compare these groups by measuring the difference in prevalence of each bias type and then use t-tests to examine whether each difference is statistically significant. As with Study 1, listwise deletion is used for each bivariate comparison.

Results

Prevalence of each victimization type, both overall and by foreign-born status, are presented in Table 2.⁷ As seen in the table, nearly 34% of respondents experienced a bias victimization, with 32.3% experiencing a non-criminal victimization and 19.5% experiencing a criminal victimization (i.e., a hate crime). The most prevalent non-criminal bias victimization type among Asian respondents is verbal insults, experienced by 23.7%, while the most prevalent criminal bias victimization type is having been threatened with physical violence, experienced by 13.1% of respondents. Additionally, 32.6% of respondents report that fear of bias victimization has affected how they act or behave and nearly 47% of respondents know at least one other person who has been the victim of a bias incident. Although not shown in the table, additional analyses revealed that 61.7% of Asian respondents either reported a bias victimization themselves, reported that fear of victimization affected how they act or behave, or reported that they knew someone who had been the victim of a bias incident.

Table 2.

Prevalence of Bias Victimization Experiences, Fear of Victimization, and Awareness of Others’ Victimization among Asian Respondents.

		All		Native-Born		Foreign-Born
		N	%	N	%	N	%	Sig.^a
Any bias victimization		575	33.9	321	34.6	247	33.2
Non-criminal bias victimization		575	32.3	321	33.3	247	31.2
	Verbal insults	575	23.7	321	24.6	247	22.3
	Been refused service (restaurant/Bar)	574	8.4	321	11.2	246	4.5	**
	Been refused service (lodging)	574	7.3	321	10.0	246	3.3	**
	Been refused service (other)	574	8.9	321	10.3	246	6.9
	Other discrimination	573	22.3	321	24.9	246	19.1
Criminal bias victimization		575	19.5	321	21.5	247	16.6
	Threatened with physical violence	574	13.1	320	15.3	247	9.7	*
	Had personal property damaged/destroyed	574	11.7	321	14.0	247	8.5	*
	Had objects thrown	574	11.0	321	14.0	246	6.5	**
	Been chased or followed	573	11.3	319	14.4	247	7.3	**
	Been spat upon	575	9.0	321	11.2	247	5.7	*
	Been punched, hit, kicked or beaten	574	9.8	321	11.8	246	6.5	*
	Been assaulted or wounded with a weapon	574	6.4	320	8.1	247	4.0	*
Fear of victimization		519	32.6	286	31.1	226	34.5
Know other victims of bias		572	46.5	320	49.4	245	42.9

p < .05; ** p < .01.

Notes: N = sample size upon which the percentage is based; Sig. = Significance

^aSignificance indicates that percentage of native-born respondents experiencing victimization type is significantly different from percentage of foreign-born respondents experiencing the same victimization type.

Prevalence of bias victimization by foreign-born status suggests that victimization is more common among native-born than among foreign-born respondents. While these differences do not amount to statistical significance for every bias victimization type, they are significantly different for having been refused service in a restaurant, refused service in a hotel, motel, or similar establishment, threatened with physical violence, had personal property damaged or destroyed, had objects thrown at them, been chased or followed, been spat upon, been punched, hit, kicked, or beaten, and been assaulted or wounded with a weapon. The largest discrepancy in victimization prevalence between native- and foreign-born respondents is for having had objects thrown at them, with 14% of native-born respondents but only 6.5% of foreign-born respondents reporting a victimization. Fear of victimization is slightly more common among foreign-born respondents and knowing others who have experienced bias victimization is slightly more common among native-born respondents, but neither of these differences are significant.

We turn now to the associations between bias victimization and our pandemic-specific measures, shown in Table 3. Essential workers report significantly greater percentages of every bias victimization type than non-essential workers. The largest discrepancy exists for any bias victimization, with the prevalence of bias victimization being 10 percentage points greater among essential than non-essential workers. This difference is closely followed by any criminal bias victimization and having been threatened with physical violence (9.8 and 9.4 percentage points difference, respectively). Fear of bias victimization does not appear to differ by essential worker status, but a significantly greater percentage of essential than non-essential workers know someone else who has been the victim of a bias incident.

Table 3.

Bivariate Associations between Bias Victimization Experiences and Pandemic-specific Characteristics among Asian Respondents.

				Still Employed	Remote Employed	Still Unemployed
	Essential Worker versus Not	Always Wear a Mask versus Not	Total Social Distancing versus Not	versus Pandemic Unemployed
	Difference	Difference	Difference	Difference	Difference	Difference
Any bias victimization	.105*	−.063	−.302***	−.123†	−.098	−.237**
Non-criminal bias victimization	.087†	−.046	−.275***	−.115	−.088	−.206**
Verbal insults	.085†	−.061	−.205**	−.092	−.112†	−.162*
Been refused service (restaurant/Bar)	.090**	−.054*	−.122**	−.033	−.077†	−.069
Been refused service (lodging)	.075**	−.021	−.135***	−.031	−.075†	−.082†
Been refused service (other)	.068*	−.015	−.199***	−.038	−.054	−.114**
Other discrimination	.075†	−.034	−.178**	−.068	−.050	−.116†
Criminal bias victimization	.098*	−.099**	−.261***	−.123†	−.113†	−.179**
Threatened with physical violence	.094*	−.049	−.227***	−.069	−.110*	−.158**
Had personal property damaged/destroyed	.082*	−.085**	−.156***	−.092	−.156**	−.150**
Had objects thrown	.062†	−.015	−.158***	−.080	−.124*	−.139**
Been chased or followed	.082*	−.043	−.119**	−.023	−.037	−.057
Been spat upon	.068*	−.027	−.182***	−.023	−.070	−.082†
Been punched, hit, kicked, or beaten	.079*	−.033	−.204***	−.025	−.030	−.069
Been assaulted or wounded with a weapon	.063*	−.034	−.171***	−.015	−.075*
Fear of victimization	.005	−.025	−.005	−.050	.012	−.036
Know other victims of bias	.113*	−.030	−.100	−.069	−.100	−.222**

†p < .10; *p < .05; **p < .01; ***p < .001.

The prevalence of all bias types is lower among respondents who always wear a mask or other PPE when they are outside of their homes than among those who do not always wear a mask, but these differences are only significant for having been refused service in a restaurant or bar, having experienced any criminal bias victimization, and having had personal property damaged or destroyed. Alternatively, the prevalence of all bias types is lower among respondents who practiced total social distancing than those who did not, and all of these differences are statistically significant. The largest difference is for any bias victimization with more than a 30 percentage-point differential between those who did and did not practice total social distancing, followed by any non-criminal bias victimization and any criminal bias victimization (27.5 and 26.1 percentage-point differentials, respectively). There were no significant differences in fear of victimization or knowing someone else who was the victim of a bias incident by either frequency of mask-wearing or extent of social distancing.

Finally, while bias victimization appears less common among those who are still employed as they were prior to the pandemic than among those that became unemployed during the pandemic, most of these differences do not reach statistical significance. The pattern is similar when comparing those who are remotely employed during the pandemic to those who became unemployed during the pandemic, with more of the differences reaching statistical significance. The greatest differences, however, are between those who are unemployed and were so prior to the pandemic and those who became unemployed during the pandemic, with nearly every bias victimization being statistically more prevalent among those who became unemployed during the pandemic. For example, the percentage of respondents who were already unemployed prior to the pandemic who reported any bias victimization is 23.7 percentage-points lower than among the percentage of respondents who became unemployed during the pandemic. Although there were no significant differences in the prevalence of fear of victimization or knowledge of other victims of bias incidents between those who were employed (either as they were prior to the pandemic or remotely) and those who became unemployed during the pandemic, those who were already unemployed prior to the pandemic are significantly less likely than those who became unemployed during the pandemic to report that they know other people who have experienced bias victimizations.

Discussion

Since the beginning of the pandemic, there has been significant discussion regarding the likely impact of COVID-19 on bias, discrimination, and hate crime directed toward the Asian American population. There has, however, been very little systematic examination of the nature of these potential impacts. Following this, the primary goal of the current research was to examine both anti-Asian xenophobia and discrimination experiences, hate crime victimization, and fear of victimization among Asian and Asian American survey respondents during the COVID-19 pandemic. In general, these results indicate at least five important findings.

First, anti-Asian xenophobia is common among non-Asian respondents, with important differences by race/ethnicity. While the highest level of agreement with any one statement across racial groups and perceived risk is 18.6%, analyses not presented indicate that nearly 33% of non-Asian respondents agreed with at least one of the anti-Asian statements. Anti-Asian sentiment was stronger among white respondents than among Hispanic respondents, but we found few differences between white and Black respondents. One possible reason for this pattern is that Hispanic respondents may be particularly sensitive to the sorts of statements included as measures of anti-Asian xenophobia, given that many of these sentiments are common stereotypes made about Hispanic immigrants as well. Therefore, Hispanic respondents may be less likely to subscribe to these stereotypes about other immigrant populations. Second, greater perceived risk of COVID-19 to oneself and one’s family is associated with greater anti-Asian sentiment. We think this finding particularly important, given that it provides further evidence for the harmful role of disease threat in exacerbating anti-Asian xenophobia during the COVID-19 pandemic (e.g., Gover et al., 2020). These results are consistent with historical patterns evident during previous disease outbreaks (e.g., Clissold et al., 2020; Tessler et al., 2020), providing some important preliminary evidence for the role that fear and concern for self might be playing in COVID-19 related prejudice; future research should continue to examine these patterns in greater detail.

Third, our results suggest that bias victimization is ubiquitous among the Asian population during the COVID-19 pandemic. While 33.9% of Asian respondents experienced at least one bias victimization themselves, that percentage jumps to 55.8% when including those respondents who know someone else who has been victimized, even if they were not victimized themselves, and to 61.7% when including those who report fear of victimization. While the timeframe of reporting for the current study only includes the first couple of months in which the pandemic flared in the U.S., there is no substantial reason to expect anti-Asian bias to have decreased since. Fourth, in most cases, the likelihood of bias victimization is either not significantly different or more common among the native-born than among the foreign-born Asian respondents in our sample. While such a finding may seem surprising, it may provide some support for Americans’ perception of the Asian population as “perpetual foreigners,” in which Americans are either unable or unwilling to consider Asian people as anything other than foreign. In this case, differences in experiences with bias victimization may be more reflective of differences in lifestyle and “opportunity” for victimization than of differences in the motivation of bias offenders to target native-versus foreign-born victims.

Fifth, and finally, our results suggest that behaviors and circumstances during the pandemic are related to bias victimization. While our analyses are correlational in nature, essential workers experience more bias victimization, and those who engage in total social distancing experience less bias victimization; these differences may be due to differences in overall “opportunity” for victimization. In other words, essential workers are more frequently in public settings in which they are able to be targeted, while those who engage in total social distancing are more likely to be at home. These findings are consistent with prior research on routine activities, lifestyle factors and non-pandemic related victimization (see McNeeley & Overstreet, 2018)—as well as research on non-Asian hate crime during the pandemic (see Wenger & Lantz, 2022a, 2022b)—which finds that those individuals with more exposure to potential hate crime offenders (i.e., essential workers who could not “stay at home”) are more likely to be the victims of hate crime. Finally, those who became unemployed during the pandemic are more likely to have been victimized than those who were already unemployed prior to the pandemic. While speculative, such differences may be the result of lifestyle changes among individuals who became unexpectedly unemployed in the midst of a global pandemic.

Our study, while conducted at the national level, is not necessarily representative of the nation as a whole; still, the results paint a concerning picture of anti-Asian bias during the early months of the COVID-19 pandemic. Taken together, the patterns we observe imply that the pandemic has likely unveiled and exacerbated deep societal prejudices regarding Asian people in the US. These results should be considered, for example, not only within the context of problematic stereotypes regarding Asian Americans and the spread of communicable diseases, but other stereotypes as well, like that of the “model minority.” This stereotype promotes the idea that Asian Americans have enjoyed success in American society due to cultural values which emphasize work ethic, intelligence, and the importance of education and achievement. Unfortunately, as Chou and Feagin (2015) noted, the model minority stereotype works to perpetuate the belief that all racial groups—White and minority alike—operate on equal status, with the hardest working members of all groups able to achieve success. The results observed in this research, however, imply that such an equal playing field is likely also a myth.

Research on hate crime more generally has posited that racism and bias-motivated violence is often intended to reinforce the societal position of the privileged over the less privileged (Lantz, 2022; Perry, 2001; Wellman, 1993), and the COVID-19 pandemic has unveiled deep-seated anti-Asian racism in American society. Drawing from this framework, Tessler et al. (2020) recently posited that perceptions of Asian Americans as foreign—in combination with perceptions of the virus as foreign—has likely contributed to a pernicious environment which threatens the safety and mental health of the Asian population. This research, which finds that xenophobia is significantly higher among those who perceive the pandemic as a more salient threat, supports these assertions. COVID-19 is a threat to all individuals, and does not discriminate; but theoretical expositions of hate crime offending posit that would-be offenders may victimize those who symbolize the disease as a way to empower themselves and exert physical dominion over the threat. In this sense, they may draw from racist stereotypes about Asian Americans and disease in order to define themselves as fighting back against the disease itself. As a result, throughout the course of the COVID-19 pandemic, the Asian American population has been forced to cope with not only the risk of infection, but also the risk of bias-motivated victimization. Following this, we echo their sentiments that these incidents offer further proof of the need to challenge any remaining notions that America is a post-racial society (Bonilla-Silva, 2006).

Limitations

While we know of no other existing data which could be used for the current analyses, there are certain limitations to the current methodology which must be acknowledged. Most importantly, the survey itself is an opt-in survey. While there is some evidence indicating that contemporary non-probability opt-in surveys can sometimes rival the effectiveness of probability-based samples given increasing issues and costs (e.g., Ansolabehere & Schaffner, 2014; Kennedy et al., 2016; Simmons & Bobo, 2015), unobserved differences between survey panelists and the general population can introduce bias. To address this, we employ quota sample matching methods, the primary objective of which is to match a sample to a control group (in our case, the general population) using one or more characteristics (Rivers & Bailey, 2009). Given the inadequacy of existing data to examine our research questions, however (e.g., Ruback et al., 2018)—and our research goal of understanding the nature of anti-Asian prejudice and hate crime, rather than generating population estimates—we believe these data are “fit for purpose.”

Research Implications

The research implications of the current results are substantial. First, Asians are among the most understudied racial/ethnic groups in the scientific literature (Yi, 2020); anti-Asian hate crime is particularly understudied, but is unique in nature and should be given greater attention moving forward. While Asian Americans currently comprise only roughly 5% of the population, they are the fastest growing racial/ethnic group in the U.S., and are projected to represent one of the largest population shares in coming decades (Chen et al., 2020; Horowitz et al., 2019). It is thus critical that anti-Asian hate crime be the focus of more research moving forward.

Future research should focus, in particular, on the long-term mental and physical health consequences of discrimination and bias during the pandemic among the Asian population. Following the increases in Islamophobia after the September 11^th terrorist attacks, hate crimes were demonstrably associated with short- and long-term health problems among Arab and Muslim Americans (Chen et al., 2020; Padela & Heisler, 2010). More specifically, research has demonstrated a relationship between experiences with racial discrimination and a number of negative mental health outcomes, including psychological distress, reduced life satisfaction, decreased self-esteem, anxiety, depression, suicidal ideation, and other mental health issues (Gee et al., 2007; Hwang & Goto, 2008; Nadal et al., 2015; Padela & Heisler, 2010; Sue et al., 2009). Prior research has also suggested that hate crimes can result in severe physical trauma and negatively impact physical health as well (Chen et al., 2020; Gee et al., 2007; Lantz & Kim, 2019; Malcom & Lantz, 2021). Given the scope of the COVID-19 pandemic, researchers should make careful efforts to better understand the specific consequences of COVID-19-related discrimination and bias if we hope to develop appropriate interventions to deal with such issues.

Recent research by Lu and Sheng (2020) also found that anti-Asian tweets were more geographically concentrated in areas with recent COVID-19 diagnoses. Given that other research has demonstrated that hate crime is geographically concentrated as well (Wenger & Lantz, 2022a), future research should consider spatial variation in the mental and physical consequences of the COVID-19 pandemic on bias and hate crime as well. Next, these results highlight the potential magnitude of underreporting issues with official hate crime statistics (Lantz et al., 2022; Myers & Lantz, 2020). In the current study, we surveyed 575 Asian Americans, and discovered that at least 112 (19.5%) of them had been the victim of at least one racially-motivated hate crime incidents. The 2019 FBI hate crime statistics, however, reported only 158 Anti-Asian hate crime statistics in the entirety of the United States. While not directly comparable because of differences in data collection, the relative similarity in the total number of hate crimes across two data sources (112, compared to 158), given that one data source represents the entire country (i.e., FBI statistics) and another represents only a small proportion of the Asian population in America (i.e., the current study), is notable. Official hate crime statistics clearly represent only a fraction of hate crimes that actually occur, and some recent research has suggested that Asian victims may be particularly unlikely to report hate crime victimization (Lantz & Wenger, 2022). Future research should continue to explore the reporting patterns of Asian hate crime victims in greater depth.

Finally, one of the most important implications of the current study is that the bias and discrimination faced by Asian Americans during the pandemic is itself endemic: most participants either indicated that they have directly experienced bias and discrimination, or that they knew someone who had (55.8%), and this percentage is even higher when accounting for those respondents who indicate some fear of victimization. Within this context, prior research has noted that bias-motivated violence may have negative emotional and behavioral impacts not just for the individual who is targeted, but for others within a shared target group. These impacts, which Perry and Alvi (2012) refer to as “in terrorem” effects, should also be considered within the context of the present study. Put simply, the negative impacts of hate crime victimization are not necessarily restricted to those who are victimized. The pervasive nature of this bias contributes to a social environment characterized by fear and vulnerability, as respondents indicated self-protective behavioral changes reflective of this fear. Unfortunately, such patterns indicate that—if hate crime is considered as an effort to do difference and defend the color line (Perry, 2001; Tessler et al., 2020)—the perpetrators of these crimes are succeeding in their goal. Asian Americans are changing their behavior, socially withdrawing, and restricting their own movements out of fear. Following this, and given the scope of Asian American victimization during the pandemic, it is imperative that future research consider the broader social impacts of hate crime among the Asian American population.

Policy Implications

The evidence presented here suggests that, while the COVID-19 pandemic does not discriminate, societal reactions to the pandemic have been deeply rooted in prejudice and xenophobia. It is thus critical that we respond to these issues as a society as well. Such a response must begin with following WHO guidance to avoid using racially charged terms or geographic identifiers when referring to the disease. The WHO (2020) has also advised against visual narratives which encourage anti-Asian prejudice and xenophobia, including the disproportionate use of photographs that imply an association between Asian people and COVID-19. Burton (2020), for example, noted that one of the most frequently used photos in the media is that of an Asian individual wearing a face mask in an urban dystopia-like setting (see also, Walker, 2020). It is also critical that we move toward an accurate, well-informed representation of the disease in more popular and political rhetoric, both in the media and among prominent public figures (e.g., former President Donald Trump). In this context, it is important that authority figures act as role models, rather than fanning the flames of xenophobic rhetoric by publicly associating the pandemic with Asian people (Clissold et al., 2020; Reny & Barreto, 2020).

These results also suggest a need for greater societal efforts for tracking anti-Asian hate crimes, especially in the post-COVID-19 era. Unfortunately, it is unlikely that the stigmatization of Asian people will dissipate quickly, even once the disease is soundly in check. In the wake of the September 11^th terrorist attacks, Islamophobia and the stigmatization of Muslim people changed dramatically, and has yet to return to levels preceding the terrorist attacks. It is possible that we are living through a similar watershed moment regarding the stigmatization and victimization of Asian people. A critical difference between these two incidents, however, was that the anti-Muslim incidents were immediately condemned by President George W. Bush; as Lee and Yadav (2020) noted, former President Trump made no such condemnations regarding anti-Asian bigotry. Following this, and given the well-known issues with existing official hate crime statistics (e.g., Lantz et al., 2019), it is crucial that we increase efforts to track these incidents moving forward. Such efforts might be modeled after those of the Stop AAPI hate forum website and the efforts of other Asian America civil rights groups, which have created websites and online reporting forms for tracking these incidents at the beginning of the pandemic. Some major cities, like Los Angeles, CA, have also encouraged the reporting of anti-Asian incidents to hate crime hotlines; New York City has even launched a specific hotline for tracking such incidents (Chen et al., 2020). Regardless of what form these efforts take, it is important to engage on a deeper level with the structural foundations in which these xenophobic attitudes and prejudices are rooted. As Clissold and colleagues (2020, p. 422) eloquently stated, “it is only through listening to these communities and amplifying the lived experiences of these biases, accepting and appreciating many of the uncomfortable truths that accompany them” that we can respond effectively to the biases and discrimination that accompany the COVID-19 pandemic and other future outbreaks.

Footnotes

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) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported in part by funding from the Florida State University Collaborative Collision Seed Fund (Project #045678).

ORCID iDs

Brendan Lantz

Marin Wenger

Notes

Author Biographies

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. He was recently awarded both the 2020 ACJS Victimology New Scholar Award and the 2021 ACJS Academy New Scholar Award. His research interests focus on hate crime, violence, victimization, race/ethnicity, and co-offending, and has been funded by the National Science Foundation (NSF), National Institutes of Health (NIH), and Bureau of Justice Statistics (BJS), among others. His published work has appeared in a number of research outlets, including Social Problems, Journal of Research in Crime and Delinquency, Justice Quarterly, British Journal of Criminology, and Criminology & Public Policy.

Marin R. Wenger is an Assistant Professor in the College of Criminology and Criminal Justice and a faculty affiliate of the Hate Crime Research and Policy Institute at Florida State University. She received her PhD in Sociology from The Pennsylvania State University. Her research interests include race/ethnicity, stratification, hate crime, communities and crime, and quantitative methods. Her work has been funded by the National Institutes of Health (NIH), and has appeared in various research outlets, including Justice Quarterly, Journal of Experimental Criminology, Crime & Delinquency, Social Science Research, and City and Community.

References

Ancheta

A. N.

(2006). Race, rights, and the Asian American experience. Rutgers University Press.

Ansolabehere

Schaffner

B. F.

(2014). Does survey mode still matter? Findings from a 2010 multi-mode comparison. Political Analysis, 22(3), 285–303. https://doi.org/10.1093/pan/mpt025

Barde

(2004). Plague in San Francisco: An essay review. Journal of the History of Medicine and Allied Sciences, 59(3), 463–470. https://doi.org/10.1093/jhmas/jrh104

Bartoš

Bauer

Cahlíková

Chytilová

(2021). Covid-19 crisis and hostility against foreigners. European Economic Review, 137, 103818.

Bonilla-Silva

(2006). Racism without racists: Color-blind racism and the persistence of racial inequality in the United States. Rowman & Littlefield Publishers.

Burton

(2020). March 6). Why Asians in masks should not be the “face” of the coronavirus. Vox. https://www.vox.com/identities/2020/3/6/21166625/coronavirus-photos-racism

Centers for Disease Control and Prevention . (2020). New ICD-10-CM code for the 2019 novel coronavirus (COVID-19). https://www.cdc.gov/nchs/data/icd/Announcement-New-ICD-code-for-coronavirus-3-18-2020.pdf

Chen

J. A.

Zhang

Liu

C. H.

(2020). Potential impact of COVID-19–related racial discrimination on the health of Asian Americans. American Journal of Public Health, 110(11), 1624–1627. https://doi.org/10.2105/AJPH.2020.305858

Chou

R. S.

Feagin

J. R.

(2015). Myth of the model minority: Asian Americans facing racism. Routledge.

10.

Clissold

Nylander

Watson

Ventriglio

(2020). Pandemics and prejudice. International Journal of Social Psychiatry, 66(5), 421–423. https://doi.org/10.1177/0020764020937873

11.

Cohn

S. K.

(2012). Pandemics: Waves of disease, waves of hate from the Plague of Athens to AIDS. Historical Research, 85(230), 535–555. https://doi.org/10.1111/j.1468-2281.2012.00603.x

12.

Dolmage

J. T.

(2018). Disabled upon arrival: Eugenics, immigration, and the construction of race and disability. The Ohio State University Press.

13.

Eichelberger

(2007). SARS and New York’s Chinatown: The politics of risk and blame during an epidemic of fear. Social Science & Medicine, 65(6), 1284–1295. https://doi.org/10.1016/j.socscimed.2007.04.022

14.

Faulkner

Schaller

Park

J. H.

Duncan

L. A.

(2004). Evolved disease-avoidance mechanisms and contemporary xenophobic attitudes. Group Processes & Intergroup Relations, 7(4), 333–353. https://doi.org/10.1177/1368430204046142

15.

Federal Bureau of Investigation . (2019). Hate crime statistics, 2019. U.S. Department of Justice.

16.

Gee

G. C.

Spencer

M. S.

Chen

Takeuchi

(2007). A nationwide study of discrimination and chronic health conditions among Asian Americans. American Journal of Public Health, 97(7), 1275–1282. https://doi.org/10.2105/AJPH.2006.091827

17.

Gladfelter

A. S.

(2016). Fish out of water: Developing a theory of person-place mismatch and victimization. The Pennsylvania State University.

18.

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(1), 55–83. https://doi.org/10.1080/07418825.2015.1096952

19.

Gover

A. R.

Harper

S. B.

Langton

(2020). Anti-Asian hate crime during the COVID-19 pandemic: Exploring the reproduction of inequality. American Journal of Criminal Justice, 45(4), 647–667. https://doi.org/10.1007/s12103-020-09545-1

20.

Horowitz

J. M.

Brown

Cox

(2019). Race in America 2019. Pew Research Center. https://www.pewsocialtrends.org/2019/04/09/race-in-america-2019/

21.

Hwang

W.-C.

Goto

(2008). The impact of perceived racial discrimination on the mental health of Asian American and Latino college students. Cultural Diversity and Ethnic Minority Psychology, 14(4), 326–335. https://doi.org/10.1037/1099-9809.14.4.326

22.

Iganski

(2001). Hate crimes hurt more. American Behavioral Scientist, 45(4), 626–638. https://doi.org/10.1177/0002764201045004006

23.

Jeung

Nham

(2020). Incidents of coronavirus discrimination: A report for A3PCON and CAA. Asian Pacific Policy and Planning Council.

24.

Kennedy

Mercer

Keeter

Hatley

McGeeney

Gimenez

(2016). Evaluating online nonprobability surveys. Pew Research Center. https://assets.pewresearch.org/wp-content/uploads/sites/12/2016/04/Nonprobability-report-May-2016-FINAL.pdf

25.

Kil

S. H.

(2012). Fearing yellow, imagining white: Media analysis of the Chinese exclusion act of 1882. Social Identities, 18(6), 663–677. https://doi.org/10.1080/13504630.2012.708995

26.

Koopmans

Olzak

(2004). Discursive opportunities and the evolution of right‐wing violence in Germany. American Journal of Sociology, 110(1), 198–230. https://doi.org/10.1086/386271

27.

Lantz

(2022). Women who commit hate-motivated violence: Advancing a gendered understanding of hate crime. Social Science Research, 104, 102682. https://doi.org/10.1016/j.ssresearch.2021.102682.

28.

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(2), 193–224. https://doi.org/10.1080/07418825.2017.1399211

29.

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(3), 437–456. https://doi.org/10.1177/0093854818810314

30.

Lantz

Wenger

M.R.

(2022). Are Asian victims less likely to report hate crime victimization to the police? Implications for research and policy in the wake of the COVID-19 pandemic. Crime & Delinquency, 68(8), 1292–1319.

31.

Lantz

Wenger

M. R.

Malcom

Z. T.

(2022). Severity matters: The moderating effect of offense severity in predicting racial differences in reporting of bias and non-bias victimization to the police. Law and Human Behavior, 46(1), 15–29. https://doi.org/10.1037/lhb0000477

32.

Lee

(2019). America for Americans: A history of xenophobia in the United States. Basic Books.

33.

Lee

Yadav

(2020). The nativist fault line and precariousness of race in the time of Coronavirus. ASA Footnotes, 48, 17.

34.

Levin

McDevitt

(2002). Hate crimes revisited: America’s war on those who are different. Westview Press.

35.

Sheng

(2020). From fear to hate: How the COVID-19 pandemic sparks racial animus in the United States. ArXiv Preprint ArXiv:2007.01448.

36.

Malcom

Z. T.

Lantz

(2021). Hate crime victimization and weapon use. Criminal Justice and Behavior, 48(8), 1148–1165. https://doi.org/10.1177/0093854820983848

37.

Margolin

(2020). FBI warns of potential surge in hate crimes against Asian Americans amid coronavirus (27). ABC News.

38.

Markel

(1999). Quarantine!: East European Jewish immigrants and the New York city epidemics of 1892. JHU Press.

39.

McKiven

Jr. (2007). The Political construction of a natural disaster: The yellow fever epidemic of 1853. The Journal of American History, 94(3), 734–742. https://doi.org/10.2307/25095134

40.

McNeeley

Overstreet

(2018). Lifestyle-routine activities, neighborhood context, and ethnic hate crime victimization. Violence and Victims, 33(5), 932–948. https://doi.org/10.1891/0886-6708.VV-D-17-00136

41.

Mohr

J. C.

(2004). Plague and fire: Battling black death and the 1900 burning of Honolulu’s Chinatown. Oxford University Press.

42.

Molina

(2006). Fit to be citizens? In Fit to be citizens. University of California Press. https://www.degruyter.com/document/doi/10.1525/9780520939202/html

43.

Mudambi

(2019). South Asian American discourses: Engaging the yellow peril-model minority dialectic. Howard Journal of Communications, 30(3), 284–298. https://doi.org/10.1080/10646175.2018.1491431

44.

Myers

Lantz

(2020). Reporting racist hate crime victimization to the police in the United States and the United Kingdom: A cross-national comparison. The British Journal of Criminology, 60(4), 1034–1055. https://doi.org/10.1093/bjc/azaa008

45.

Nadal

K. L.

Wong

Sriken

Griffin

Fujii-Doe

(2015). Racial microaggressions and Asian Americans: An exploratory study on within-group differences and mental health. Asian American Journal of Psychology, 6(2), 136–144. https://doi.org/10.1037/a0038058.

46.

Nelkin

Gilman

S. L.

(1988). Placing blame for devastating disease. Social Research, 55(3), 361–378.

47.

Padela

A. I.

Heisler

(2010). The association of perceived abuse and discrimination after September 11, 2001, with psychological distress, level of happiness, and health status among Arab Americans. American Journal of Public Health, 100(2), 284–291. https://doi.org/10.2105/AJPH.2009.164954

48.

Perry

(2001). The name of hate: Understanding hate crimes. Routledge.

49.

Perry

Alvi

(2012). ‘We are all vulnerable’: The in terrorem effects of hate crimes. International Review of Victimology, 18(1), 57–71. https://doi.org/10.1177/0269758011422475

50.

Piatkowska

S. J.

Lantz

(2021). Temporal clustering of hate crimes in the aftermath of the Brexit vote and terrorist attacks: A comparison of Scotland and England and Wales. The British Journal of Criminology, 61(3), 648–669. https://doi.org/10.1093/bjc/azaa090

51.

Power

J. G.

(1995). Media dependency, bubonic plague, and the social construction of the Chinese other. Journal of Communication Inquiry, 19(1), 89–110. https://doi.org/10.1177/019685999501900106

52.

Prati

Pietrantoni

(2016). Knowledge, risk perceptions, and xenophobic attitudes: Evidence from Italy during the Ebola outbreak. Risk Analysis, 36(10), 2000–2010. https://doi.org/10.1111/risa.12537

53.

Randall

D. K.

(2019). Black death at the golden gate: The race to save America from the bubonic plague. W. W. Norton & Company.

54.

Ren

Feagin

(2021). Face mask symbolism in anti-Asian hate crimes. Ethnic and Racial Studies, 44(5), 746–758. https://doi.org/10.1080/01419870.2020.1826553

55.

Reny

T. T.

Barreto

M. A.

(2020). Xenophobia in the time of pandemic: Othering, anti-Asian attitudes, and COVID-19. Politics, Groups, and Identities, 0(0), 1–24. https://doi.org/10.1080/21565503.2020.1769693

56.

Rivers

Bailey

(2009). Inference from matched samples in the 2008 U.S. National Elections. Proceedings of the Joint Statistical Meetings, 1, 627–639. YouGov/Polimetrix.

57.

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(2), 330–350. https://doi.org/10.1891/0886-6708.VV-D-16-00173

58.

Simmons

A. D.

Bobo

L. D.

(2015). Can non-full-probability internet surveys yield useful data? A comparison with full-probability face-to-face surveys in the domain of race and social inequality attitudes. Sociological Methodology, 45(1), 357–387. https://doi.org/10.1177/0081175015570096

59.

Sue

D. W.

Bucceri

Lin

A. I.

Nadal

K. L.

Torino

G. C.

(2009). Racial microaggressions and the Asian American experience. Asian American Journal of Psychology, S(1), 88–101. https://doi.org/10.1037/1948-1985.s.1.88.

60.

Taylor

(2019). The psychology of pandemics: Preparing for the next global outbreak of infectious disease. Cambridge Scholars Publishing.

61.

Tessler

Choi

Kao

(2020). The anxiety of being Asian American: Hate crimes and negative biases during the COVID-19 Pandemic. American Journal of Criminal Justice, 45(4), 636–646. https://doi.org/10.1007/s12103-020-09541-5.

62.

Tuan

(1998). Forever foreigners or honorary whites? The Asian ethnic experience today. Rutgers University Press.

63.

Van der Veer

Ommundsen

Yakushko

Higler

Woelders

Hagen

K. A.

(2013). Psychometrically and qualitatively validating a cross-national cumulative measure of fear-based xenophobia. Quality & Quantity, 47(3), 1429–1444.

64.

Walker

(2020). News outlets contribute to anti-Asian racism with careless stock photos on coronavirus coverage. Media Matters for America.

65.

Wang

Horby

P. W.

Hayden

F. G.

Gao

G. F.

(2020). A novel coronavirus outbreak of global health concern. Lancet, 395(10223), 470–473. https://doi.org/10.1016/S0140-6736(20)30185-9

66.

Washer

(2004). Representations of SARS in the British newspapers. Social Science & Medicine, 59(12), 2561–2571. https://doi.org/10.1016/j.socscimed.2004.03.038

67.

Wellman

D. T.

(1993). Portraits of white racism. Cambridge University Press.

68.

Wenger

M. R.

Lantz

(2022a). Hate crime and place: The spatial and temporal concentration of bias-motivated crime in Washington, D.C. Journal of Interpersonal Violence, 37(13–14), NP10683–NP10708. https://doi.org/10.1177/0886260520987817

69.

Wenger

M. R.

Lantz

(2022b). Generalized hate: Bias victimization against non-Asian racial/ethnic minorities during the COVID-19 pandemic. Victims & Offenders, 1–24. https://doi.org/10.1080/15564886.2021.1974136

70.

White

A. I. R.

(2020). Historical linkages: Epidemic threat, economic risk, and xenophobia. Lancet, 395(10232), 1250–1251. https://doi.org/10.1016/S0140-6736(20)30737-6

71.

Wong

(2020, March 17). Video shows passenger defending Asian woman facing racism on New York subway. NBC News. https://www.nbcnews.com/news/asian-america/video-shows-passenger-defending-asian-woman-facing-racism-new-york-n1162296

72.

World Health Organization . (2015a). World Health Organization best practices for the naming of new human infectious diseases (WHO/HSE/FOS/15.1). World Health Organization. https://apps.who.int/iris/bitstream/handle/10665/163636/WHO_HSE_FOS_15.1_eng.pdf

73.

World Health Organization . (2015b). WHO issues best practices for naming new human infectious diseases [Media Note]. World Health Organization. https://www.who.int/mediacentre/news/notes/2015/naming-new-diseases/en/

74.

S. S.

(2020). Taking action to improve Asian American health. American Journal of Public Health, 110(4), 435–437. https://doi.org/10.2105/AJPH.2020.305596