Psychological Outcomes Differ for Real Vs. Computer-Generated Multiracial Faces

The Journal of Social Psychology

ISSN: 0022-4545 (Print) 1940-1183 (Online) Journal homepage: http://www.tandfonline.com/loi/vsoc20

At face value: Psychological outcomes differ for real vs. computer-generated multiracial faces

Sarah E Gaither, Jacqueline M Chen, Kristin Pauker & Samuel R Sommers

To cite this article: Sarah E Gaither, Jacqueline M Chen, Kristin Pauker & Samuel R Sommers (2018): At face value: Psychological outcomes differ for real vs. computer-generated multiracial faces, The Journal of Social Psychology, DOI: 10.1080/00224545.2018.1538929 To link to this article: https://doi.org/10.1080/00224545.2018.1538929

Published online: 30 Oct 2018.

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Full Terms & Conditions of access and use can be found at http://www.tandfonline.com/action/journalInformation?journalCode=vsoc20 THE JOURNAL OF SOCIAL PSYCHOLOGY https://doi.org/10.1080/00224545.2018.1538929

At face value: Psychological outcomes differ for real vs. computer-generated multiracial faces Sarah E Gaithera, Jacqueline M Chenb,c, Kristin Paukerd, and Samuel R Sommerse aPsychology and Neuroscience, Duke University, Durham, USA; bPsychology Department, University of Utah, Salt Lake City, USA; cPsychology Department, University of California, Irvine, Honolulu, USA; dPsychology Department, University of Hawaii at Manoa, Honolulu, USA; ePsychology Department, Tufts University, Medford, USA

ABSTRACT ARTICLE HISTORY Multiracial research emphasizes hypodescent categorizations and relies on Received 24 August 2017 computer-generated stimuli. Four experiments showed that real biracial Accepted 3 October 2018 faces in a 2-Choice categorization task (White, Black) elicited hypodescent KEYWORDS more than computer-generated faces. Additionally, Experiment 2 showed a Computer-generated faces; 2-Choice categorization task with real biracial faces increased racial essenti- hypodescent; multiracial alism more than a 3-Choice categorization task. Experiment 3 showed that categorization; racial mere exposure to real biracial faces did not increase essentialism. Finally, essentialism; real biracial Experiments 4a and 4b replicated hypodescent outcomes when comparing faces real biracial faces to computer-generated versions of those same faces. In sum, these findings initiate a discussion surrounding the methodology of multiracial categorizations.

Since multiracial individuals are projected to be one of the fastest-growing populations in the United States across the next 40 years (Dunham & Olson, 2016; Kang & Bodenhausen, 2015;Richeson& Sommers, 2016;), it is important for research to understand the nuance surrounding how multiracial individuals are categorized by society. It is true that not all multiracial people are racially ambiguous in appearance. However, it is clear that this emerging multiracial demographic has inspired a growing body of social psychological research on ambiguous categorization processes (e.g., Carpinella, Chen, Hamilton, & Johnson, 2015; Chen & Hamilton, 2012; Chen, Moons, Gaither, Hamilton, & Sherman, 2014; Freeman, Pauker, & Sanchez, 2016; Gaither, 2015; Gaither, Pauker, Slepian, & Sommers, 2016; Halberstadt, Sherman, & Sherman, 2011; Ho, Kteily, & Chen, 2017; Ho, Sidanius, Levin, & Banaji, 2011; Ho, Sidanius, Cuddy, & Banaji, 2013; Krosch, Berntsen, Amodio, Jost, & Van Bavel, 2013;Peery& Bodenhausen, 2008). Moreover, other research has also focused on how exposure to this growing group influences social attitudes, since multiracial individuals directly contradict U.S. society’s more fixed notions about racial group membership (e.g., Gaither, Babbitt, & Sommers, 2018a; Gaither, Toosi, Babbitt, & Sommers, 2018b; Sanchez, Good, & Chavez, 2011; Sanchez, Young, & Pauker, 2015; Pauker, Meyers, Sanchez, Gaither, & Young, 2018; Young, Sanchez, & Wilton, 2013). However, the majority of multiracial categorization research to date has utilized computer- generated images of faces. Therefore, we do not know whether computer-generated depictions of multiracial individuals are ecologically valid in terms of reflecting how actual multiracial individuals are categorized. Here, we explicitly test the generalizability of these past findings by directly comparing the use of computer-generated and real multiracial faces. Social categorization research uses a variety of methods. Some studies utilize computer-generated faces and other studies use photographs of actual people. Some studies use forced-choice binary

CONTACT Sarah E Gaither [email protected] Duke University, Psychology and Neuroscience, 417 Chapel Drive, Box 90086, Durham, NC 27708-0086, USA Color versions of one or more of the figures in the article can be found online at www.tandfonline.com/vsoc. © 2018 Taylor & Francis 2 S. E. GAITHER ET AL. categorizations, and other studies provide more options. Although multiracial and racially ambiguous perception research has clearly used a variety of stimuli type and methods (e.g., Chen & Hamilton, 2012; Freeman, Pauker, Apfelbaum, & Ambady, 2010; Krosch et al., 2013; Pauker et al., 2009; Peery & Bodenhausen, 2008), much of this work has solely relied on computer-generated or computer-morphed stimuli. Both computer-generated and computer-morphed stimuli (faces made by morphing two photos of monoracial individuals together) attempt to represent multiracial stimuli as a 50:50 blend of the racial backgrounds of interest. Yet real multiracial individuals may not always have features that reflect these 50:50 blends, and no work has systematically compared these different types of stimuli in a single study. We argue that computer-generated faces may be qualitatively different than actual biracial faces, since real biracial people are not perfectly controlled blends of their parents’ faces and also are simply more realistic. Based on the Social Relevance Hypothesis, we argue that real biracial faces may be processed differently than computer-generated faces, because the former are more realistic and should be viewed as more socially relevant and more meaningful to the perceiver. Some work shows that higher levels of social relevance cause that stimuli to be processed in a more purposeful and socially meaningful manner (e.g., Bastian, Loughnan, & Koval, 2011; Mullen, Brown, & Smith, 1992; Oberman, Ramachandran, & Pineda, 2008) due to the realistic qualities of the stimuli that create a personal connection (see also Bailenson, Yee, Merget, & Schroeder, 2006; Schroeder, 2002). Hypodescent is one prevalent heuristic that some perceivers use during racially ambiguous categorization, whereby ambiguously raced individuals are labeled more often as members of their minority or socially subordinate group based on their physical appearance (Halberstadt et al., 2011; Ho et al., 2013, 2011; Krosch et al., 2013; Peery & Bodenhausen, 2008; Sanchez et al., 2011). Historically known as the one-drop rule, whereby one drop of “Black blood” identified a mixed- race individual as Black, hypodescent is consistent with either/or categorical approaches to race (e.g., Allport, 1954; Bodenhausen & Macrae, 1998). Strictly speaking, hypodescent involves assigning individuals to their socially subordinate group when you know their ancestry (Jordan, 2014), but individuals could still categorize someone in a manner consistent with hypodescent by assuming a targets’ ancestry based on their outward appearance and then categorizing them according to their socially subordinate group. For clarity, we call this specific process of categorizing where only visual information is utilized—visual hypodescent. Social categorization research documenting visual hypodescent has relied primarily on computer-generated or computer-morphed faces (e.g., Halberstadt et al., 2011; Ho et al., 2011; Krosch & Amodio, 2014; Krosch et al., 2013; Hugenberg & Bodenhausen, 2004; Peery & Bodenhausen, 2008). Therefore, we predicted that real racially ambiguous biracial faces should also heighten social motivations and elicit higher levels of visual hypodescent compared to computer-generated faces. To our knowledge, only one set of studies has directly compared categorizations of computer- generated and real biracial faces. Chen and Hamilton (2012; Experiment 2) found that hypodescent categorizations were more readily elicited by real Black/White biracial faces than by morphed biracial faces (created by morphing Black and White monoracial faces together). However, these researchers did not test whether they elicited different levels of visual hypodescent in a racially dichotomous categorization task (i.e., one that only asks participants to categorize the faces as Black or White), which is most often used in research. Moreover, these authors did not provide an explanation for the differences in hypodescent rates by stimulus type. Here, we aimed to answer two main questions: (1) is visual hypodescent applied differently to experimenter controlled, computer-generated racially ambiguous biracial stimuli compared to actual racially ambiguous biracial individuals?; and (2) does visual hypodescent vary based on what racial categories are explicitly cognitively accessible to the perceiver?

Experiment 1: 2- vs. 3-choice categorization outcomes Experiment 1 tested whether real racially ambiguous biracial faces are categorized differently than computer-generated racially ambiguous biracial faces by comparing a 2-Choice versus a 3-Choice THE JOURNAL OF SOCIAL PSYCHOLOGY 3 categorization task. We hypothesized that a 2-Choice categorization task, which asks participants to dichotomously categorize racially ambiguous faces into discrete monoracial categories would lead to higher levels of visual hypodescent (categorizing more faces as Black) for real biracial faces over computer-generated biracial faces because real biracial faces are likely to be seen as more socially relevant (Bastian et al., 2011; Oberman et al., 2008).

Stimuli pretest FaceGen is a frequently used program in face categorization studies that allows researchers to control various aspects of faces when creating stimuli (i.e., skin color, facial features, affect). For example, to create a racially ambiguous face, the setting for a face would be at the midpoint between the two desired racial categories (i.e., White and Black). To compare categorization outcomes between real biracial faces and FaceGen computer-generated faces, we first conducted a pretest to ensure that the stimuli sets were equivalent in racial ambiguity and related characteristics. Twenty FaceGen computer-generated racially ambiguous Black/White faces (10 female) with neutral expressions were used in this study (see Pauker et al., 2009; Gaither et al., 2014; Hinzman & Kelly, 2013; for other uses). All images were in color, cropped to an oval shape to display only the face (ears were partially visible, but no hair was visible) and were adjusted to uniform size and resolution (275 × 360 pixels; 3.8 × 5.0 inches; see Appendix A). Thirty biracial Black/White individuals (15 female) were photographed in the lab on a white back- ground while making a neutral facial expression as part of a previous study. Twenty of these photos were selected (13 female) based on perceived ambiguity. These images were in color and were cropped to the same oval shape. All of these images were adjusted to uniform size and resolution (184 × 248 pixels; 3.8 × 5.0 inches; see Appendix A). ’ Fifty participants (27 female; Mage = 24.46, SD = 11.06) were recruited using Amazon s Mechanical Turk using the keywords “short face perception study” and received 50 cents for their work (Buhrmester, Kwang, & Gosling, 2011). The sample included 33 White, 3 Asian, 1 Latino, 1 Black, 2 Native American, 2 biracial, and 8 racially unspecified individuals. Participants first read the following prompt: “You will see a series of pictures of different people. Some of these individuals have features that are more typical of African Americans, and some have features that are more typical of Caucasian Americans in terms of skin color, hair, eyes, nose, cheeks, lips, etc. Please rate the following photos to the best of your ability using your gut or instinctual responses.” Participants then were randomly assigned to rate 20 out of the 40 faces (a mix of the computer-generated and real biracial faces) on a scale ranging from 1 (not at all)to7(very much) for each of the following dimensions: prototypical White appearance, prototypical Black appearance, prototypical White features, prototypical Black features, neutrality of facial expression, and attractiveness. Results showed that the two sets of stimuli did not significantly differ on any of the ratings (all Fs < 2.91, all ps > .10; p = .10 was for attractiveness with computer-generated faces being rated as slightly higher). Additionally, there were no differences based on target gender (all Fs < 2.18, all ps > .15). While real biracial faces will vary considerably in the prototypicality and distinctiveness of their features in reality, the current set of faces were specifically selected to match the racial ambiguity of the computer-generated set to systematically test how computer-generated versus actual racial ambiguity may influence race categorization.

Method Participants Experiment 1 was our initial investigation of this research question. One hundred and thirty-three undergraduates (81 females; 4 gender unspecified; Mage = 19.29, SD = 1.21) participated in exchange for partial course credit. This data was collected in 2012, and we followed the norm (at the time) of 4 S. E. GAITHER ET AL. collecting 30 participants per between-subjects condition. Based on recruitment limitations using the department participant pool, our goal was to recruit approximately 25–35 participants in each of four conditions during a one-semester recruitment period. The sample included 89 Whites, 10 Asians, 4 Latinos, 2 Blacks, 23 biracials, and 5 racially unspecified.

Procedure The categorization task was programmed using javascript in Qualtrics to allow each screen to automatically advance to the next face after a participant entered a response. Participants first read: “You will complete a short-face categorization task. Your job is to sort these faces into categories by pressing the numeric key ON THE KEYBOARD (e.g., “1”, “2”,or“3”) corresponding to the appropriate category displayed on the screen as quickly as possible. The page will automatically advance after you type one of the numbers.” Participants were then randomly assigned to view either the 20 pre-tested computer-generated faces or the 20 pre-tested real biracial faces in a randomized order. They were also randomly assigned to use either a 2-Choice or a 3-Choice categorization task. Therefore, the design was a 2 (stimuli type: computer-generated, real biracial faces) × 2 (categorization task: 2-Choice, 3-Choice) between-subjects design. The response options in the 2-Choice task were Black (1 key) or White (2 key), and the response options in the 3-Choice task were Black (1 key), Biracial (2 key), and White (3 key).

Results Hypodescent Relative rates We computed each participant’s hypodescent tendencies by subtracting the proportion of White categorizations from the proportion of Black categorizations. We hypothesized that participants would engage in visual hypodescent significantly more when categorizing real biracial faces in the 2-Choice task than when categorizing computer-generated faces and/or in the 3-Choice task. We conducted a 2(Categorization Task) × 2(Stimuli Type) between-subjects ANOVA on hypodescent. η 2 There was a main effect of categorization task, F(1, 129) = 4.14, p = .04, p = .03, indicating that hypodescent occurred more frequently in the 2-Choice task (M = 0.06, SD = .39) than in the 3-Choice task (M = −0.06, SD = .28). There was also a main effect of stimuli type, F η 2 (1, 129) = 4.80, p = .03, p = .04. Hypodescent was applied more to real biracial faces (M = 0.07, SD = .30) than to computer-generated faces (M = −0.06, SD = .37). The interaction was not η 2 significant, p = .31, p = .01. However, we conducted follow-up pairwise comparisons given our a priori hypotheses that hypodescent would be most prevalent with biracial faces in the 2-Choice task. In the 2-Choice task, hypodescent was applied to real biracial faces (M = .15, SD = .31) more than to − η 2 computer-generated faces (M = .03, SD = .44), p = .02, p = .04. There was no difference by η 2 stimulus type in the 3-choice task, p = .41, p = .01. In addition, real faces elicited more hypodescent − η 2 in the 2-Choice condition than in the 3-Choice condition (M = .02, SD = .27), p = .03, p = .04, whereas categorization task did not affect hypodescent levels for computer-generated faces, p = .48, η 2 1 p = .004 (see Figure 1).

Absolute rates We then sought to determine whether evidence for hypodescent (significantly more Black categorizations than White categorizations) was obtained in each of the four conditions. A hypodescent score that was positive and significantly different from zero provides evidence for hypodescent (i.e., that participants are making consistently more Black than White categorizations, and their categorizations are different from chance). A series of one sample t-tests showed that participants engaged in hypodescent in the 2-Choice/Real Face condition (M = .15, SD = 0.31), t(34) = 2.93, p = .01, THE JOURNAL OF SOCIAL PSYCHOLOGY 5

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0.1 2 choice task 3 choice task Hypodescent 0

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-0.2 Facegen Real Type of Biracial Face

Figure 1. Hypodescent tendencies (Black categorizations – White categorizations) by type of biracial face and categorization task in Experiment 1. Error bars represent standard error.

Cohen’s d = 1.00, but not in the 2-Choice/Computer-generated condition (M = −.03, SD = 0.44), p = .67, or the 3-Choice/Real Face condition (M = −.02, SD = 0.27), p = .61. Participants in the 3-Choice/Computer-generated condition (M = −.09, SD = 0.29) actually exhibited a marginal tendency for hyperdescent (more White categorizations than Black categorizations), t(31) = −1.77, p = .09, Cohen’s d = .64.

Discussion These results provide initial evidence that hypodescent is applied more readily when categorizing real biracial faces compared to computer-generated faces, especially when perceivers’ categorizations are constrained to two choices. This finding suggests that experiments using computer-generated faces may actually underestimate the prevalence of hypodescent for real biracial individuals. However, Experiment 1 also demonstrated that perceivers categorizing faces in the 3-Choice condition did not engage in hypodescent regardless of face type, demonstrating that the addition of a biracial category reduced hypodescent for both types of faces. This finding clarifies the role of categorization task in contributing to the discrepant findings in the literature in which the same faces sometimes compel hypodescent (Peery & Bodenhausen, 2008) and sometimes do not (Chen & Hamilton, 2012; Chen et al., 2014). In sum, Experiment 1 provided preliminary evidence that perceivers respond to racially ambiguous faces differently depending on whether they are real or computer-generated and how they are asked to categorize them. Experiment 2 sought to replicate and extend these findings by examining perceivers’ beliefs about race.

Experiment 2: 2- vs. 3-choice task, categorization outcomes and essentialism Some work regarding the perceptions of racially ambiguous individuals has focused on whether increased exposure to biracial individuals will change perceivers’ beliefs about race, specifically their endorsement of racial essentialism (Sanchez et al., 2015; Young et al., 2013). Racial essentialism is a rigid (as opposed to malleable) view of race, in which racial groups are perceived as naturally occurring discrete categories (e.g., Leyens et al., 2001; Rothbart & Taylor, 1992). Biracial people represent the blurring of racial boundaries, which directly conflicts with the idea that racial categories must be 6 S. E. GAITHER ET AL. discrete. Indeed, exposure to biracial individuals, especially those who identify as multiracial, has been shown to decrease essentialism and colorblindness attitudes (Gaither, Babbitt, et al. 2018a; Gaither et al., 2018b; Sanchez et al., 2015; Young et al., 2013). This relationship between essentialist beliefs and hypodescent appears to be bidirectional. Adults who are high in racial essentialism believe that the boundaries between racial groups are in fact discrete (Chen & Hamilton, 2012; Haslam, Rothschild, & Ernst, 2000; Plaks, Malahy, Sedlins, & Shoda, 2012), and they tend to follow the rule of hypodescent when categorizing ambiguous others (Chao, Hong, & Chiu, 2013). Thus, essentialist beliefs influence hypodescent (e.g., Chao et al., 2013; Ho, Roberts, & Gelman, 2015). Additionally, being presented with information consistent with hypodescent increases essentialist beliefs (Gaither et al., 2018a; Young et al., 2013). For example, when perceivers are exposed to real racially ambiguous faces that are labeled as monoracial (e.g., Black) compared to multiracial, participants actually show an increase in essentialism since the monoracial label activates a more fixed, categorical view of race (Young et al., 2013). Therefore, this suggests that if someone is asked to categorize a face by using two monoracial categories (i.e., White, Black) versus three racial categories (one of which includes a “biracial” option), these two distinct categorization tasks may activate differing levels of fixed views about race. In other words, a 2-Choice task could lead to higher levels of essentialism, whereas a 3-Choice task could lead to lower levels of essentialism. Thus, we expected that asking participants to categorize real biracial faces into monoracial categories, thereby reinforcing traditional racial boundaries, would increase perceivers’ endorsement of essentialist beliefs, but not when the same task was completed with less socially meaningful, computer-generated faces. On the other hand, we predicted that a task that does not solely prime monoracial categories but also reminds perceivers of a multiracial category option will not show these same outcomes. Consequently, we predicted that essentialist thinking would only increase when perceivers engaged in the task that forced monoracial labels onto the more socially meaningful faces.

Method Participants

Two hundred and forty-one undergraduates (145 females; 3 gender unspecified; Mage = 19.00, SD = 1.14) participated in exchange for partial course credit. To ensure generalizability of our findings from Study 1 with a larger sample size, our goal was to recruit approximately 50–65 participants in each of four conditions during a one-semester recruitment period. The sample contained 171 Whites, 35 Asians, 9 Latinos, 8 Blacks, 13 biracials, and 5 unspecified.

Procedure The laboratory session procedure was identical to that of Experiment 1, except that we collected participants’ endorsement of essentialist beliefs after the categorization task. Using the essentialism scale from No et al. (2008), participants rated eight statements about essentialist beliefs (e.g., “To a large extent, a person’s race biologically determines his or her abilities or traits”; α = .63) using a scale of 1 = not at all to 7 = very much.

Results Hypodescent Relative rates The same analysis approach utilized in Experiment 1 was used here. We hypothesized that participants would engage in more hypodescent in the 2-Choice/Real Face condition compared to the other three conditions. We conducted a 2(Categorization Task) × 2(Stimuli Type) between-subjects ANOVA on hypodescent. There was a main effect of categorization task, F(1, 237) = 9.54, THE JOURNAL OF SOCIAL PSYCHOLOGY 7

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Hypodescent 0 Facegen Real

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Figure 2. Hypodescent tendencies (Black categorizations – White categorizations) by type of biracial face and categorization task in Experiment 2. Error bars represent standard error.

η 2 η 2 p = .002, p = .04, and a main effect of stimuli type, F(1, 237) = 16.82, p < .001, p = .07. These η 2 main effects were qualified by a significant interaction, F(1, 237) = 5.89, p = .02, p = .02. Follow-up pairwise comparisons revealed that real faces (M = .32, SD = .32) elicited more hypodescent than η 2 computer-generated faces (M = .05, SD = .42) in the 2-Choice condition, p < .001, p = .08, but there was no difference in hypodescent by stimuli type in the 3-Choice condition, p = .24. Furthermore, real faces elicited more hypodescent in the 2-Choice condition (M = .32, SD = .32) η 2 than in the 3-Choice condition (M = .09, SD = .21), p < .001, p = .06, whereas categorization task did not affect hypodescent levels for computer-generated faces. It is important to note that these patterns replicated the follow-up comparison results in Experiment 1 (even though the two-way interaction was not statistically significant in that experiment) (see Figure 2).

Absolute rates One-tailed tests revealed participants engaged in hypodescent in the 2-Choice/Real Face condition (M = .32, SD = 0.32), t(61) = 7.86, p < .001, Cohen’s d = 2.01, and in the 3-Choice/Real Face condition (M = .09, SD = 0.21), t(56) = 3.32, p < .001, Cohen’s d = 0.89. Participants did not engage in hypodescent when categorizing computer-generated faces into two categories (M = .05, SD = 0.42), t (60) = 0.99, p = .33, Cohen’s d = .26, or three categories (M = .03, SD = 0.28), t(60) = 0.71, p = .48, Cohen’s d = .18.

Psychological essentialism We hypothesized that categorizing the real biracial faces into two categories would lead to higher levels of endorsing racial essentialism relative to the other three conditions. First, we conducted a 2 (Categorization Task) × 2(Stimuli Type) between-subjects ANOVA on essentialism scores. There η 2 was a significant main effect of stimuli type, F(1, 229) = 5.21, p = .02, p = .02. Participants who categorized the real faces (M = 3.46, SD = .74) endorsed essentialism more strongly than those who categorized computer-generated faces (M = 3.24, SD = .76). The categorization task by stimulus-type η 2 interaction was not significant, F(1, 229) = 2.36, p = .13, p = .01. We conducted follow-up pairwise 8 S. E. GAITHER ET AL. comparisons given our a priori hypotheses. They revealed that participants who categorized real biracial faces using the 2-Choice task (M = 3.51, SD = .66) endorsed psychological essentialism more than those who categorized computer-generated faces in the 2-Choice task (M = 3.14, SD = .68), η 2 η 2 p = .01, p = .03. No other comparisons were significant, ps > .16, p s < .008.

Discussion In conjunction with Experiment 1, our findings indicate that stimulus type and categorization task affect how biracial faces are perceived and influence beliefs about race. Only when participants categorized real biracial faces did we find visual hypodescent, and those who categorized real faces into monoracial categories of Black or White exhibited the highest levels of essentialist beliefs. It is important to note that if we had only used computer-generated stimuli, we might not have concluded that categorizing ambiguous individuals as monoracial relative to multiracial increases essentialism. These findings are consistent with our assertion that real biracial faces are more socially relevant stimuli that elicit different psychological processes than computer-generated faces. Experiment 2 is also consistent with past work showing that essentialist thinking is associated with social categorization outcomes (e.g., Chao et al., 2013; Haslam et al., 2000; Rothbart & Taylor, 1992). Our findings suggest that in addition to essentialist thinking affecting social categorization outcomes, using traditional monoracial categories to categorize ambiguous stimuli appears to activate more fixed thinking about race. However, an alternative explanation for our results is that mere exposure to real racially ambiguous individuals increases essentialism and that the 2-Choice task merely reflects how people naturally categorize those faces, whereas the 3-Choice task primes people to think more about multiracialism and categorize more faces as multiracial than they would otherwise. To directly address this alternative explanation, we conducted Experiment 3 and measured perceivers’ essentialist beliefs after participants either categorized real biracial faces into monoracial categories or were simply exposed to the faces. Experiments 1 and 2 also both did not include reaction times during categorization—an outcome variable frequently utilized in face categorization research to reflect ease or difficulty in categorization. Therefore, Experiment 3 also measured categorization latencies during the 2-Choice categorization task.

Experiment 3: 2-choice vs. mere exposure task, categorization outcomes, and latencies, and essentialism Thus far, Experiments 1 and 2 have highlighted differences in outcomes for racially ambiguous faces, especially when perceivers used the 2-Choice task and saw real faces. Experiment 3 tested whether the essentialism findings were due to imposing monoracial categories on real biracial faces or due to mere exposure to these faces. Additionally, Experiment 3 provided another opportunity to replicate the hypodescent effects while also examining if participants spend differing amounts of time categorizing real versus computer-generated faces. Here, we manipulated whether perceivers saw real or computer-generated faces and whether they categorized those faces (into 2 categories) or viewed them without a categorization task. We predicted that, because real biracial faces are more socially relevant stimuli, both a 2-Choice categorization task and simply exposing participants to the same real biracial faces one-at-a-time (which still gives participants the opportunity to mentally categorize each face into pre-existing monoracial categories), would increase essentialist beliefs more than with computer-generated biracial faces. Moreover, since the 2-Choice categorization task primes categorical thinking, we hypothesized that this task would lead to higher levels of racial essentialist beliefs than mere exposure. Lastly, since past work has shown that racially ambiguous faces take longer to categorize than racially prototypical faces (e.g., Blascovich, Wyer, Swart, & Kibler, 1997; Castano, Yzerbyt, Bourguignon, & Seron, 2002; Chen & Hamilton, 2012), we also sought to determine whether face type affected how long perceivers spend categorizing racially ambiguous others. We predicted that THE JOURNAL OF SOCIAL PSYCHOLOGY 9 participants would spend more time categorizing computer-generated faces compared to real biracial faces because participants’ increased use of hypodescent as a categorization shortcut with real faces would speed up their categorization process.

Method Participants

One hundred and forty-two undergraduates (102 females; Mage = 18.62, SD = 1.17) participated in the experiment for partial course credit. Based on department recruitment limitations, our goal was to recruit approximately 25–35 participants in each of four conditions during a one-semester recruitment period. The sample had 71 Whites, 42 Asians, 13 Multiracials, 9 Latinos, 4 Blacks, and 3unspecified.

Procedure Participants were randomly assigned to a 2 (stimuli type: computer-generated, real) × 2 (task: 2-Choice categorization, mere exposure) between-subjects experiment. The tasks also differed by whether categorical thinking was primed or not when the 2-Choice categorization option was or was not present. Participants in the 2-Choice Categorization condition read the same prompt from Experiments 1 and 2. Participants in the Mere Exposure condition read: “You will be a shown a series of faces one by one. Each face will remain on the screen for three seconds and will advance automatically. Please pay attention to each face.” Faces were shown for three seconds (see Blascovich et al., 1997; Peery & Bodenhausen, 2008; Experiment 1). The same stimuli, programming, and 8-item essentialism scale from Experiments 1 and 2 were used (α = .78). A timer programmed through Qualtrics timed how long participants spent during the 2-Choice categorization task. All participants completed this experiment on the same lab computers.

Results Hypodescent Relative rates Replicating our previous findings, an independent samples t-test showed that participants in the Real Biracial Faces Condition engaged in more hypodescent than did participants in the Computer- η 2 generated Condition, t(68) = 2.13, p = .04, p = .06.

Absolute rates One-tailed t-tests revealed that participants in the Real Biracial Faces Condition displayed a marginally significant tendency for hypodescent (M = .12, SD = 0.36), t(36) = 1.96, p = .06, Cohen’s d = .65. Participants in the Computer-generated Condition (M = −.08, SD = 0.42) did not engage in hypodescent, t(32) = −1.13, p = .27, Cohen’sd=−0.40.

Categorization latencies In addition, we hypothesized that participants would take longer to categorize the computer- generated faces than real biracial faces. We computed participants’ average categorization response time. As expected, participants categorizing real biracial faces spent significantly less time categorizing each face (M = 2.45 seconds, SD = .98) in comparison to categorizing computer-generated faces − η 2 (M = 2.85 seconds, SD = 1.37; t(68) = 2.02, p = .047, p = .03). 10 S. E. GAITHER ET AL.

Psychological essentialism We conducted a 2(Task) × 2(Stimuli Type) between-subjects ANOVA on psychological essentialism. η 2 There was a main effect of stimuli type, F(1, 138) = 4.79, p = .03, p = .03. As predicted, participants who viewed real biracial faces (M = 3.76, SD = .85) endorsed essentialism more than participants who viewed computer-generated faces (M = 3.42, SD = 1.05). This effect was qualified by a η 2 significant stimuli type by task interaction, F(1, 138) = 4.51, p = .04, p = .03. Follow-up pairwise comparisons confirmed that participants endorsed essentialism more after categorizing real biracial faces (M = 3.97, SD = .75) than after categorizing computer-generated faces (M = 3.28, SD = 1.16), η 2 p = .003, p = .06. Additionally, categorizing real biracial faces led to marginally higher essentialism η 2 than did simply viewing real biracial faces (M = 3.56, SD = .90), p = .07, p = .02. There was no difference in essentialism between participants who were merely exposed to real versus computer- η 2 generated faces, p = .96, p = .01, nor was there a difference in essentialism between participants η 2 who were merely exposed to versus categorized computer-generated faces, p = .25, p = .01.

Discussion Experiment 3 again demonstrated that, compared to computer-generated faces, real biracial faces were categorized more often as Black than as White. Importantly, we also showed that computer- generated stimuli also took longer for participants to categorize. We believe these results provide evidence that participants may categorize real racially ambiguous biracial faces by applying the hypodescent heuristic to them more readily than computer-generated faces, resulting in a faster categorizations. Thus, this research suggests that previous work documenting hypodescent with computer-generated faces may underestimate how often it is actually applied to real biracial individuals. Experiment 3 also found that exposure to real biracial faces actually increased perceivers’ essentialist thinking when they categorized real biracial faces into fixed, monoracial categories compared to when they passively viewed these same faces, or compared to when they categorized or viewed computer-generated faces. One potential question that remains is the possibility that the real biracial face stimuli set is not matched well enough with the computer-generated, FaceGen faces. Further, the previous studies relied on a relatively small number of faces, and it is possible that the findings were influenced by specific, distinctive faces within a stimulus set. Therefore, Experiments 4a and 4b aimed to replicate the findings of Experiments 1–3 by comparing real biracial faces with FaceGen versions of the same faces.

Experiments 4a & 4b: real biracial faces and their matched facegen faces Although the faces utilized in Experiments 1–3 were equivalent on all dimensions measured by the pretest, we have not tested the possibility that the distinctiveness of the real biracial faces is really what drives the differences we see between real biracial faces and computer-generated faces. Therefore, here we directly compare the same real biracial faces to FaceGen versions of those same faces. Study 4a compares outcomes for these faces in the 2-Choice and 3-choice categorization tasks and Study 4b compares outcomes for these faces in the 2-Choice and mere exposure tasks. The stimuli pretest for this set of real and computer-generated faces is presented first, followed by the methods, results, and a combined discussion section.

Stimuli pretest All 20 real biracial faces were converted into FaceGen versions using the Photo Fit Procedure. All images were in color, cropped to an oval shape to display only the face, and were adjusted to uniform size and resolution (275 × 360 pixels; 3.8 × 5.0 inches; see Appendix A). THE JOURNAL OF SOCIAL PSYCHOLOGY 11

Forty participants (24 female; Mage = 34.98, SD = 34.18) were recruited for the pretest via Amazon’s Mechanical Turk using the keywords “short face perception study,” and they received 50 cents for their work. The sample included 29 White, 5 Black, 3 Asian, 2 biracial, and 1 Latino. The same prompt was used from the earlier pretest. Participants were randomly assigned to rate either the 20 real biracial faces or the 20 FaceGen versions of the real biracial faces on a scale ranging from 1(not at all)to7(very much) for each of the following: prototypical White appearance, prototypical Black appearance, racial ambiguity, neutrality of facial expression, attractiveness, how real the face appeared, and distinctiveness. Results showed that the two sets of facial stimuli did not significantly differ on most of the ratings (ts < 1.66, ps > .10; p = .11 was for ratings of attractiveness with the real biracial faces being rated as slightly more attractive than the FaceGen versions). As would be expected, however, the real biracial faces were rated as significantly more real in appearance (M = 5.45, SD = .35) compared to the FaceGen versions (M = 4.83, SD = .25), t(38) = 6.41, p < .001. Therefore, this new set of FaceGen faces created from photos from actual biracial people show the same variability as actual biracial faces with regard to prototypically, racial ambiguity, emotion expression, and distinctiveness.

Experiment 4a: real biracial faces and their matched facegen faces, 2-choice vs. 3-choice task, categorization outcomes and essentialism Participants

Four hundred and eleven participants (201 females; 4 gender unspecified; Mage = 35.28, SD = 12.10) were recruited via Amazon’s Mechanical Turk using the keywords “short face perception study” and received 50 cents for their work. To increase generalizability of our findings from the previous studies, we collected a larger online and non-undergraduate sample. Our goal was to recruit approximately 80–100 participants in each of four conditions. The sample contained 309 Whites, 28 Blacks, 25 Asians, 17 Latino, 19 biracials, and 2 unspecified.

Procedure The study was identical to that of Experiment 2, except, here, participants were randomly assigned to either the 20 pre-tested real biracial faces or the 20 pre-tested FaceGen versions of the real biracial faces in a randomized order and either a 2-Choice or a 3-Choice categorization task. Therefore, the design was a 2 (stimuli type: real biracial faces, real biracial faces as FaceGen) × 2 (categorization task: 2-Choice, 3-Choice) between-subjects design. After the categorization task, participants completed the same 8-item essentialism scale as other experiments (α = .60).

Results Hypodescent Relative rates We used the same analysis approach as in the previous experiments. We conducted a 2 (Categorization Task) × 2(Stimuli Type) between-subjects ANOVA on hypodescent. There was a η 2 main effect of stimuli type, F(1, 407) = 17.72, p < .001, p = .04, and a main effect of categorization η 2 task, F(1, 407) = 23.08, p < .001, p = .05. Participants who categorized the Real Biracial Faces (M = .06, SD = .25) engaged in hypodescent more than those who categorized the Real FaceGen Faces (M = −.02, SD = .15). Participants in the 2-Choice conditions (M = .06, SD = .30) engaged in hypodescent more than participants in the 3-choice conditions (M = −.03, SD = .15). These main η 2 effects were qualified by a significant interaction, F(1, 407) = 138.71, p < .001, p = .25, and we conducted follow-up pairwise comparisons. Participants in the Real Biracial Faces condition engaged in hypodescent significantly more in the 2-Choice (M = .22, SD = .24) than the 3-choice condition 12 S. E. GAITHER ET AL.

− η 2 (M = .11, SD = .12), p < .001, p = .25. Participants in the Real FaceGen Faces condition engaged in hypodescent more in the 3-choice condition (M = .04, SD = .15) than in the 2-Choice condition − η 2 (M = .10, SD = .27), p < .001, p = .06. The 2-Choice condition elicited more hypodescent on real η 2 faces compared to FaceGen faces, p < .001, p = .23, whereas the 3-choice condition elicited more η 2 hypodescent on the FaceGen faces than on the real faces, p < .001, p = .07.

Absolute rates Participants in the 2-Choice/Real Biracial Faces condition engaged in hypodescent (M = .22, SE = .02), t(96) = 9.15, p < .001, Cohen’s d = 1.87, as did participants in the 3-Choice/Real Facegen Faces condition (M = .04, SE = .01), t(111) = 3.02, p < .003, Cohen’s d = .57. Participants in the 3-Choice/Real Biracial Faces condition (M = −.11, SE = .01), t(105) = −8.95, p < .001, Cohen’s d = 0.57, and the 2-Choice/Real Facegen Faces condition (M = −.10, SE = .03), t(95) = −3.50, p < .001, Cohen’s d = −0.72, exhibited hyperdescent (i.e., categorized the faces as more White than Black).

Essentialism We conducted a 2(Categorization Task) × 2(Stimuli Type) between-subjects ANOVA on essentialism. η 2 2 There was a significant interaction, F(1, 398) = 12.17, p <.001, p =.03, which we followed up on by conducting pairwise comparisons. In the 2-Choice condition, participants who categorized Real Biracial Faces (M = 3.93, SD = 1.02) had higher essentialism than participants who categorized Real FaceGen η 2 Faces (M =3.64,SD =.84),p = .04, p = .01. In the 3-choice conditions, participants who categorized Real FaceGen Faces (M =4.01,SD = .98) had higher essentialism than those who categorized Real η 2 Biracial Faces (M =3.64,SD =.92),p =.004, p = .02. When participants viewed the real biracial faces, they had higher essentialism after categorizing them in the 2-Choice task compared to the 3-choice task, η 2 p = .03, p = .01. When participants viewed the real FaceGen faces, they had higher essentialism after η 2 categorizing them in the 3-choice task compared to the 2-Choice task, p = .01, p =.02.

Experiment 4b: real biracial faces and their matched facegen faces, 2-choice vs. mere exposure task, categorization outcomes and essentialism Participants

Five hundred and eleven participants (264 females; 3 gender unspecified; Mage = 33.90, SD = 11.20) were recruited via Amazon’s Mechanical Turk using the keywords “short face perception study,” and received 50 cents for their work. Since Experiments 1–3 all used undergraduate samples, combined with the failed replication during the 3-choice task for the essentialism results in Experiment 4a, our goal was to recruit over 100 participants in each of four conditions. The sample contained 363 Whites, 47 Blacks, 27 Asians, 33 Latino, 31 biracials, and 10 unspecified.

Procedure This study was identical to Experiment 3, except, here, participants were randomly assigned to view either real biracial faces or the FaceGen versions of the real biracial faces. Participants were randomly assigned either to a 2-Choice or a Mere Exposure condition. Therefore, the design was a 2 (stimuli type: real biracial faces, real biracial faces as FaceGen) x 2 (categorization task: 2-Choice, mere exposure) between-subjects design. After the categorization task, participants completed the same 8-item essentialism scale as in the other studies (α = .79). THE JOURNAL OF SOCIAL PSYCHOLOGY 13

Results Hypodescent Relative rates An independent samples t-test confirmed that the face stimuli had a significant effect on the rate of hypodescent, t(256) = −7.56, p < .001, Cohen’s d = −0.95. Consistent with the previous studies, participants in the 2-Choice/Real Biracial Faces condition engaged in hypodescent (M = .23, SE = .03), t(129) = 7.36, p < .001, Cohen’s d = 1.30, whereas participants in the 2-Choice/Real FaceGen Faces engaged in hyperdescent (M = −.11, SE = .03), t(127) = −3.36, p < .001, Cohen’s d = −0.60.

Absolute rates Participants in the 2-Choice/Real Faces condition engaged in hypodescent (M = 0.23, SD = .36), t (129) = 7.36, p < .001, categorizing faces as Black more often than as White. Participants in the 2-Choice/FaceGen condition engaged in hyperdescent (M = −.11, SD = .37), t(127) = −3.36, p < .001, categorizing faces as White more often than as Black.

Essentialism We conducted a 2(Task) × 2(Stimuli Type) between-subjects ANOVA on psychological essentialism. η 2 There was no significant interaction, F(1, 507) = .44, p = .51, p = .001, nor was there a main effect η 2 of stimuli type, F(1, 507) = 1.67, p = .20, p = .003, or a main effect of task, F(1, 507) = .01, p = .93, η 2 p = .000. There were also no significant pairwise comparisons.

Experiments 4a & 4b discussion Experiments 4a and 4b compared real biracial faces to computer-generated versions of those same faces and replicated the previous hypodescent findings—real biracial faces were categorized as Black more often than computer-generated versions of the same faces.3 Together across all experiments, these findings suggest that if perceivers are asked to use monoracial categories to describe racially ambiguous individuals, such as on the U.S. Census or in eyewitness reports, perceivers may exhibit an increase in their tendencies to categorize that ambiguous individual more often as Black relative to as White—at least for real racially ambiguous faces. Regarding essentialist thinking, the present results remain mixed. Experiments 2 and 3 both showed that categorizing a real ambiguous face compared to a computer-generated face using fixed, monoracial categories led to higher essentialism. Experiments 4a and 4b only partially replicated these results. There are a variety of possible explanations for these differences. Undergraduates completed in-lab testing sessions in Experiments 1–3 and non-student adults completed the study online for Experiments 4a and 4b. Although some work suggests that undergraduate and online samples are comparable (e.g., Sprouse, 2011), other work shows that online crowd-sourced samples are higher in social desirability concerns, more motivated by the payment compensation, and more open to new experiences (in other words potentially less fixed or essentialist in their views) compared to a college sample (Behrend, Sharek, Meade, & Wiebe, 2011). Moreover, the samples in Experiments 1–3 were also significantly younger, suggesting perhaps the online adult sample simply had more stable views in general that were less susceptible to change. Individual item analyses also confirms that removing any item from the essentialism scale actually worsens the overall reliability. Given these mixed findings, our work highlights the need for additional research to examine possible boundary effects surrounding the link between exposure to racially ambiguous, biracial faces and racial beliefs (e.g., Eberhardt, Dasgupta, & Banaszynski, 2003; Plaks et al., 2012; Williams & Eberhardt, 2008) and if the use of other essentialism scales may lead to different outcomes. 14 S. E. GAITHER ET AL.

General discussion Our findings extend the literature on racially ambiguous face perception by systematically examining some of the possible factors that may affect the historically and socially important outcome of hypodescent. Despite the fact that computer-generated and real biracial stimuli had the same levels of racial ambiguity, participants consistently applied hypodescent more often toward real biracial faces compared to computer-generated biracial faces (Experiments 1–4) and spent less time while making those decisions (Experiment 3). Given how important racial categorizations are in our society across a variety of contexts such as healthcare, jury decisions, and job interviews (e.g., Maddox, 2004; Sommers, 2007; van Ryn & Burke, 2000), this evidence highlights stimulus differences that face perception researchers should consider in future research. Although the variability seen here might not apply to all computer-generated faces, this set of studies is the first to compare how different types of stimuli and tasks may impact the categorization of racially ambiguous faces. Hypodescent can have a number of negative consequences for targets, including stigmatization, racial profiling, and increased levels of discrimination (e.g., MacLin & Malpass, 2001; Sanchez et al., 2011). Thus, the present findings, which suggest that actual biracial individuals may face higher rates of visual hypodescent, have important implications for the biracial demographic. Importantly, when a third, multiracial categorization option was offered, perceivers were significantly less likely to engage in hypodescent for real biracial faces. This finding emphasizes the importance of acknowl- edging the multiracial category at a societal level since minority categorizations are so strongly correlated with negative social outcomes. Additionally, the current studies provided mixed evidence suggesting that exposure to real biracial faces compared to computer-generated faces may sometimes increase racial essentialist beliefs when categorizing these faces into monoracial categories (i.e., using a two choice categorization task). Thus, more work is needed to understand how stimuli, categorization task, and potential individual differences may impact essentialist beliefs. Moreover, the present data also cannot assess whether existing levels of essentialism endorsement also moderate racially ambiguous face categorization (see Ho et al., 2015). The present studies also had small heterogenous samples of non-White participants. Although our results generally held when using race (White vs. non-White) as a covariate, we lacked the power to systematically investigate participant race differences. Some work has shown that Black individuals perceive racially ambiguous faces similarly to White individuals (Ho et al., 2017) and that White, Asian, and Latino participants categorize multiracial faces in similar ways in 3-Category tasks (Chen & Hamilton, 2012; Chen et al., 2014). However, the majority of hypodescent research has yet to examine whether categorization varies systematically by participant race (Young, Sanchez, Pauker, & Gaither, 2018). A recent paper also suggests that some hypodescent categorization patterns (especially when examining visual hypodescent) may actually reflect a minority categorization bias, whereby, for example, multiracial Black/White targets are simply categorized more often as non- White than White, but not necessarily always as Black (Chen, Pauker, Hamilton, Gaither, & Sherman, 2018). Additionally, the current research (like most previous studies on hypodescent work) used a between-subjects design, and therefore future research should consider the use of within-subject designs to directly test differences based on stimuli and task. Importantly, the present set of studies only included Black/White biracial stimuli and these stimuli only contained 20 unique computer-generated or real biracial faces. We do not know whether these effects apply toward other multiracial combinations (Chen & Norman, 2016). We do know that perceivers often categorize Asian/White biracials in line with hypodescent (Halberstadt et al., 2011; Ho et al., 2011; cf. Chen, Kteily, & Ho, 2017), though they elicit hypodescent to a lesser extent than Black/White biracial faces (Ho et al., 2011). Based on our findings, we would expect to find similar effects for real Asian/White biracial faces, but the differences between real biracial and computer-generated faces might be weaker due to skin tone differences between Asians and Blacks. Moreover, we also only utilized FaceGen computer-generated faces and thus did not measure these results with computer-morphed faces or faces generated by other programs. Experiments 4a and 4b, THE JOURNAL OF SOCIAL PSYCHOLOGY 15 which created FaceGen versions of real biracial faces, help mitigate some concerns surrounding possible differences in distinctiveness between the face stimuli sets, but replications with other types of biracial faces is needed. Finally, our studies only examined racial ambiguity, and there are other ambiguous group members that remain to be examined within this framework (see Tskhay & Rule, 2013, for a review). Knowing that faces of actual people are more multifaceted and distinct than faces typically studied in laboratory settings, these findings spark a needed discussion surrounding stimuli selection and stimuli generalizability to the real world.

Conclusions Although we have shown that past findings, including computer-generated racially-ambiguous stimuli, may be limited in some contexts in their applicability to real-world perceptions of actual biracial individuals, we do not believe that researchers should discontinue the use of these stimuli or that there is an ideal categorization task. Depending on a researcher’smainresearch question, it may be important to use more experimentally controlled stimuli and to have participants categorize faces into dichotomous categories. Furthermore, using computer-generated stimuli (in addition to being an easier form of stimuli to obtain) can also be advantageous for examining how certain components of a face may or may not contribute toward its categorization. However, if a researcher wants to investigate real-world exposure to multiracials, those researchers should use real biracial stimuli to increase ecological validity. On the other hand, if a researcher wants to examine the specific social cognitive processes that underlie face perception outcomes more broadly, using controlled computer-generated stimuli will allow those researchers to isolate specific variables more easily (e.g., independent manipulation of skin tone and facial features). As such, our objective has not been to invalidate previous findings that used either type of stimuli or tasks. Rather, we feel that the current empirical findings highlight an overlooked consideration in research that hopefully will spark needed discussions surrounding generalizability and application of various psychological findings from the lab to the real world.

Notes

1. We conducted all analyses in the manuscript using race (White vs. non-White) as a covariate, and the results yielded the same significance-levels with one exception: the main effect of categorization task in this study became marginally significant, p = .05. 2. Nine participants did not complete essentialism questions and were omitted from analysis. 3. Specific stimuli effects within each condition for the 2-Choice conditions on hypodescent were tested. We conducted a 2 (Stimuli Type) × 20 (Target Face) mixed-model ANOVA with the latter factor within-subjects on categorizations (1 = Black, 0 = White). In all instances, the main effect of stimuli type remained significant and in the expected direction, showing that on average participants engaged in hypodescent more for real faces compared to computer-generated faces (Exps 1–3) or computer-generated versions of the same real faces (Exps 4a, 4b). These results support the main effects that real biracial faces elicited higher levels of hypodescent. Study 1—Stimuli Type effect, p = .04; Study 2—Stimuli Type effect, p < .001; Study 3—Stimuli Type effect, p = .04; Study 4a—Stimuli Type effect, p < .001; Study 4b—Stimuli Type effect, p < .001.

Funding

This work was supported by the Ford Foundation [Dissertation Fellowship];National Science Foundation [Graduate Research Fellowship];Society for the Psychological Study of Social Issues [Clara Mayo Award];University of California, Davis [Chancellor’s Post-doctoral Fellowship];University of Chicago [Provost’s Postdoctoral Scholarship]. 16 S. E. GAITHER ET AL.

Notes on contributors Sarah Gaither is an Assistant Professor in the Department of Psychology and Neuroscience at Duke University. She is also a faculty affiliate at the Cook Center on Social Equity and the Center on Health and Society. Her research focuses on the role identities and diversity exposure play in shaping our behavior and attitudes.

Jacqueline Chen is an Assistant Professor in the Department of Psychology at the University of Utah. Her research examines how an individual's psychology is shaped by his or her social group memberships.

Kristin Pauker is an Associate Professor in the Department of Psychology at the University of Hawaii at Manoa. Her work explores how a person’s immediate environment and culturally-shaped theories about race impact basic social perception, social interactions, and stereotyping in childhood and throughout development. Samuel Sommers is an Associate Professor in the Department of Psychology at Tufts University. His research investigates issues related to stereotyping, prejudice, and group diversity.

References

Allport, G. W. (1954). The nature of prejudice. Reading, MA: Addison-Wesley. Bailenson, J. N., Yee, N., Merget, D., & Schroeder, R. (2006). The effect of behavioral realism and form realism of real- time avatar faces on verbal disclosure, nonverbal disclosure, emotion recognition, and copresence in dyadic interaction. Presence: Teleoperators and Virtual Environments, 15, 359–372. doi:10.1162/pres.15.4.359 Bastian, B., Loughnan, S., & Koval, P. (2011). Essentialist beliefs predict automatic motor-responses to social categories. Group Processes & Intergroup Relations, 14, 559–567. doi:10.1177/1368430210385258 Behrend, T. S., Sharek, D. J., Meade, A. W., & Wiebe, E. N. (2011). The viability of crowdsourcing for survey research. Behavior Research Methods, 43, 800. doi:10.3758/s13428-011-0081-0 Blascovich, J., Wyer, N. A., Swart, L. A., & Kibler, J. L. (1997). Racism and racial categorization. Journal of Personality and Social Psychology, 72, 1364–1372. doi:10.1037/0022-3514.72.6.1364 Bodenhausen, G. V., & Macrae, C. N. (1998). Stereotype activation and inhibition. In R. S. Wyer Jr. (Ed.), Stereotype activation and inhibition: Advances in social cognition (Vol. 11, pp. 1–52). Hillsdale, NJ: Erlbaum. Buhrmester, M. D., Kwang, T., & Gosling, S. D. (2011). Amazon’s Mechanical Turk: A new source of inexpensive, yet high-quality data? Perspectives on Psychological Science, 6,3–5. doi:10.1177/1745691610393980 Carpinella, C. M., Chen, J. M., Hamilton, D. L., & Johnson, K. L. (2015). Gendered facial cues influence race categorizations. Personality and Social Psychology Bulletin, 41, 405–419. doi:10.1177/0146167214567153 Castano, E., Yzerbyt, V., Bourguignon, D., & Seron, E. (2002). Who may enter? The impact of ingroup identification on ingroup/outgroup categorization. Journal of Experimental Social Psychology, 38, 315–322. doi:10.1006/ jesp.2001.1512 Chao, M. M., Hong, Y., & Chiu, C. (2013). Essentializing race: Its implications on racial categorization. Journal of Personality and Social Psychology, 104, 619–634. doi:10.1037/a0031332 Chen, J. M., & Hamilton, D. L. (2012). Natural ambiguities: Racial categorization of multiracial individuals. Journal of Experimental Social Psychology, 48, 152–164. doi:10.1016/j.jesp.2011.10.005 Chen, J. M., & Norman, J. B. (2016). Toward a comprehensive understanding of the factors underlying multiracial person perception. Analyses of Social Issues and Public Policy, 16(1), 417–420. doi:10.1111/asap.12122 Chen, J. M., Kteily, N. S., & Ho, A. K. (2018). Whose side are you on? Mistrust of Asian-White biracials’ allegiances leads Asian Americans to deny them group membership. Personality and Social Psychology Bulletin, Early Online Access. doi:10.1177/0146167218798032 Chen, J. M., Moons, W. G., Gaither, S. E., Hamilton, D. L., & Sherman, J. W. (2014). Motivation to control prejudice predicts categorization of multiracials. Personality and Social Psychology Bulletin, 40, 510–603. doi:10.1177/ 0146167213520457 Chen, J. M., Pauker, K., Hamilton, D., Gaither, S. E., & Sherman, J. (2018). Black + White = Not White: A minority bias in categorizations of Black-White multiracials. Journal of Experimental Social Psychology, 78,43–54. doi:10.1016/j.jesp.2018.05.002 Dunham, Y., & Olson, K. R. (2016). Beyond discrete categories: Studying multiracial, intersex, and transgender children will strengthen basic developmental science. Journal of Cognition and Development, 17, 642–665. doi:10.1080/15248372.2016.1195388 Eberhardt, J. L., Dasgupta, N., & Banaszynski, T. L. (2003). Believing is seeing: The effects of racial labels and implicit beliefs on face perception. Personality and Social Psychology Bulletin, 29, 360–370. doi:10.1177/0146167202250215 Freeman, J. B., Pauker, K., Apfelbaum, E. P., & Ambady, N. (2010). Continuous dynamics in the real-time perception of race. Journal of Experimental Social Psychology, 46, 179–185. doi:10.1016/j.jesp.2009.10.002 THE JOURNAL OF SOCIAL PSYCHOLOGY 17

Gaither, S. E. (2015). “Mixed” Results multiracial research and identity explorations. Current Directions in Psychological Science, 24, 114–119. doi:10.1177/0963721414558115 Gaither, S. E., Babbitt, L. G., & Sommers, S. R. (2018a). Resolving racial ambiguity in social interactions. Journal of Experimental Social Psychology, 76, 259–269. doi:10.1016/j.jesp.2018.03.003 Gaither, S. E., Toosi, N., Babbitt, L.G., & Sommers, S. R. (2018b). Exposure to multiracial faces decreases colorblind attitudes. Personality and Social Psychology Bulletin. Online Early Access. doi:10.1177/0146167218778012 Gaither, S. E., Pauker, K., Slepian, M. L., & Sommers, S. R. (2016). Social belonging motivates categorization of racially ambiguous faces. Social Cognition, 34,97–118. Gaither, S. E., Schultz, J. R., Pauker, K., Sommers, S. R., Maddox, K. B., & Ambady, N. (2014). Essentialist thinking predicts decrements in children’s memory for racially ambiguous faces. Developmental Psychology, 50, 482–488. doi:10.1037/a0033493 Halberstadt, J., Sherman, S. J., & Sherman, J. W. (2011). Why Barack Obama is Black: A cognitive account of hypodescent. Psychological Science, 22,29–33. doi:10.1177/0956797610390383 Haslam, N., Rothschild, L., & Ernst, D. (2000). Essentialist beliefs about social categories. British Journal of Social Psychology, 39, 113–127. doi:10.1348/01446660016436 Hinzman, L., & Kelly, S. D. (2013). Effects of emotional body language on rapid out-group judgments. Journal of Experimental Social Psychology, 49(1), 152–155. doi:10.1016/j.jesp.2012.07.010 Ho, A. K., Kteily, N., & Chen, J. M. (2017). “You’re one of us”: Black Americans’ use of hypodescent and its association with egalitarianism. Journal of Personality and Social Psychology, 113, 753–768. doi:10.1037/pspi0000107 Ho, A. K., Roberts, S. O., & Gelman, S. A. (2015). Essentialism and racial bias jointly contribute to the categorization of multiracial individuals. Psychological Science, 26(10), 1639–1645. doi:10.1177/0956797615596436 Ho, A. K., Sidanius, J., Cuddy, A. J. C., & Banaji, M. R. (2013). Status-boundary enforcement and the categorization of Black-White biracials. Journal of Experimental Social Psychology, 49, 940–943. doi:10.1016/j.jesp.2013.04.010 Ho, A. K., Sidanius, J., Levin, D. T., & Banaji, M. R. (2011). Evidence for hypodescent and racial hierarchy in the categorization and perception of biracial individuals. Journal of Personality and Social Psychology, 100, 492–506. doi:10.1037/a0021562 Hugenberg, K., & Bodenhausen, G. V. (2004). Ambiguity in social categorization the role of prejudice and facial affect in race categorization. Psychological Science, 15, 342–345. doi:10.1111/j.0956-7976.2004.00680.x Jordan, W. D. (2014). Historical origins of the one-drop racial rule in the United States. Journal of Critical Mixed Race Studies, 1(1). Retrieved from https://escholarship.org/uc/item/91g761b3 Kang, S. K., & Bodenhausen, G. V. (2015). Multiple identities in social perception and interaction: Challenges and opportunities. Annual Review of Psychology, 66, 547–574. doi:10.1146/annurev-psych-010814-015025 Krosch, A. R., Berntsen, L., 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, 1196–1203. doi:10.1016/j.jesp.2013.05.009 Krosch, A. R., & Amodio, D. M. (2014). Economic scarcity alters the perception of race. Proceedings of the National Academy of Sciences, 111(25), 9079–9084. doi:10.1073/pnas.1404448111 Leyens, J. P., Rodriguez, A. P., Rodriguez, R. T., Gaunt, R., Paladino, P. M., & Vaes, J. (2001). Psychological essentialism and the differential attribution of uniquely human emotions to ingroups and outgroups. European Journal of Social Psychology, 31 , 395–411. doi:10.1002/ejsp.50 MacLin, O. H., & Malpass, R. S. (2001). Racial categorization of faces: The ambiguous race face effect. Psychology, Public Policy, and Law, 7,98–118. doi:10.1037/1076-8971.7.1.98 Maddox, K. B. (2004). Perspectives on racial phenotypicality bias. Personality and Social Psychology Review, 8, 383– 401. doi:10.1207/s15327957pspr0804_4 Mullen, B., Brown, R., & Smith, C. (1992). Ingroup bias as a function of salience, relevance, and status: An integration. European Journal of Social Psychology, 22, 103–122. doi:10.1002/ejsp.2420220202 No, S., Hong, Y., Liao, H., Lee, K., Wood, D., & Chao, M. M. (2008). Lay theory of race moderates Asian Americans’ responses toward American culture. Journal of Personality and Social Psychology, 95, 991–1004. doi:10.1037/ a0012978 Oberman, L. M., Ramachandran, V. S., & Pineda, J. A. (2008). Modulation of mu suppression in children with autism spectrum disorders in response to familiar or unfamiliar stimuli: The mirror neuron hypothesis. Neuropsychologia, 46, 1558–1565. doi:10.1016/j.neuropsychologia.2008.01.010 Pauker, K., Meyers, C. K., Sanchez, D. T., Gaither, S. E., & Young, D. M. (2018). A review of multiracial malleability: Identity, categorization, and shifting racial attitudes. Social and Personality Psychology Compass, 12, e12392. doi:10.1111/spc3.v12.6 Pauker, K., Weisbuch, M., Ambady, N., Sommers, S. R., Adams, R. B., Jr., & Ivcevic, Z. (2009). Not so black and white: Memory for ambiguous group members. Journal of Personality and Social Psychology, 96, 795–810. doi:10.1037/ a0013265 Peery, D., & Bodenhausen, G. V. (2008). Black+ White= Black hypodescent in reflexive categorization of racially ambiguous faces. Psychological Science, 19, 973–977. doi:10.1111/j.1467-9280.2008.02185.x 18 S. E. GAITHER ET AL.

Plaks, J. E., Malahy, L. W., Sedlins, M., & Shoda, Y. (2012). Folk beliefs about human genetic variation predict discrete versus continuous racial categorization and evaluative bias. Social Psychological and Personality Science, 3,31–39. doi:10.1177/1948550611408118 Richeson, J. A., & Sommers, S. R. (2016). Toward a social psychology of race and race relations for the twenty-first century. Annual Review of Psychology, 67, 439–463. doi:10.1146/annurev-psych-010213-115115 Rothbart, M., & Taylor, M. (1992). Category labels and social reality: Do we view social categories as natural kinds? In G. R. Semin & K. Fiedler (Eds.), Language and social cognition (pp. 11–36). Thousand Oaks, CA, US Sage Publications, Inc. Sanchez, D. T., Good, J. J., & Chavez, G. (2011). Blood quantum and perceptions of Black-White biracial targets: The black ancestry prototype model of affirmative action. Personality & Social Psychology Bulletin, 37,3–14. doi:10.1177/ 0146167210389473 Schroeder, R. (2002). Social interaction in virtual environments: Key issues, common themes, and a framework for research. In R. Schroeder (Ed.), The social life of avatars: Presence and interaction in shared virtual environments (pp. 1–18). London, UK: Springer. Sommers, S. R. (2007). Race and the decision-making of juries. Legal and Criminological Psychology, 12, 171–187. doi:10.1348/135532507X189687 Sprouse, J. (2011). A validation of Amazon Mechanical Turk for the collection of acceptability judgments in linguistic theory. Behavior Research Methods, 43, 155–167. doi:10.3758/s13428-010-0039-7 Tskhay, K. O., & Rule, N. O. (2013). Accuracy in categorizing perceptually ambiguous groups a review and meta- analysis. Personality and Social Psychology Review, 17,72–86. doi:10.1177/1088868312461308 van Ryn, M., & Burke, J. (2000). The effect of patient race and socio-economic status on physicans’ perceptions of patients. Social Science and Medicine, 50, 813–828. doi:10.1016/S0277-9536(99)00338-X Williams, M. J., & Eberhardt, J. L. (2008). Biological conceptions of race and the motivation to cross racial boundries. Journal of Personality and Social Psychology, 94, 1033–1047. doi:10.1037/0022-3514.94.6.1033 Young, D., Sanchez, D., Pauker, K., & Gaither, S. E. (2018, under review). Testing the predictions of hypodescent and the ingroup over-exclusion effect: Meta-analytic and systematic review of multiracial and racially ambiguous categorization. Young, D., Sanchez, D. T., & Wilton, L. S. (2013). At the crossroads of race: Racial ambiguity and biracial identification influence psychological essentialist thinking. Cultural Diversity and Ethnic Minority Psychology, 19, 461–467. doi:10.1037/a0032565 THE JOURNAL OF SOCIAL PSYCHOLOGY 19

Appendix A

FaceGen Computer-Generated Black/White Face Samples

Real Biracial Black/White Face Samples

Real Biracial Black/White Faces as FaceGen Samples Of the Above Real Faces

Note: Stimuli were shown in color for all experiments.