White Categorical Ambiguity: Exclusion of Middle Eastern Americans From the White Racial Category

Abstract

Despite legal classification as White, Middle Eastern and North African (MENA) Americans experience high levels of discrimination, suggesting low social status precludes them from accessing the White racial category. After first demonstrating that the rated Whiteness of MENA Americans influences support for discriminatory policies (Study 1), the present research explores ratings and perceptions of Whiteness of MENA Americans by demonstrating how MENA ethnicities shift racial categorization of prototypically White and racially ambiguous targets (Studies 2–4), and how MENA Americans’ social status influences rated Whiteness (Study 5). As few studies have explored the relative Whiteness of different ethnicities in the United States despite the fluid history of the White racial category, the present studies have implications for the processes that inform White categorization and lay categorizations of MENA Americans.

Keywords

racial categorization Middle Eastern White

Middle Eastern and North African (MENA) Americans are legally classified as White ( Ex Part Mohriez, 1944; U.S. Census Bureau, 2018; U.S. Equal Employment Opportinity Commision, 2006) but face high levels of racial discrimination (Awad, 2010; Moradi & Hasan, 2004; Public Affairs Alliance of Iranian Americans, 2008). This unique categorical dissonance between legal classification and treatment in the United States highlights the precarious position of MENA Americans who are not legally recognized as a racial minority group, yet are unable to fully occupy a space inside the White racial category (Fourlas, 2015; Suleiman, 2010).

To date, no research has examined lay White categorization of MENA Americans, the contexts that may shift categorization, and implications for MENA Americans when not categorized as White. As lighter skinned MENA immigrants are rated as less threatening than darker skinned immigrants (Kunst et al., 2018), we propose that understanding when MENA Americans are included (and excluded) from the White racial category may have important implications for better understanding discrimination against MENA Americans, such as support for discriminatory travel bans. The present research examines the role of racial categorization and attitudes in support of discriminatory policies and tests whether MENA ethnographic information shifts racial categorization of racially ambiguous and prototypically White targets while exploring contexts that influence White categorization of MENA Americans.

Racial Categorization

When forming impressions, people automatically categorize individuals by race, gender, and age (Hewstone et al., 1991). While racial categorization may initially depend on physical cues such as skin color (Hill et al., 1995), biographical information learned from self-report or environmental cues is rapidly integrated until a final categorization is made (Freeman et al., 2013). For example, racial categorization can be influenced by racial labels (Eberhardt et al., 2003) and attire (Freeman et al., 2011). When faced with racial ambiguity stemming from competing physical information (e.g., multiracial targets) or stereotypically incongruent contextual cues, individuals are motivated to categorize targets into monoracial categories, often as White or Black in the United States (Freeman et al., 2016; Peery & Bodenhausen, 2008). Yet, recent research demonstrated that Black–White morphed faces are often classified as MENA (Chen et al., 2018; Nicolas et al., 2018), suggesting MENA Americans may not be perceived as prototypical members of the White racial category.

As Whiteness is associated with high status in the United States (e.g., Devos & Banaji, 2005) and lighter skinned MENA immigrants are seen as less threatening and more assimilated to American culture than darker skinned immigrants (Kunst et al., 2018), we proposed that individuals who exclude MENA Americans from the White racial category would more strongly support discriminatory policies regarding MENA Americans. Moreover, MENA stereotypes often signal low social status in Western contexts, including being stereotyped as low in warmth (Nicolas et al., 2018) and as terrorists (Ghavami & Peplau, 2013). We therefore proposed that targets presented with MENA ethnographic information would be excluded from the White racial category more frequently than targets with European ethnographic information.

Context and Social Status

Social contexts shift racial categorization, such that racially ambiguous targets were categorized as Black more frequently in a context with only White targets and as White more frequently in a context with only Black targets due to an anchoring effect (Ito et al., 2011). Thus, we sought to examine the extent to which MENA American targets would be categorized as White in a categorization task with prototypically Black compared to prototypically White targets. Following anchoring theory (Ostrom & Upshaw, 1968), we hypothesized that in a context with prototypically Black targets, standards for inclusion in the White racial category would expand, resulting in greater inclusion of MENA Americans in the White racial category compared to a context with only prototypically White targets, in which stricter standards for inclusion would emerge.

In contrast, making MENA Americans’ low social status salient should decrease categorization of MENA Americans as White. As social class moderates racial categorization, such that it takes less low-status information to categorize a target as not White when the racial minority identity is lower in the social class hierarchy (Young et al., 2015), we proposed that making MENA Americans’ low status salient would decrease categorization of MENA Americans as White.

Current Research

Racial categories are powerful structures for organizing information, and perceivers often rely on stereotypes to draw inferences and calibrate attitudes (Macrae & Bodenhausen, 2000). As darker skinned MENA targets are rated as more threatening (Kunst et al., 2018), the present research first sought to examine whether the effect of racial attitudes on support for anti-MENA American policies was moderated by ratings of the Whiteness of MENA Americans (Study 1) in order to underscore the importance of examining Whiteness ratings and categorization of MENA Americans. Thus, subsequent studies examined whether MENA American labels on prototypically White and racially ambiguous targets resulted in less frequent White categorization compared to European American labels (Studies 2–4). Additionally, we examined contexts in which categorization of MENA American targets as White may increase (contrasted with prototypically Black targets; Study 2) and decrease (when low social status is salient; Study 5). All study measures are reported in this article and in the Supplemental Material. The present studies focus on the ratings of MENA Americans’ Whiteness by U.S. participants. Utilizing multiple methodologies, the present research is the first to experimentally examine the racial categorizations of MENA Americans and downstream social consequences of their presumed “Whiteness.” Data and Materials for all studies can be found here: https://osf.io/3bafz/.

Study 1

Study 1 sought to examine the effect of ratings of MENA Americans as (non)prototypical members of the White racial category on discrimination against MENA Americans in order to demonstrate the impact of racial categorization on the treatment of MENA Americans. Specifically, we explored how ratings of Whiteness and attitudes toward MENA Americans interacted to predict support for discriminatory policies such as travel bans. As darker skinned MENA immigrants are rated as more threatening (Kunst et al., 2018), we hypothesized that individuals who rated MENA Americans as less prototypically White would be more likely to support discriminatory policies, regardless of attitudes toward MENA Americans. However, as Whiteness is tied to high social status in the United States (Devos & Banaji, 2005), we proposed that among individuals who perceived MENA Americans as more prototypically White, only those who endorsed negative attitudes toward MENA Americans would support discriminatory policies.

Method

Participants

An a priori power analysis for a hierarchical regression to examine the proposed moderation with 95% power to detect a medium effect size (d = 0.30) indicated a desired sample size of 119. A data collection stop point was set at 140 in case of high exclusion rates. Undergraduate participants (N = 140) who did not identify as MENA American completed the survey for partial course credit. Eight were excluded for failing three instructional attention checks, leaving a sample of 132 (65 women; M _age = 19.26, SD = 1.34; 51 Asian/Asian American, 35 White/Caucasian, 20 Latinx/Hispanic, 11 Black/African American, 14 multiracial).

Procedure and Measures

Participants indicated their attitude toward MENA Americans on a scale from 0 (very negative) to 100 (very positive; M = 74.80, SD = 21.96; range: 0–100). To measure ratings of MENA Whiteness, participants completed a visual spectrum measure (Figure 1), in which one White and one Black computer-generated male face were morphed on a 9-point race continuum, from Black (morph = −4) to White (morph = +4), using FaceGen Modeller (Blanz & Vetter, 1999). Participants indicated which of the images they believed best represented “Middle Eastern Americans” from 1 (100% Black) to 9 (100% White; M = 3.94, SD = 1.42, range: 1–8).

Figure 1.

Morphed images for visual spectrum measure, Studies 1 and 5.

On a scale from 1 (strongly disagree) to 7 (strongly agree), participants completed a measure of support for a MENA ban in the United States: “I support America developing a ban against Middle Easterners” and “America would be safer if we prevent Middle Easterners from entering the country,” r(132) = .80, p < .001 (M = 1.67, SD = 1.19; range: 1–7). On the same scale, participants completed a MENA registry support item, “America would be safer if there was a registry of Middle Easterners” (M = 2.31, SD = 1.58; range: 1–7) and an airport ban support item, “Middle Easterners should not be allowed to work in places where many Americans gather such as airports” (M = 1.30, SD = 0.74; range: 1–6). Measure order was randomized.

Results

Correlations indicated that rated Whiteness and attitudes were positively correlated, r(130) = .29, p = .001, and both Whiteness and attitudes were negatively correlated with discriminatory policy support, rs(130) < −.29, ps ≤ .001. Hierarchical linear regressions were conducted to examine the extent to which attitudes toward MENA Americans were associated with (1) support for a U.S. MENA ban, (2) support for a U.S. MENA registry, and (3) a MENA airport employee ban, and if these effects were moderated by ratings of Whiteness. Standardized measures of attitudes and rated Whiteness were entered in Step 1, and the interaction term was entered in Step 2. In each hierarchical linear regression, attitude and Whiteness were significant or marginally significant predictors of policy support, but effects were qualified by significant or marginally significant interaction terms (Table 1).

Table 1.

Study 1 Hierarchical Linear Regression and Conditional Effect Analyses.

Regression Steps and Conditional Effects	MENA Ban		MENA Registry		Airport Ban
Regression Steps and Conditional Effects	B (SE)	p	B (SE)	p	B (SE)	p
Step 1
Attitude	−.62 (.09)	<.001	−.65 (.13)	<.001	−.37 (.06)	<.001
Whiteness	−.30 (.09)	.001	−.26 (.13)	.045	−.11 (.06)	.063
Step 2
Attitude	−.56 (.08)	<.001	−.60 (.13)	<.001	−.34 (.06)	<.001
Whiteness	−.28 (.08)	.001	−.26 (.13)	.048	−.10 (.06)	.071
Interaction	.29 (.07)	<.001	.20 (.11)	.061	.14 (.05)	.004
Conditional effects of attitude on policy support by rated Whiteness
−1 SD Whiteness	−.57 (.10)	<.001	−.46 (.17)	.006	−.24 (.07)	.001
+1 SD Whiteness	.01 (.11)	.96	−.05 (.17)	.78	.04 (.07)	.61

Conditional effects revealed no significant difference in policy support based on attitudes among participants who rated MENA Americans as more prototypically White (+1 SD), but there was a significant difference among participants who rated MENA Americans as less prototypically White (−1 SD). Among individuals who rated MENA Americans as less prototypically White, only those with negative attitudes toward MENA Americans supported discriminatory policies (Figure 2). Alternative analyses examining the effect of attitudes on Whiteness with policy support measures as a moderator were not significant, R ²Δs < .007, ps > .31.

Figure 2.

Study 1 effect of rated Whiteness and attitudes toward MENA Americans on support for a MENA ban in the United States. MENA = Middle Eastern and North African.

Discussion

Regardless of attitudes, participants who rated MENA Americans as more prototypically White did not support discriminatory policies. Among participants who rated MENA Americans as less prototypically White, only those with negative attitudes toward MENA Americans supported discriminatory policies. While attitudes toward MENA Americans were significantly correlated with rated Whiteness of MENA Americans, the present study indicates that ratings of Whiteness are more than just a proxy for MENA attitudes. As Whiteness ratings had important implications for the treatment of MENA Americans, we believe it is important to examine the contexts under which ratings of Whiteness shift and next sought to examine the effect of context on White categorization of MENA Americans.

Study 2

Past research has demonstrated that racially ambiguous (White–Black) targets were categorized as Black more frequently in a context with only White targets and as White more frequently in a context with only Black targets (Ito et al., 2011) due to an anchoring effect (Ostrom & Upshaw, 1968), demonstrating the relative nature of racial categorization and highlighting the importance of context. As such, Study 2 sought to examine the effect of context, either all-White or White–Black, on categorization of MENA American targets as White. Categorization tasks allow for clear measurement of inclusion/exclusion from racial categories. In line with this past research, we hypothesized that MENA American targets would be categorized as White more frequently in a White–Black context than an all-White context but would be categorized as White less frequently than European American targets regardless of context as European Americans hold a higher social status than MENA Americans (Kteily et al., 2015). While racial categorization of racially ambiguous targets is more susceptible to top-down processes than the categorization of unambiguous targets (e.g., Ito et al., 2011), we first sought a strict test of the effect and employed prototypically White MENA American targets.

Method

Participants

As an a priori power analysis for a 2 (condition: all-White, White–Black context) × 2 (ethnicity: MENA, European) mixed analysis of variance (ANOVA) with 85% power, a small effect size (d = 0.3) and small correlation (r = .2) indicated an N = 162, a data collection stop point was set at 175 in case of exclusions. Undergraduate participants completed an in-lab study in exchange for partial course credit (N = 175). One MENA American participant was excluded, leaving a sample of 174 (114 women; M _age = 19.18, SD = 3.11, range: 18–55). The sample was racially diverse (85 Asian/Asian American, 46 White/Caucasian, 19 Latinx/Hispanic, 20 Black/African American, 4 multiracial).

Procedure and Measures

Participants completed a categorization task. Targets included 24 prototypically White male and 12 prototypically Black male targets (Chicago Face Database; Ma et al., 2015). Each target was egged and gray-scaled. Each White target was paired with one of four ethnicity labels: British, Irish, Iranian, or Syrian (12 European, 12 MENA targets), and each Black target was paired with one of four ethnicity labels: Jamaican, Angolan, Kenyan, or Nigerian (12 African/Caribbean targets). Participants were told all targets were U.S. citizens, and the semantic labels simply indicated a target’s ethnicity (semantic ethnicity labels influence racial categorization; Tskhay & Rule, 2015). For each trial, a fixation cross was presented for 500 ms, followed by the target until response. Participants were instructed to categorize targets as either “White” or “non-White” as quickly as possible via key presses. All participants completed eight practice trials and two blocks of test trials in which the categorization labels were flipped across the screen.

Participants in the all-White context condition completed 120 trials that included only the White male targets paired with European and MENA ethnicities. Participants in the White–Black context condition completed 180 trials that included White male targets paired with European and MENA ethnicities and Black male targets paired with African/Caribbean ethnicities. In both conditions, participants completed 60 MENA trials and 60 European trials (each White target was presented 5 times with the same ethnicity), and in the White–Black context condition, participants also completed 60 African/Caribbean trials (each Black target was presented 5 times with the same ethnicity).¹

Results

Responses for White targets were calculated across British and Irish (European) and Iranian and Syrian (MENA), resulting in composite European and MENA categorization frequency measures. A 2 (condition: all-White, White–Black) × 2 (ethnicity: MENA, European) mixed ANOVA on White categorization frequency with ethnicity as a within-subjects factor revealed significant effects of condition, F(1, 172) = 52.79, p < .001, d = 1.11, 95% confidence interval (CI _d ) = [0.66, 1.56], and ethnicity, F(1, 172) = 237.73, p < .001, d = 2.35, 95% CI _d = [1.96, 2.74], and a significant interaction, F(1, 172) = 22.57, p < .001, d = 0.72, 95% CI _d = [0.41, 1.03].

Participants categorized European American targets as White (M = 0.92, SE = 0.01) more frequently than MENA American targets (M = 0.63, SE = 0.04) in a White–Black context, F(1, 87) = 61.67, p < .001, d = 1.68, 95% CI _d = [1.19, 2.16], and in an all-White context (M _Euro = 0.84, SE = 0.02; M _MENA = 0.28, SE = 0.03), F(1, 85) = 188.25, p < .001, d = 2.98, 95% CI _d = [2.37, 3.60], though this effect was larger in an all-White context. Moreover, participants categorized MENA American targets as White more frequently in the White–Black context condition (M = 0.63, SE = 0.04) than the all-White context condition (M = 0.28, SE = 0.04), F(1, 172) = 43.04, p < .001, d = 1.00, 95% CI _d = [0.55, 1.44].² As African/Caribbean trials were only completed by participants in the White–Black context condition, conditional analyses are not presented, though they were rarely categorized as White (M = 0.04, SD = 0.06).

Discussion

Participants categorized prototypically White MENA American targets as White significantly less frequently than European American targets, and this effect was greatest in a White–Black context. Indeed, the presence of prototypically Black targets within the context significantly increased the White categorization frequency of MENA American targets. These results suggest an anchoring effect, such that the range of presented targets affected participants’ categorization and standard of comparison (e.g., Ostrom & Upshaw, 1968). The presence of Black targets significantly expanded standards for the White category, while the presence of only White targets resulted in significantly stricter standards for the White category. This is consistent with other work on racial perception and anchoring (Ito et al., 2011) but uniquely demonstrates the flexibility of White category inclusion/exclusion for MENA Americans.

Study 3

As MENA Americans are a diverse group that are not all prototypically White and Black–White mixed-race targets can be spontaneously categorized as MENA (Nicolas et al., 2018), we next examined perceptions of MENA Americans on a categorization task with a Black–White racial morphed spectrum of targets, thus examining how frequently racially ambiguous targets presented as MENA American are categorized as White compared to European American. In Study 3, all participants completed a racial categorization task that included prototypically White, prototypically Black, and racially ambiguous targets that were labeled either MENA American or European American. We hypothesized that participants would categorize MENA American targets as White less frequently than European American targets, regardless of the target’s racial prototypicality, as MENA American ethnicities signal lower status than European Americans (Ghavami & Peplau, 2013) and Whiteness is associated with high status (Devos & Banaji, 2005).

Method

Participants

Undergraduate participants (N = 263) completed the in-lab study for course credit. Ten were excluded for identifying as MENA American, leaving a sample of 253 (M _age = 19.03, SD = 1.39; 174 women) that was racially diverse (115 Asian American, 99 White, 18 Latino/Hispanic, 13 Black/African American, 8 multiracial).³ Although our intention was to examine participant race, participant race did not alter categorization of MENA targets (see Supplemental Material). For parsimony, we collapsed across participant race to examine the categorization based on labels. A sensitivity power analysis indicated the present sample had 90% power to detect a small effect size (d = 0.20) for a paired samples t test (MENA American or European American).

Procedures and Measures

Participants completed the categorization task described below. The task employed 77 morphed male faces that represented 11 subcategories ranging from 100% White to 0% White (100% Black) in 10% increments of racial ambiguity (see Krosch et al., 2013). Participants were presented with these targets on red or blue backgrounds that signaled different ethnicities; background color was counterbalanced across ethnicities. The MENA ethnicity label was either “Iranian” or “Lebanese,” while the European label was either “British” or “Irish.” Participants were informed that targets were American and were instructed to classify the faces as “White” or “non-White” as quickly as possible via key presses.

Participants completed 10 practice trials and 154 test trials (each face was presented once with a red background and once with a blue background). Each trial began with a fixation cross (1,000 ms) followed by the target and colored background that remained in the center of the screen either until the participant responded or for 2,000 ms. The categorization task was a 2 (regional ethnicity: European, MENA) × 2 (ethnicities: British/Iranian, Irish/Lebanese) mixed design with regional ethnicity as a within-subjects variable. See Supplemental Material for additional point of subjective equality analysis.

Results

Initial analyses confirmed no difference for categorization patterns of Iranian and British or Lebanese and Irish, F(1, 250) = 1.61, p = .21, d = 0.16, 95% CI _d = [−0.09, 0.41], thus we collapsed across these to examine regional ethnicity. Paired samples t tests (regional ethnicity: European, MENA) revealed participants categorized MENA American targets as White less frequently than European American targets at all levels of the racial morph (Table 2).

Table 2.

Probability of Categorizing Targets as White by Regional Ethnicity at Each Level of the Racial Morph (Study 3).

Racial Morph Level	MENA M (SE)	European M (SE)	t	p	d	95% CI _d
100% White	.60 (.03)	.95 (.01)	14.27	<.001	1.21	[0.94, 1.48]
90% White	.57 (.03)	.91 (.01)	13.50	<.001	1.14	[0.87, 1.40]
80% White	.44 (.03)	.83 (.01)	11.56	<.001	1.08	[0.82, 1.34]
70% White	.40 (.02)	.80 (.02)	16.13	<.001	1.49	[1.21, 1.77]
60% White	.33 (.02)	.73 (.01)	16.61	<.001	1.62	[1.33, 1.90]
50% White	.16 (.01)	.56 (.02)	16.73	<.001	1.52	[1.24, 1.80]
40% White	.27 (.01)	.65 (.02)	14.81	<.001	1.50	[1.22, 1.78]
30% White	.10 (.01)	.45 (.02)	13.47	<.001	1.17	[0.90, 1.44]
20% White	.07 (.01)	.39 (.03)	12.00	<.001	0.99	[0.73, 1.25]
10% White	.11 (.01)	.44 (.02)	12.47	<.001	1.41	[1.13, 1.68]
0% White	.06 (.01)	.38 (.03)	12.61	<.001	0.95	[0.69, 1.21]

Discussion

Participants categorized MENA American targets as White significantly less than European American targets regardless of the target’s racial ambiguity, such that even prototypically Black and White targets were categorized as White more frequently when a European ethnicity was cued than when a MENA ethnicity was cued. While these results strongly suggest that MENA ethnicity cues imbue information that excludes targets from the White racial category due to MENA Americans’ low status, they may also suggest that European ethnicity cues imbue White inclusion information due to their high status. Additionally, the forced choice nature of categorization tasks may not accurately map on to lay classification processes (Nicolas et al., 2018). As such, in the remaining studies, we next examined the ratings of MENA American’s Whiteness on explicit scales in order to more carefully isolate rated Whiteness of MENA Americans.

Study 4

Study 4 was preregistered (https://osf.io/74qh5) and examined prototypically White MENA American targets rated on an explicit scale (0%–100% White). We again hypothesized that participants would indicate that MENA American targets were significantly less White than European American targets. Moreover, Asian ethnicities were included to mitigate demand effects, to better conceal hypotheses, and to compare rated MENA American Whiteness to a prototypical racial minority group in order to isolate the extent to which MENA ethnicities imbue White exclusion information. We returned to an all-White context (i.e., all White faces) given this produced the strongest exclusion of MENA Americans from the White racial category in Study 2.

As past research has demonstrated that it takes less low-status information to categorize a target as not White when the racial minority identity is lower in the social class hierarchy among racial minorities and Whites (Young et al., 2015), we proposed that MENA Americans would be rated as less White than European Americans by both racial minorities and Whites, as suggested by Studies 1–3 that included racially diverse samples. Yet, as we were primarily interested in understanding racial categorization of MENA American because it effects support for discriminatory policies (Study 1), and White Americans are the prototypical perpetrators of racial discrimination (Inman & Baron, 1996), in the remaining studies only White American participants were recruited.

Method

Participants

A preregistered power analysis for a 3 (ethnicity: MENA, European, Asian) × 2 (block: 1, 2) mixed ANOVA with ethnicity as a within-subjects factor, 95% power, a small correlation between ethnicity categories (r = .20), and a medium effect size (d = .40) indicated a desired sample of 106. White participants (N = 106) were recruited via Amazon Mechanical Turk (MTurk). Thirteen were excluded for failing instructional attention checks, leaving 93 participants (42 women; M _age = 40.49, SD = 13.42).

Procedure and Measures

Participants completed 27 trials in which 1 of 27 White male faces (Chicago Face Database; Ma et al., 2015) and 1 of 9 ethnic labels were presented below the face (European: Irish, British, German; MENA: Iranian, Syrian, Lebanese; Asian: Chinese, Japanese, Korean). Participants were randomly assigned to one of two blocks in which target–ethnicity pairings were different (e.g., 50% of participants saw Target “A” paired with a European ethnicity and 50% of participants saw Target “A” paired with a MENA ethnicity). On each trial, participants indicated how likely they would be to classify the person as “White” on a scale from 0 (not at all) to 100 (very much). Trial order was randomized.⁴

Results

Rated Whiteness was calculated for the three regional ethnicities (MENA, European, Asian). A 3 (regional ethnicity: MENA, European, Asian) × 2 (block) mixed ANOVA revealed a significant effect of regional ethnicity, F(2, 182) = 51.83, p < .001, d = 1.51, 95% CI _d = [1.15, 1.87], no effect of block, F(1, 91) = 3.09, p = .08, d = 0.37, 95% CI _d = [−0.05, 0.78], and no interaction, F(2, 182) = 1.24, p = .29, d = 0.23, 95% CI _d = [−0.06, 0.52]. Bonferroni corrected post hoc tests indicated European Americans (M = 79.72, SE = 1.57) were rated as more White than MENA Americans (M = 60.13, SE = 2.13), t(93) = 8.63, p < .001, d = 1.79, 95% CI _d = [1.40, 2.17], and Asian Americans (M = 62.77, SE = 2.22), t(93) = 7.54, p < .001, d = 1.56, 95% CI _d = [1.19, 1.92]. There was no significant difference between MENA and Asian Americans, t(93) = 1.71, p = .32, d = 0.34, 95% CI _d = [0.05, 0.63] (Figure 3).

Figure 3.

Study 4, rated Whiteness of European, MENA, and Asian American targets with means and standard errors.

Discussion

In Study 4, MENA Americans rated Whiteness did not significantly differ from a prototypical racial minority group, suggesting that MENA ethnicities do indeed cue information that excludes targets from the White racial category and that the present findings are not simply a product of European ethnicities cuing White inclusion. Moreover, Study 4 was conducted with an all-White context and employed an explicit rating measure of Whiteness for prototypically White targets. As such, we believe the present findings are a strong test of our hypothesis that lay perceivers do not consider MENA Americans prototypical members of the White racial category.

Study 5

As salient low-status social or economic identities can shift racial categorization away from Whiteness (Penner & Saperstein, 2008) and we proposed that MENA ethnicities imbue information that excludes targets from the White racial category due to the low social status of MENA Americans, we next sought to manipulate social status. We hypothesized that highlighting discrimination against MENA Americans would make their low social status in the United States salient, resulting in lower ratings of MENA Americans’ Whiteness compared to a control condition. Study 5 was preregistered: https://osf.io/s3qrp.

Method

Participants

A preregistered data collection stop point was set at 110, with an anticipated analytical sample of 100 participants in order to achieve 50 participants per condition based on recommendations for unknown effect sizes (Simmons et al., 2011). MTurk workers who identified as White (N = 110) during a brief demographic questionnaire submitted the study. Eleven participants did not identify as White at the end of the session, seven did not complete the full survey, and five failed manipulation check questions (described below) and were excluded, leaving 87 participants (50 women, 57.50%; M _age = 41.03, SD = 14.86).

Procedure and Measures

Participants were informed they would be completing two unrelated studies on cognition and perception. Participants completed the cognition portion by reading and answering questions about two newspaper articles. All participants first read a neutral article (about left-handedness; Craig et al., 2012) and completed questions and then were randomly assigned to read either a second neutral article (control; U.S. moving rates) or an article about the rise in discrimination against MENA Americans in the United States (discrimination prime; articles in the Supplemental Material). Participants then completed questions to verify their attention to the article content and, if accurate (after at most two attempts⁵), continued to the perception portion of the survey. The discrimination prime article indicated that MENA Americans face “discrimination from individuals of all ethnicities” and never highlighted Whites as the primary perpetrators. Participants then responded to filler questions, followed by the same visual spectrum measure from Study 1 (Figure 1), indicating which image best represented “Middle Eastern Americans.” Lastly, participants completed a 3-item perceived Whiteness measure, “Do you perceive Middle Easterners…” “as ‘White’,” “to be ‘White’,” and “as prototypical of ‘White’ people,” on a scale from 1 (not at all) to 7 (very much; α = .95).

Results

Participants in the discrimination prime condition chose an image for MENA Americans on the visual spectrum that was less prototypically White (M = 4.14, SD = 1.16) than participants in the control condition (M = 4.71, SD = 1.27), t(85) = 2.18, p = .032, d = 0.47, 95% CI _d = [0.03, 0.90]. Participants’ ratings of MENA American Whiteness did not significantly differ in the discrimination prime condition (M = 3.01, SD = 1.61) and control condition (M = 2.89, SD = 1.43), t(85) = 0.34, p = .74, d = 0.08, 95% CI _d = [−0.34, 0.50]. Ratings were significantly below the scale mean, indicating low explicit ratings of Whiteness, t(86) = 943, p < .001, d = 1.01, 95% CI _d = [0.56, 1.45].

Discussion

Highlighting the low status of MENA Americans shifted selection of prototypical group members to less prototypically White targets, but unexpectedly, not explicit ratings of Whiteness. The explicit nature of this question may have enacted social desirability concerns, though ratings for this measure were significantly below the scale mean. As Study 1 demonstrated that rated Whiteness of prototypical MENA Americans shifted support for discriminatory policies, the present study suggests that discrimination against MENA Americans results in less perceived Whiteness of MENA Americans, which may in turn result in greater support for discriminatory policies against MENA Americans.

General Discussion

Despite legal classification as White in the United States and past scholars having described MENA Americans as “honorary Whites” who are afforded some of the benefits of White privilege (Suleiman, 2010), this is in stark contrast to the high levels of dehumanization faced by MENA Americans (Kteily et al., 2015). To elucidate this incongruent understanding of MENA Americans’ status in the United States, we sought to examine the racial categorical ambiguity of MENA Americans. Underscoring the importance of understanding when MENA Americans are afforded inclusion in the White racial category, the present report demonstrates that greater support for discriminatory policies against MENA Americans was only found among participants who held negative attitudes toward MENA Americans and rated MENA Americans as less White (Study 1).

As White ratings influenced support for discriminatory policies, contexts and conditions that may shift categorization and ratings of MENA Americans’ Whiteness were next examined. MENA American ethnographic information resulted in prototypically White and racially ambiguous targets being categorized as White less frequently (Studies 2 and 3) and rated as less White (Study 4) than the same targets with a European ethnicity, indicating simple ethnographic information shifted racial categorization. While MENA Americans were categorized as White at low rates, inclusion in the White category was more frequent when MENA targets were contrasted with African/Caribbean American targets (Study 2) and when the low social status of MENA Americans was not salient (Study 5). This research demonstrates the fluidity of MENA American racial categorization and indicates that MENA Americans’ inclusion (and exclusion) from the White racial category may be one component that determines whether MENA Americans are dehumanized (Kteily et al., 2015) or are afforded some of the benefits of White privilege (Suleiman, 2010).

While individuals’ ethnicities are rarely semantically cued as in the current studies, ethnicity, or perceived ethnicity, can be gleamed from other cues such as names on job applications. Additionally, certain environments (e.g., airport security) may make perceivers more motivated to ascertain ethnicities or to categorize racially ambiguous targets as MENA American (Freemen et al., 2013). MENA Americans are phenotypically diverse, and such racial ambiguity should inherently motivate individuals to ascertain additional information, including ethnographic information. Yet, MENA ethnographic information shifted racial ratings and categorization among even prototypically White and Black targets, not just racially ambiguous targets, indicating the powerful effect of higher order social cognitive processes, such as knowledge of MENA Americans’ low social status (Freeman & Johnson, 2016). We encourage future research to examine the effect of more subtle cues of MENA ethnicity and the role of environment in guiding dynamic person perception.

Notably, only male targets were employed based on the growing literature demonstrating that race and sex categories are intertwined (e.g., Galinsky et al., 2013). Yet, in line with the subordinate male target hypothesis which argues that male outgroup members are more prone to bias due to evolutionary concerns of male dominance and aggression (Navarrete et al., 2010), recruiters rated resumes of MENA men more negatively than comparable resumes of MENA women (Derous et al., 2015). As such, we encourage future research to examine perceptions of MENA American women to more fully understand the nuances of MENA American racial categorization.

In conclusion, our findings reveal the racial categorical ambiguity of MENA Americans who, despite legal classification as White, are rarely included in the White racial category by lay perceivers. While MENA Americans’ racial categorization is fluid and dependent on context, discrimination against MENA Americans results in less perceived Whiteness of MENA Americans, which may in turn result in greater support for discriminatory policies against MENA Americans, demonstrating the powerful implications of categorical ambiguity for MENA Americans.

Supplemental Material

WhiteSpectrum_SUPPLEMENT_Final - White Categorical Ambiguity: Exclusion of Middle Eastern Americans From the White Racial Category

WhiteSpectrum_SUPPLEMENT_Final for White Categorical Ambiguity: Exclusion of Middle Eastern Americans From the White Racial Category by Kimberly E. Chaney, Diana T. Sanchez and Lina Saud in Social Psychological and Personality Science

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 by a National Science Foundation Graduate Research Fellowship to Kimberly E. Chaney.

ORCID iD

Kimberly E. Chaney

Supplemental Material

The supplemental material is available in the online version of the article.

Notes

References

Awad

G. H.

(2010). The impact of acculturation and religious identification on perceived discrimination for Arab/Middle Eastern Americans. Cultural Diversity and Ethnic Minority Psychology, 16(1), 59–67.

Blanz

Vetter

(1999). A morphable model for the synthesis of 3D faces. In Proceedings SIGGRAPH’99 (pp. 187–194). https://gravis.dmi.unibas.ch/publications/Sigg99/morphmod2.pdf

Chen

J. M.

Pauker

Gaither

S. E.

Hamilton

D. L.

Sherman

J. W.

(2018). Black + White = Not White: A minority bias in categorizations of Black–White multiracials. Journal of Experimental Social Psychology, 78, 43–54.

Craig

M. A.

DeHart

Richeson

J. A.

Fiedorowicz

(2012). Do unto others as others have done unto you? Perceiving sexism influences women’s evaluations of stigmatized racial groups. Personality and Social Psychology Bulletin, 38(9), 1107–1119. https://doi.org/10.1177/0146167212445210

Derous

Ryan

A. M.

Serlie

A. W.

(2015). Double jeopardy upon resume screening: When Achmed is less employable than Aisha. Personnel Psychology, 68(3), 659–696.

Devos

Banaji

M. R.

(2005). American = White? Journal of Personality and Social Psychology, 88(3), 447–466.

Eberhardt

J. L.

Dasgupta

Banaszynski

T. L.

(2003). Believing is seeing: The effects of racial labels and implicit beliefs on face perception. Personality and Social Psychology Bulletin, 29(3), 360–370.

Ex part Mohriez, 54 F. Supp. 941, 942 (D. Mass. 1944).

Fourlas

G. N.

(2015). Being a target: On the racialization of Middle Eastern Americans. Critical Philosophy of Race, 3(1), 101–123.

10.

Freeman

J. B.

Johnson

K. L.

(2016). More than meets the eye: Split-second social perception. Trends in Cognitive Sciences, 20(5), 362–374.

11.

Freeman

J. B.

Han

Ambady

(2013). Influences of culture and visual context on real-time social categorization. Journal of Experimental Social Psychology, 49(2), 206–210.

12.

Freeman

J. B.

Pauker

Sanchez

D. T.

(2016). A perceptual pathway to bias: Interracial exposure reduces abrupt shifts in real-time race perception that predict mixed-race bias. Psychological Science, 27(4), 502–517.

13.

Freeman

J. B.

Penner

A. M.

Saperstein

Scheutz

Ambady

(2011). Looking the part: Social status cues shape race perception. PLoS One, 6(9), e25107.

14.

Galinsky

A. D.

Hall

E. V.

Cuddy

A. J.

(2013). Gendered races: Implications for interracial marriage, leadership selection, and athletic participation. Psychological Science, 24(4), 498–506.

15.

Ghavami

Peplau

L. A.

(2013). An intersectional analysis of gender and ethnic stereotypes: Testing three hypotheses. Psychology of Women Quarterly, 37(1), 113–127.

16.

Hewstone

Hantzi

Johnston

(1991). Social categorization and person memory: The pervasiveness of race as an organizing principle. European Journal of Social Psychology, 21(6), 517–528.

17.

Hill

Bruce

Akamatsu

(1995). Perceiving the sex and race of faces: The role of shape and colour. Proceedings of the Royal Society of London B: Biological Sciences, 261(1362), 367–373.

18.

Inman

M. L.

Baron

R. S.

(1996). Influence of prototypes on perceptions of prejudice. Journal of Personality and Social Psychology, 70(4), 727–739.

19.

Ito

T. A.

Willadsen-Jensen

E. C.

Kaye

J. T.

Park

(2011). Contextual variation in automatic evaluative bias to racially-ambiguous faces. Journal of Experimental Social Psychology, 47(4), 818–823.

20.

Krosch

A. R.

Berntsen

Amodio

D. M.

Jost

J. T.

Van Bavel

J. J.

(2013). On the ideology of hypodescent: Political conservatism predicts categorization of racially ambiguous faces as Black. Journal of Experimental Social Psychology, 49(6), 1196–1203.

21.

Kteily

Bruneau

Waytz

Cotterill

(2015). The ascent of man: Theoretical and empirical evidence for blatant dehumanization. Journal of Personality and Social Psychology, 109(5), 901–931.

22.

Kunst

J. R.

Dovidio

J. F.

Dotsch

(2018). White look-alikes: Mainstream culture adoption makes immigrants “look” phenotypically White. Personality and Social Psychology Bulletin, 44(2), 265–282.

23.

D. S.

Correll

Wittenbrink

(2015). The Chicago Face Database: A free stimulus set of faces and norming data. Behavior Research Methods, 47, 1122–1135.

24.

Macrae

C. N.

Bodenhausen

G. V.

(2000). Social cognition: Thinking categorically about others. Annual Review of Psychology, 51(1), 93–120.

25.

Moradi

Hasan

N. T.

(2004). Arab American persons’ reported experiences of discrimination and mental health: The mediating role of personal control. Journal of Counseling Psychology, 51, 418–428.

26.

Navarrete

C. D.

McDonald

M. M.

Molina

L. E.

Sidanius

(2010). Prejudice at the nexus of race and gender: An outgroup male target hypothesis. Journal of Personality and Social Psychology, 98(6), 933–945.

27.

Nicolas

Skinner

A. L.

Dickter

C. L.

(2018). Other than the sum: Hispanic and Middle Eastern categorizations of Black–White mixed-race faces. Social Psychological and Personality Science. https://doi.org/10.1177/1948550618769591

28.

Ostrom

T. M.

Upshaw

H. S.

(1968). Psychological perspective and attitude change. In Greenwald

A. G.

Bock

T. C.

Ostrom

T. M.

(Eds.), Psychological foundations of attitudes (pp. 217–242). Academic Press.

29.

Public Affairs Alliance of Iranian Americans. (2008). Public Opinion Survey of Iranian Americans. http://paaia.org/CMS/Data/Sites/1/PDFs/survey_of_iranian_americans_final_report_dec_102008.pdf

30.

Peery

Bodenhausen

G. V.

(2008). Black + White = Black: Hypodescent in reflexive categorization of racially ambiguous faces. Psychological Science, 19(10), 973–977.

31.

Penner

A. M.

Saperstein

(2008). How social status shapes race. Proceedings of the National Academy of Sciences, 105(50), 19628–19630.

32.

Simmons

J. P.

Nelson

L. D.

Simonsohn

(2011). False positive psychology: Undisclosed flexibility in data collection and analysis allows presenting anything as significant. Psychological Science, 22, 1359–1366

33.

Suleiman

(Ed.). (2010). Arabs in America: Building a new future. Temple University Press.

34.

Tskhay

K. O.

Rule

N. O.

(2015). Semantic information influences race categorization from faces. Personality and Social Psychology Bulletin, 41(6), 769–778.

35.

U.S. Census Bureau. (2018). Memorandum 2018.02: Using two separate questions for race and ethnicity. https://www.census.gov/programs-surveys/decennial-census/2020-census/planning-management/memo-series/2020-memo-2018_02.html

36.

U.S. Equal Employment Opportunity Commision. (2006). Compliance Manual No 915.003, Section 15: Race & Color Discrimination 15-3. www.eeoc.gov/policy/docs/race-color.pdf

37.

Young

D. M.

Sanchez

D. T.

Wilton

L. S.

(2015). Too rich for diversity: Socioeconomic status influences multifaceted person perception of Latino targets. Analyses of Social Issues and Public Policy, 16(1), 392–416.

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