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Proceedings of the National Academy of Sciences of the United States of America logoLink to Proceedings of the National Academy of Sciences of the United States of America
. 2022 Feb 7;119(7):e2117940119. doi: 10.1073/pnas.2117940119

Middle Eastern and North African Americans may not be perceived, nor perceive themselves, to be White

Neda Maghbouleh a,b,1, Ariela Schachter c, René D Flores d
PMCID: PMC8851556  PMID: 35131945

Significance

The US government’s classification of Middle Eastern and North African (MENA) Americans as White means there is no direct way to numerically count members of this group in official statistics. Therefore, any potential disparities and inequalities faced by MENA Americans remain hidden. Nevertheless, we find that MENA Americans may not be perceived, nor perceive themselves, to be White. These findings underscore the minoritized status of MENA Americans and support the inclusion of a new MENA identity category in the US Census. This would allow researchers to examine the social, economic, and health status of this growing population and empower community advocates to ameliorate existing inequalities.

Keywords: race and ethnicity, racial categories, White, Middle Eastern, North African

Abstract

People of Middle Eastern and North African (MENA) descent are categorized as non-White in many Western countries but counted as White on the US Census. Yet, it is not clear that MENA people see themselves or are seen by others as White. We examine both sides of this ethnoracial boundary in two experiments. First, we examined how non-MENA White and MENA individuals perceive the racial status of MENA traits (external categorization), and then, how MENA individuals identify themselves (self-identification). We found non-MENA Whites and MENAs consider MENA-related traits—including ancestry, names, and religion—to be MENA rather than White. Furthermore, when given the option, most MENA individuals self-identify as MENA or as MENA and White, particularly second-generation individuals and those who identify as Muslim. In addition, MENAs who perceive more anti-MENA discrimination are more likely to embrace a MENA identity, which suggests that perceived racial hostility may be activating a stronger group identity. Our findings provide evidence about the suitability of adding a separate MENA label to the race/ethnicity identification question in the US Census, and suggest MENAs’ official designation as White may not correspond to their lived experiences nor to others’ perceptions. As long as MENA Americans remain aggregated with Whites, potential inequalities they face will remain hidden.


Among North American and European countries that collect population-level data on race and ethnicity, the United States stands alone in counting Middle Eastern and North African (MENA) individuals as White. This stems from a legal ruling in 1944 that deemed all persons from the MENA region, regardless of their religion, “White by law” alongside European Americans (13). This decision has had profound consequences for the collection of sociodemographic data. For one, the US Census currently has no direct way to identify MENA individuals, as they are considered part of the White category by the federal government. However, using small surveys, scholars have found that MENAs may be different in some regards from the White population. They are more likely to live below the poverty line, rent rather than own their homes, and report worse health outcomes, including higher age-adjusted mortality risk and lower birth weights (46). In countries that collect data on MENA as racialized minorities or people of color, MENAs report rates of discrimination higher than Whites, and on par with other groups of color (7, 8). Such findings suggest that MENA’s official designation in the United States as White does not correspond to their lived experiences. Nevertheless, given the diversity of the MENA population, composed of 19 different nationalities and 11 ethnicities who arrived and settled across the United States at different time periods, such empirical trends cannot be fully examined without finer-grained Census-level data (9). And because Census definitions of race and ethnicity influence how data are collected in survey research, the federal Office of Management and Budget’s decision to continue counting MENA as White in the 2020 Census has the downstream effect of rendering this group invisible in most available survey data.

For most of the United States' history, Hispanics were also not identifiable from the larger White population, despite evidence of discrimination and systematic racialization (10, 11). Nevertheless, in 1970 a group of Hispanic activists, ethnic entrepreneurs, and Census officials came together to create an ethnicity question in the US Census to identify Hispanics (12). For nearly 50 y, MENA activists have similarly called for the creation of a MENA identity category apart from the White category in federal data. In making their case, activists argued that MENA populations are not actually perceived by others in the United States as White. They have suggested that September 11, 2001 (9/11), the War on Terror, and increasingly divisive rhetoric in United States political campaigns further differentiated this group from Whites, leading to discriminatory experiences (13, 14). However, due to the invisibility of this population in administrative data, it has been difficult for researchers to empirically test these claims.

The activists’ suggestion to the MENA community to “Check it Right, You Ain’t White” warrants systematic examination (15). First, it is not clear whether non-MENA Whites think of MENAs as part of the White population or as a separate non-White group (16). MENAs’ perceived racial status may shape how Whites treat MENAs in their everyday lives (17, 18). There is some evidence that MENA-origin names hold non-White ethnic/racial connotations in the United States, but less is known about the comparative effects of multiple social characteristics, like names, skin tone, and religion, on the classification of MENA people (19). Furthermore, given the significant linguistic, ethnic, and phenotypic heterogeneity of the MENA population, it is unclear who is perceived as MENA by others, and where the boundaries of this panethnic label may lie (20).

Second, it is not clear how MENA individuals will self-identify (21). Identification as White was a conscious effort pursued by prior generations of immigrants to qualify for naturalization and signal their entry into the American mainstream (2224). The White category may continue to be preferred by certain immigrant generations or specific ethnic, religious, and national groups from the diverse MENA region. For example, in the United States, where White and Christian identities are closely linked, Christian Arab Americans are more likely than Muslim Arab Americans to self-identify as White (25, 26). At the same time, there is evidence that MENA Americans, as a class, face prejudice and discrimination as in the Trump Administration’s Executive Orders 13769 (2017) and 13780 (2017–2021), which largely targeted potential migrants of MENA origin (27). Such racial hostility may trigger reactive ethnicity or ethnic militancy in reaction to perceived discrimination by the mainstream (28, 29). External attacks may increase MENA’s internal solidarity and strengthen their identification as MENA (30). Nevertheless, even if MENA individuals perceive discrimination from others, this does not necessarily mean that they will identify as non-White. Some express worry that identifying as MENA in the Census may result in state surveillance based on alleged national security interests (31). Others may choose to identify as White as a coping mechanism to deal with perceived racial animosity or even due to different ethnoracial categories or ideologies from their countries of origin (3234). It is unclear whether a MENA category is equally appealing to all members of this heterogenous population.

Moreover, MENA individuals may not see identification as a zero-sum decision between MENA and White, and instead choose to identify as both White and MENA. Indeed, similar identification patterns have been observed among descendants of Hispanic and Asian immigrants, whose ultimate position within the United States ethnoracial hierarchy remains uncertain (35).

In response to growing public pressure, the Census Bureau conducted a preliminary internal test in 2015 to examine how MENA populations would react to the addition of a MENA category in Census forms. Based on these internal results, the report recommended a dedicated MENA category separate from the White box on the 2020 US Census. This also would have meant that persons marking both MENA and White would be counted as MENA in the Census’ analyses, as this is how persons who mark one White (majority) and one non-White (minority) box are counted (35). However, in 2018, Census Bureau officials rejected the recommendation to add a MENA category on the grounds that “more research and testing is needed” (36).

We heed the calls for more evidence by empirically examining both sides of this ethnoracial boundary: 1) how Whites and MENAs in the United States perceive the racial status of MENA traits (external categorization), and 2) how MENA American individuals identify themselves (self-identification).

Materials and Methods

In our first experiment focused on external categorization we assessed how both non-MENA, non-Hispanic Whites, and MENAs perceive the racial status of MENA traits. Identifying MENA respondents is not easy or straightforward. Many survey companies in the United States do not explicitly identify MENA individuals. Furthermore, the lack of Census data on this population makes it difficult to develop sampling frames to create nationally representative samples of MENA respondents. Therefore, we turned to online survey platforms to collect nonprobability samples of respondents. Recent evidence suggests that, for online experiments, crowdsource-recruited, nonprobability samples can provide similar results to population-based samples (37, 38). The survey experiments, which were approved by the Institutional Review Board of the Washington University in St. Louis, were implemented in summer 2021. Informed consent was obtained from all respondents (a detailed description of all sampling and survey procedures is in SI Appendix, Sampling and Survey Procedures).

We relied on three different samples of online respondents. The first sample consisted of 421 adults living in the United States who identified as non-Hispanic White, as this group has historically played a key role in the formation and content of racial boundaries (39). We contacted these respondents via Prolific, an online crowdsourcing platform. We excluded respondents (n = 4) who identified as White but listed one or more MENA grandparents, because self-identified Whites with family roots in the Middle East or North Africa may have different perceptions about the racial status of MENA traits than those whose families originate elsewhere (40).

For the second and third samples, we identified MENA respondents using two different strategies: self-identification and reported ancestry. First, we surveyed 333 adult United States residents who had been preidentified as Middle Eastern in Prolific’s pool of respondents via this question: “Please indicate your ethnicity (i.e., peoples’ ethnicity describes their feeling of belonging and attachment to a distinct group of a larger population that shares their ancestry, color, language or religion).” We selected all individuals who self-identified as Middle Eastern. Unfortunately, Prolific’s question did not include a North African identity option, which is an important omission since individuals of North African descent are an estimated 30% of the overall MENA population in the United States (41). Nevertheless, we were able to identify 50 individuals in the Prolific MENA sample with at least one North African grandparent (SI Appendix, Table S1).

To address this limitation and validate our results, we collected an additional sample of MENA respondents via Lucid, a different online survey platform. Since Lucid did not have a preestablished way to identify MENA individuals from its pool of respondents, we developed a filter based on the place of birth of individuals’ grandparents. We identified 329 individuals who reported having at least one grandparent born in the MENA region; 121 of these individuals reported at least one grandparent born in North Africa. This provides an alternative way to capture MENA identity based on ideas about ancestry, which have been shown to shape identification and ethnic belonging (42, 43). The two MENA samples therefore reflect different but complementary strategies for selecting respondents. We note that while our Lucid sample slightly overrepresents respondents with North African ancestry, relative to country of origin estimates from the US Census/American Community Survey, North African MENAs are underrepresented in our combined sample (41).

Each survey included a conjoint experiment that presented randomized profiles of individuals and asked respondents to ethnoracially classify each profile. Both surveys of MENA respondents also included a second experiment that tested whether offering a MENA response option changed patterns of ethnoracial self-identification. The order of the two experiments within each survey was randomized and background demographic measures were collected between each experiment to reduce any possible carryover effects (Fig. 1).

Fig. 1.

Fig. 1.

Example of fictitious “immigrant” profile viewed by respondents in the external classification experiment.

First, to understand external classification of MENA individuals by both White and MENA respondents, we used a conjoint, or multidimensional choice, experimental design to simultaneously compare the effects of multiple ethnoracial signals on classification (4446). Respondents viewed and classified 10 profiles each. Respondents were randomly assigned to either view profiles of immigrants or native-born individuals to control for nativity effects. As is typical in conjoint experiments, all treatments were fully randomized for each profile. While this randomization scheme may lead to some combinations of signals that are more likely to be observed outside of the experimental context than others, all are theoretically possible. Our design is based on previous research that uses a conjoint experiment to examine external classification inclusive of the proposed MENA category (47). See SI Appendix, Text and Questions for External Classification Experiment for more detailed explanation of the conjoint experiment. The total number of observations for each sample ranges from 3,240 to 4,210.

The key dependent variable was respondents’ decisions to classify each hypothetical profile as either MENA, White, or Black. Our profiles of fictitious individuals varied along dimensions chosen to reflect ethnoracial perceptions between White, Black, and MENA categories in the United States, as well as the three largest estimated MENA American subgroupings: Middle Eastern, North African, and non-Arab Iranian (41). We varied given name, religion, language, class (indexed by occupational status), skin color, and family ancestry, employing country-level labels that represent specific regions around the world.

Second, to assess how MENA American individuals identify themselves, we replicated an experiment applied by the US Census in 2015 to examine how MENA individuals self-identify when given a MENA option. We replicated this experiment because the Census data were not available for reanalysis and because this allowed us to look at heterogeneous treatment effects within our sample. We inserted this second experiment in our two surveys of MENA respondents collected via Prolific and Lucid.

The dependent variable was ethnoracial self-identification. Respondents in the control condition were asked: “What is your race or origin?” (9). The response options were: White; Hispanic, Latino, or Spanish origin; Black or African American; Asian; American Indian or Alaska Native; Native Hawaiian or other Pacific Islander; and some other race or origin. Crucially, the control did not include a MENA category but rather, reproduced the White response category provided by the Census, which listed two MENA nationalities, Lebanese and Egyptian, as examples of White subgroups alongside German, Irish, English, and Italian. In turn, respondents in the experimental condition were asked “Which categories describe you?” (9). Critically, a new identity category was added as a response option: Middle Eastern or North African. Nationalities like Lebanese and Egyptian were also no longer listed as examples of White subgroups. They were listed instead as examples of Middle Eastern or North African subgroups. All other category labels were the same as in the control condition. Individuals were randomly assigned to either the control or the experimental condition. Therefore, our survey experiment assesses the effect of being offered a MENA option on respondents’ identification choices. In both treatment and control conditions, respondents were able to check more than one box. Although phrasing of the two questions is different, the Census reported no effect on individuals’ responses (9). We retained the phrasing to ensure replication of the Census experiment. See SI Appendix, Table S9 for a randomization check.

Results

Treatment Effects Based on the External Classification Conjoint Experiment.

Results from the external classification conjoint experiment demonstrate that both non-MENA Whites and MENAs clearly recognize particular ethnoracial characteristics as MENA (Fig. 2) and not White (Fig. 3) or Black (Fig. 4). Fig. 2 plots the average marginal component effects for all attributes predicting external classification as MENA (see also SI Appendix, Table S2). Results are largely consistent among non-MENA Whites and MENAs.

Fig. 2.

Fig. 2.

Average marginal effects predicting classification as MENA among MENA and non-Hispanic White respondents. Results are based on SI Appendix, Table S2.

Fig. 3.

Fig. 3.

Average marginal effects predicting classification as White among MENA and non-Hispanic White respondents. Results are based on SI Appendix, Table S2.

Fig. 4.

Fig. 4.

Average marginal effects predicting classification as Black among MENA and non-Hispanic White respondents. Results are based on SI Appendix, Table S2.

First, among both groups of respondents, we found the largest effects with fully MENA ancestries compared to a fully European ancestry. MENA individuals react even more strongly to the ancestry treatments compared to Whites; for example, compared to a fully European ancestry, a fully Arab ancestry (signaled via having only Lebanese and Syrian ancestors) increases the probability that MENA respondents will classify a profile as MENA by 51 percentage points, while it increases the probability that White respondents will classify a profile as MENA by 36 percentage points. (See SI Appendix, Fig. S8 for formal comparison of ancestry treatment effects across survey samples.)

Second, MENA and White respondents similarly react to certain cultural traits as a signal of MENA classification. Common MENA names and languages increase classification as MENA by 5 to 20 percentage points among both groups of respondents (see SI Appendix, Table S2 for detailed point estimates). We found relatively large effects for language; relative to speaking English, speaking Amharic, Arabic, or Persian increases the probability that a profile is classified as MENA by both respondent groups by 11 to 20 percentage points. Interestingly, neither MENA nor White respondents associate certain occupations with MENA classification. However, relative to profiles marked as Protestant, those described as Atheist/Agnostic, Hindu, Jewish, and Muslim are more likely to be classified as MENA by both MENA and White respondents; the largest religion effects are observed for Muslim, which increases MENA classification by 8 to 11 percentage points. In sum, MENA-related religion, language, and names have a negative effect on White classification, but overall, the effect size for cultural cues is smaller than ancestry cues.

Third, MENA and White respondents substantively differ on how skin color relates to MENA classification. MENA respondents are more likely to classify individuals with light and medium skin tones as MENA over individuals with dark skin tones. In contrast, White respondents associate medium skin tones with MENA classification, but not light skin tones or dark skin tones. Overall, MENA individuals understand MENA as a category that crosscuts a wider array of skin colors, whereas for White respondents MENA exists within a narrower band. See SI Appendix, Fig. S9 for a formal comparison of skin color treatment effects by survey sample.

We also examined the extent to which traits associated with the MENA category in the United States are used by MENA and White respondents to mark individuals as not White or Black. As shown in Figs. 3 and 4, MENA and White respondents similarly use MENA traits to exclude individuals from the White and Black categories. For example, fully Arab, North African, and Iranian ancestries reduce the probability that a profile will be classified as White or Black (SI Appendix, Table S3). Common MENA names and languages and identifying as Muslim also reduce White and Black classification among both groups of respondents. The negative effect of identification as Muslim on Black categorization is particularly notable, given that one in five American Muslims are Black, highlighting the racialization of Islam as not White or Black (4851). White and MENA respondents also recognize that medium and dark skin tones mark someone as not White and as Black, though in general White respondents appear to react more strongly to skin color relative to MENA respondents. See SI Appendix, Fig. S10 for a formal comparison of skin color treatment effects on White and Black classification by survey sample.

In SI Appendix we analyze the conjoint experiment results with our second MENA sample of respondents collected from Lucid and find small variations in magnitude but substantively similar treatment effects for MENA, White, and Black classification (SI Appendix, Figs. S1–S3 and Tables S2 and S3). This successful replication of our findings among MENA respondents suggests that the ethnoracial classification norms we uncovered are not driven by the specific sample selection criteria we used but may be widespread in the United States.

Our results from the external classification experiment show that many non-MENA White and MENA respondents consider MENA cultural and ancestry traits to be non-White ethnoracial markers. Nevertheless, it is still not clear whether MENA respondents would prefer to identify as White-only or in a new MENA category if given the option, which we examined in our second experiment on self-identification.

Treatment Effects for Self-Identification.

Results from the self-identification factorial experiment demonstrate that offering a MENA category significantly decreases the rate of MENA individuals who identify as exclusively White. Fig. 5 shows the percentage of respondents who identified in each category in both the control and the treatment conditions in the Prolific sample (n = 330), which underrepresents North African respondents. It shows that 80% of MENA respondents who were not given a MENA identity option (control group) identified as White and 6% identified as Asian. In addition, 15% of respondents checked “some other race” (SOR).

Fig. 5.

Fig. 5.

MENA respondent self-identification across experimental conditions, Prolific sample. Respondents in the control condition were not offered a MENA response category. Respondents in both treatment and control conditions were instructed to check all categories that apply. See SI Appendix, Table S4 for results of a Pearson χ2 test of the association between self-identification and treatment assignment.

In contrast, 88% of individuals in the treatment condition identified as MENA when we included both those who identified as only MENA and those who identified as MENA and an additional category. The majority of individuals in the treatment condition, 59%, identified as only MENA. The second most common identification was MENA and White, at 27%. Only 11% identified as exclusively White when offered a specific MENA category. These results show that, when given the option, most MENA respondents self-identify as MENA. As shown in SI Appendix, Table S4, a Pearson χ2 test indicates that the distribution of self-identification is significantly different in the treatment condition—when the MENA identification category was offered—compared to the control condition.

We similarly found that offering a MENA identification category significantly reduced self-identification as exclusively White in our Lucid sample of respondents with MENA ancestry (SI Appendix, Fig. S9). However, overall, we found more heterogeneity in identification patterns in both the control and treatment conditions in the Lucid sample compared to the Prolific sample (SI Appendix, Fig. S12 and Tables S4 and S5).

To better understand which MENA individuals are more likely to identify as MENA alone or in combination compared to White alone, we next tested for heterogeneous treatment effects among our MENA respondents. Because our Prolific and Lucid samples were both relatively small, for these analyses we combined the two survey samples to increase statistical power. We tested for heterogeneity along four key dimensions known to vary within the United States MENA population: ancestry (comparing individuals with one or more Middle Eastern grandparents to those with one or more North African grandparents), religion (comparing Christian, Muslim, nonreligious, and other religiously identified individuals), immigrant generation (comparing first-generation individuals to second-generation children of immigrants, and third-plus generations), and perceived levels of anti-MENA discrimination (comparing those who perceive a lot of discrimination to those who perceive less) (52, 53). (See SI Appendix, Table S1 for the distributions of each variable across each survey sample.)

Overall, we found that offering a specific MENA identity category significantly decreases identification as exclusively White among each subgroup, underscoring overall widespread preferences by individuals with MENA ancestry to not identify with just the White category. Effect sizes for each subgroup range from 47 to 65 percentage point decreases in identifying as White-only (SI Appendix, Figs. S3–S18). However, our results also point to some heterogeneity in identification patterns among MENA individuals.

First, with respect to ancestry, we found that MENA individuals reject identifying as exclusively White at similar rates (SI Appendix, Figs. S13 and S14). This suggests that the MENA grouping, which combines Middle Eastern and North African, is legible to both groups as a distinct category. However, we did observe some variation in identification trends across these two subgroups for other ethnoracial categories. We found that 12% of North African ancestry individuals identify as exclusively Black even when offered a separate MENA category, compared to just 1% of Middle Eastern individuals (SI Appendix, Figs. S10 and S11 and Table S6). This finding aligns with expectations that some individuals will continue to identify as Black, as the inclusive definition of MENA we drew upon in this study intentionally brings together persons typically aggregated in Black (e.g., Somali, Sudanese) as well as White (e.g., Iranian, Syrian) Census categories. It may also be the case that some individuals from countries like Morocco or Egypt will consistently identify as Black regardless of labels offered, based on how their phenotypes are perceived in the United States.

Second, we found that respondents who identify as Muslim, along with those identifying as nonreligious, reject Whiteness in favor of the MENA category at higher rates than those who identify as Christian (SI Appendix, Table S10). When offered a MENA option, just 6% of Muslim MENAs choose the White-only category versus 25% of Christian MENAs. However, Christian MENAs are also more likely to choose MENA or MENA and White (61%) over White-only when offered a MENA option (SI Appendix, Figs. S23–S27). Respondents identifying with other religions (beyond Islam or Christianity) appear to display similar patterns to Christian respondents, though the confidence intervals for this heterogenous group are much wider. Altogether, our findings suggest that Christian and White identities remain linked among MENA Americans. But because a much higher share of post-1965 MENA arrivals are Muslim than previous waves of MENA migration, our findings on religion also suggest that MENA Americans may increasingly prefer the MENA category over White in the future (41).

Next, we interacted treatment assignment with immigrant generation and found that second-generation individuals—the children of immigrants—are significantly more likely to reject identifying as exclusively White compared to both the first generation (foreign-born immigrants) and the third-plus generation (SI Appendix, Fig. S21). In addition, the third-plus generation (one or both parents born in the United States) is less likely to identify as only MENA (at just 18%, compared to 76% of second-generation individuals and 60% of first-generation respondents), and more likely to identify as MENA and White (32%, compared to 11% of second generation and 16% of first generation) and only White (25%, compared to 5% of second generation and 13% of first generation) (SI Appendix, Figs. S15–S17 and Table S7).

These generational patterns are likely driven by differing norms and practices of ethnoracial identification across immigrant generations, as well as higher odds of third-plus generation individuals having mixed ancestries (35, 54). Due to their likely mixed-heritage as well as deeper cultural assimilation, third-plus generation individuals may be less affected than more recent MENA arrivals by the post-9/11 increase in public animosity against persons from the Middle East and North Africa. This also includes former President Trump’s harsh rhetoric portraying MENA individuals as security threats. Such politically charged developments may have especially pushed second-generation MENA individuals into “reactive” or “affiliative” identification with a non-White category, a phenomenon that has also been observed among the children of immigrants from Asia and Latin America (55, 56).

Finally, if reactive ethnicity is propelling MENA identification, we should expect that MENA identification is stronger among those who perceive more hostility against MENAs. To test this hypothesis, we examined two different survey questions: whether individuals perceive discrimination against MENAs and (given common associations of this ethnic label with Muslim religion) whether they believe Muslims are discriminated against in the United States. These items do not necessarily capture individual-level discrimination experiences. Rather, they aim to capture perceptions of discrimination at the group level, which may better reflect the ambiguous social status of MENAs in the United States (57). In line with this hypothesis, SI Appendix, Figs. S18 and S19 show that those who perceive significant discrimination are over nine times less likely to choose “White-only” if offered a MENA option; those who perceive less discrimination are merely three times less likely to choose White-only. This evidence mirrors prior research linking perceptions of discrimination with stronger ethnic identities among Latinos and Asians (58, 59). Previous research with South Asian Muslims in the United States has also shown that even “anticipated” discrimination predicts weakened “American” identification and more positive attitudes toward Islam (60). Moreover, in contexts where the MENA category is not offered, those who perceive “a lot” of discrimination against MENA and Muslim Americans choose SOR over “White” at significantly higher rates than their counterparts who perceive less discrimination (SI Appendix, Figs. S18 and S19). Replicating this analysis using our measure of perceived anti-Muslim discrimination yields largely similar results. (SI Appendix, Fig. S28). Together, these patterns suggest that respondents who seek out the MENA category do so as a broader reflection of their perception that this group is minoritized in United States society.

Nevertheless, because we rely on relatively small, convenience samples, we consider these analyses to offer preliminary, suggestive evidence of heterogeneity in the identification preferences of MENA Americans. Further research with larger, nationally representative samples of MENA ancestry individuals are needed to confirm our findings.

Conclusion and Discussion

We conducted two online survey experiments to investigate how non-MENA White and MENA individuals perceive the racial status of MENA traits (external categorization) and how MENA individuals identify themselves (self-identification). With respect to the external categorization experiment, we found that both non-MENA Whites and MENAs classify MENA-related traits, including ancestry, names, and religion as non-White ethnoracial markers. We found that MENA ancestry strongly cues MENA classification, and significantly reduces White and Black classification. While a person’s ancestry may not be as readily apparent to others as skin tone or name, ancestry has historically been the bedrock of racial membership in the United States. By uncovering how ideas of ancestry relate to the MENA category, our experiment illuminates the cognitive underpinnings of this category and helps uncover the racial norms that prevail in United States society today. The primacy of ancestry for MENA classification may in fact mean that—even among MENAs who are “White passing,” or have been in the United States for generations—evidence of lineage to the MENA region may lead to reclassification as non-White for some. We also found that MENA names are perceived as distinctly MENA and not White. This is consequential because names are a primary basis for differentiation and discrimination in settings where this information is especially prominent, as in labor and housing markets (19). Furthermore, we found that non-Christian religions like Judaism, Hinduism, and especially Islam are perceived as “MENA,” which could increase inequality, as research has shown significant “Muslim penalties” in Western labor markets (61, 62).

The perceived relationship between MENA individuals and skin color is complex. Whites associated a medium skin tone with MENA categorization. MENA respondents, on the other hand, viewed both light and medium skin colors as more typical MENA traits. These different understandings of who represents MENAs suggest that significant portions of the MENA population may not be read as such by others, which could have significant consequences for street-level discrimination. At the same time, the fact that Whites associate MENAs with a darker skin color underscores the fact that they seem to understand MENAs as a group with a non-White phenotype.

Overall, our findings on external classification highlight how ancestry, color, and culture inform an emerging White–MENA boundary. Given pervasive public perceptions of a “majority–minority” future in the United States (35), research has shown that the threat of demographic decline can push Whites to tighten the White category and exclude “ambiguous” Whites and Latinos (63). We expanded this inquiry to show that when categorizing others today, White and MENA people will also distinguish and exclude MENA, an ambiguously White population, from the White category.

With respect to self-identification, we show that when MENA are not offered a MENA label, 80% choose to identify as White. However, when MENA is offered as a category, only 10% continue to exclusively choose White. The majority instead choose MENA, and this appears to be an especially salient single category of choice for second-generation immigrants, MENA Muslims and nonreligious MENAs, those with Middle Eastern (versus North African) ancestry, and those who perceive more discrimination against MENA people. We speculate that the MENA category may therefore represent for some a reactive ethnoracial identity, triggered acutely since the events of September 11, 2001, which led to an increase in state surveillance and public stigmatization of this group. President Donald Trump’s anti-immigrant and anti-Muslim rhetoric and policies—exemplified by the Muslim Ban, which curtailed immigration from a list of mostly MENA countries—and the significant backlash to such divisive politics may have hastened MENA peoples’ exit from the White box. This seems to contradict expectations that MENA Americans, like conditionally White immigrant generations before them, would seek cover under the White category. Past research has examined how individuals develop identities through interactions with others. European Americans claim ethnic identities that are “symbolic, voluntary, and intermittent”; in contrast, Black Americans’ encounters with racial discrimination trigger reactive and oppositional identities (64). Future research should adjudicate whether MENA Americans’ ultimate path is more ethnic or racial in character.

At the same time, we found that a sizable minority of individuals with MENA ancestry identify as both White and MENA. This may be linked to a growing number of individuals of mixed MENA–White parentage, especially by the third generation. In addition, some members of the MENA population may understand White and MENA as identities that are cooccurring or nonexclusive with one another. The considerable number of respondents who self-identify as both MENA and White may also reflect how, according to the 2020 Census, more Americans than ever are identifying as multiracial. These heterogeneous findings suggest that the relationship between Whiteness and MENAness is complex and far from settled, which future research should examine.

Importantly, offering MENA as a box reduced the percentage of respondents who chose the single category SOR from 15 to 0. The proportion of the United States population identifying as SOR has grown substantially over time, reaching 49.9 million people in the 2020 Census (65). Our study suggests that adding a MENA category would lead many MENA individuals to reclassify themselves out of SOR to MENA, which would improve the useability of Census data for both administrative and research purposes.

By examining the unsettled MENA ethnoracial category from outside and inside the community, both experiments suggest that MENA Americans’ official designation as White-only by the federal government is not consistent with how many MENA and non-MENA Whites perceive this population. Our findings empirically support the call from activists to “Check it Right, You Ain’t White,” and establish a separate MENA identity category in the US Census. Adding a new Census label would allow researchers and community leaders to better understand the experiences of MENA Americans along key dimensions, including economic well-being, health status, residential segregation, and political representation, among others. At the same time, real privacy concerns exist within MENA communities about the federal government gathering more detailed data on this population, particularly considering explicit policies prohibiting MENA immigration, refugee resettlement, and travel.

We cannot make definitive claims from our study due to challenges related to sampling this unique community. It is difficult to investigate population-level trends among MENA Americans precisely because the US Census datasets do not explicitly identify MENA people. For this reason, our study uses nonprobability convenience samples, which may not fully capture the significant heterogeneity of the MENA American population. Nonetheless, we hope this study substantiates the call for continued testing on the viability of a MENA category for our federal data collection systems. In addition, future research should investigate how individuals of partial MENA ancestry identify racially. There is evidence that individuals of mixed parentage encounter less resistance from the mainstream (32).

Beyond the MENA case, we hope that this work supports ongoing research and advocacy around inequalities faced by communities that are rendered invisible through current means of data collection and categorization. Grassroots ideas about racial categories, even when not officially sanctioned by the state, are a powerful force in the social construction of race (32). For this reason, we place attention on how everyday people—not bureaucrats, experts, or power brokers—understand ethnoracial group boundaries. Although membership in a bigger demographic box may confer greater political power for some, it may also obscure or foster inequality for others. Thus, we believe that a partial but powerful way to overcome the erasure of meaningful heterogeneity within groups is through the harmonization of administrative categories, policies, and practices with everyday people’s understandings of belonging and difference.

Supplementary Material

Supplementary File

Acknowledgments

We thank Clayton Childress, S. Michael Gaddis, John S. Kuk, and Hajar Yazdiha for their valuable comments and Rachel Marks for her time and expertise. All errors are uniquely ours.

Footnotes

The authors declare no competing interest.

This article is a PNAS Direct Submission.

This article contains supporting information online at https://www.pnas.org/lookup/suppl/doi:10.1073/pnas.2117940119/-/DCSupplemental.

Data Availability

A replication package containing all data and code used in this analysis is available through the Harvard Dataverse (https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/BTFTQE).

Change History

May 6, 2022: The article text has been updated.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary File

Data Availability Statement

A replication package containing all data and code used in this analysis is available through the Harvard Dataverse (https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/BTFTQE).


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