Racial Attention Deficit
Racial Attention Deficit
Sheen S. Levine1,2 *, Charlotte Reypens1
, and David Stark2,3
1 The University of Texas at Dallas, Richardson, TX 75080, USA
2 Columbia University, New York, NY 10027, USA
3 University of Warwick, Coventry CV4 7AL, UK
* To whom correspondence may be addressed. Email: [email protected]
Teaser
Americans make poor decisions because they ignore their Black peers — a large
experimental study shows and suggests a remedy.
Abstract
Despite concerted efforts towards equity in organizations and elsewhere, minority members
report that they are often ignored and their contributions undervalued. Against this
backdrop, we conduct a multi-year experimental study to investigate patterns of attention,
using a large, gender-balanced sample of White working-age Americans. The findings
provide causal evidence of a racial attention deficit: Even when in their best interest, White
Americans pay less attention to Black peers. In a baseline study, we assign an incentivized
puzzle to participants and examine their willingness to follow the example of their White and
Black peers. White participants presume that Black peers are less competent — and fail to
learn from their choices. We then test two interventions: Providing information about past
accomplishments reduces the disparity in evaluations of Black peers, but the racial attention
deficit persists. When Whites can witness the accomplishments of Black peers — rather than
being told about them — the racial attention deficit subsides. We suggest that such a deficit
can explain racial gaps documented in science, education, health, and law.
Introduction
Despite the long struggle to promote diversity and create equity, racial disparities continue to
disfigure the core institutions of society. From policing to housing and medical care, from
our criminal justice system to our universities and research institutes, minorities confront
bias in treatment and access. Alongside inequalities in income, education, and health, there is
also a disparity in attention. By investigating the patterns of who pays attention to whom,
our study provides evidence of a racial attention deficit: Even when in their self-interest,
Whites pay less attention to Black peers. Specifically, White Americans rate Black peers as
less competent than White ones, and are less likely to follow their example as a guide to
making a better decision. The findings corroborate qualitative evidence that Blacks are more
likely to be overlooked or underestimated (1, 2). Racial attention deficit provides a
behavioral mechanism that can explain the gaps documented in science, education, health,
and law (3-9) — gaps that are not easily explained by extent theories of racial discrimination.
As we discuss, racial attention deficit is distinct from other forms of discrimination, and it
carries essential consequences for organizations and society.
We test two remedial interventions: When we provide information about prior
accomplishments of Black peers, White participants rate them as equally skillful but remain
hesitant to learn from their choices. In contrast, when Whites can experience the ongoing
accomplishments of Black peers, the exposure changes not only attitudes — but also closes
the attention deficit. The findings suggest that measures to establish ongoing, experiential
recognition can marshal racial diversity as a resource for learning in organizations.
Squandered Learning Opportunities
Learning from others can be valuable. Sometimes such learning requires that one recognizes
the limits of their viewpoint and acknowledges that others may possess better information.
As organizations in many fields are becoming less homogeneous, racial diversity adds new
perspectives, offering more opportunities for potential learning. Yet the evidence points to a
racial disparity in attention. Such patterns are observed across individuals and disciplines
even in science — where recognizing the limitations of one?s viewpoint is so fundamental to
the scientific endeavor. This is evidenced by a recent analysis of 1.2 million doctoral
dissertations: Although researchers from underrepresented groups produce higher rates of
scientific innovation, their novel contributions are devalued: Taken up at lower rates and less
likely to result in successful scientific careers than for majority groups (3).
Similar patterns emerge in questionnaires, interviews, and personal accounts (10-12). Black
university students report that White peers are reluctant to collaborate with them on
classroom projects, and professors are less likely to invite them to work on research (13). A
survey of thousands of medical school faculty revealed that underrepresented minorities
reported worse perceptions of inclusion and connection (14). Similarly, a survey of some
9,200 economists found that 83% of Black respondents did not agree that “people of my
race/ethnicity are respected within the field.” Most of the respondents, across races and
ethnicities, agreed that gaps in respect remain (15).
2
Among the many purported benefits of diversity initiatives is the promise that when
minority members contribute novel perspectives, they create a learning opportunity for their
peers. But for minority contributions to affect the performance of others, majority members
must attend to them.
The problem is that when assessing others, observers often resort to irrelevant cues that can
be misleading, even deleterious (16, 17). In a series of experiments, Levine et al. (18) showed
that market traders were more likely to mimic counterparts who happened to share their race
or ethnicity. They were less likely to heed the behavior of non-co-ethnics. Even if such a
distinction was not in the traders? self-interest, it persisted across markets and cultures and
led to mispricing and market bubbles.
Such evidence motivates the question we pose here: To what extent do White working-age
Americans pay attention to Black peers? If people allocate their attention along racial lines,
then they will be less likely to learn from those of a different race. In recent years, advocates
for racial diversity have been stressing that changing the demographic composition of a field
is not enough (19, 20). Diversity initiatives that simply involve the mixing of people with
different characteristics may not suffice to overcome the racial disparity in attention. The
essential link between diversity and learning from peers may require inclusive recognition –
respectful attendance to diverse peers.
The Study: Are Whites Less Likely to Learn from Black Peers?
As an everyday example of learning from the choices of others, consider the decision to
carry an umbrella to work: A woman looks out the window of her urban apartment building
and sees no signs of impending rain. On second thought, she turns her gaze to the sidewalk
below, where she observes many passersby carrying umbrellas. Aware that the perspective
from her window allows only a limited view of the sky, she rightly grabs her umbrella when
leaving the apartment. It would seem unwise for her to ignore the umbrella-carrying choices
of minority passersby. Yet something like that might be happening, with more severe
consequences, in the organizations in which we live and work.
To answer questions about attention and behavior across races, we designed an experiment
that resembles the umbrella-carrying decision. Tasked with solving a puzzle, participants
were exposed to (what they knew to be) ambiguous information. Before deciding, they could
observe the choices of two peers who, like the umbrella-carrying passersby, solved the same
puzzle. A participant could reach an accurate solution only if they noticed the peers? choices
and incorporated that information in their decision-making (Appendix). Put differently,
whether a participant paid attention to their peers was evident from the solution submitted.
Those who failed to attend to others? choices made poor decisions.
By experimentally varying the race of the peers, we were able to ascertain whether White
participants paid equal attention to Black peers versus White ones (Fig. 1 and Materials and
Methods).
Like many organizational decisions, the puzzle required piecing together uncertain
information to reach a decision. And the task was highly salient for achieving a reward based
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observe the solutions of two peers, who are identified by their first names, typically
American Black or White. Depending on the condition, participants may also receive
information about past peer accomplishments or witness the ongoing accomplishments of
their peers. (III) The participant submits a solution, then he or she assesses peers? skill and
provides some demographic information. At the session?s end, (IV) the participants who
choose correctly receive a 200% bonus. For details, see Materials and Methods and
Appendix.
Sample
To answer the research question, we assembled a highly powered sample of White workingage
Americans (N=2,116). Sample size and criteria for recruitment and exclusion were
preregistered, and we proceeded to recruit participants.
We screened on demographics, and each prospective participant also underwent a rigorous
comprehension test of the task (see Materials and Methods). After attrition due to lacking
comprehension and other causes, the initial sample produced a usable sample (N=1,449)
that was gender-balanced (Male: 49.6%; Female: 48.5%; Non-binary: 1.9%) comprised of
participants who were well educated (over 88% had at least some higher education) and of
working-age (mean age: 35; 97.5% between ages 18–65). The setting allowed us to motivate
participants to reason carefully: Those who answered correctly earned up to $26.43/hour,
well above the going rate (see Materials and Methods).
Experimental Conditions
Participants were randomized into 6 conditions (2x3 design), such that any given participant
was matched with two fictitious peers who bore typically (A) Black or (B) White names —
and each participant either I) received no information about peer accomplishments (Baseline);
or II) received information about the prior accomplishments of the peers (Information
Provision); or III) could experience the ongoing accomplishments of the peers by witnessing
them (Experiential Recognition).
Information Provision. Before engaging with the puzzle, each participant received
information about the peers? prior accomplishments. This design allowed us to observe if a
participant is more likely to pay attention to peers after learning that they performed well in a
test of relevant ability. Why might such a priori certification remedy the racial attention
deficit? If ignorance causes prejudice, then it can be cured by information, argues a longrooted
view (23-25). Similarly, if discrimination is statistical (26, 27), then it should be
diminished when information about specific individuals replaces population averages.
Empirically, a similar treatment was shown to reduce sex discrimination in employment (28).
The treatment is also informed by evidence that minorities were quicker to integrate into
professions that rely on credentials (29).
But there are also reasons to expect that a priori certification will not change racial disparities
in attention. Studies suggest that credentials held by Black job applicants or employees may
matter less than identical ones held by Whites (30-32). Research, both archival and
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experimental, questions the possibility of reducing bias or encouraging diversity through the
provision of information (33-36).
Method-wise, participants in this condition were first asked to undergo a test of cognitive
ability (Appendix). After the test, we provided their grades together with the grades of their
peers, which were invariably high (Appendix). Then, as in the baseline study, participants
were presented with the experimental task and peer choices, made behavioral choices, and
evaluated peers? skills.
Experiential Recognition. Whereas information provision involves a priori information
about skill, this intervention directly alters the participant?s experience with peers. As the
participant repeatedly observes the peers? behavior, he or she witnesses the peers? continued
accomplishments. This treatment, therefore, involves the ongoing experience of peers?
abilities.
The treatment is informed by research that points to recognition gaps, “disparities in worth
and cultural membership between groups in a society” (2), resulting from stigmatization in
which the contributions of individuals and groups are devalued. Not based on racial
antipathy or overtly racist ideology (16, 31, 37), stigmatization is an environmental condition
(38-40). This remedy corresponds to a situation in which an organization adopts a policy of
subtle inclusion cues, built into the work environment. Such policies can be designed not
only to “affect the psychology of [targeted minorities], but also the psychology of those who
interact with them” (20).
Why may experiential recognition remedy the racial attention deficit? Psychologists have
shown that learning from experience differs from learning from description (41). People
seem to weigh experience more heavily than other sources of knowledge (42, 43), perhaps
because personal experience is readily available and emotionally vivid (44, 45). Researchers
found that experience can reduce the tendency to categorize people by their race (46). An
experience perceived as positive can reduce bias (although just slightly; 47). But on the other
hand, the experience of diversity has been associated with outcomes that suggest less
attention to minority members, such as reduced communications (48), increased polarization
(49), and inadequate responses to changing circumstances (50). Further, experiencing firsthand
contact may maintain or even reinforce stereotypes (51, 52). In this setting, such
findings imply that Whites could remain inattentive to Black peers. A similar prediction
arrives from other research perspectives: Black peers can be overlooked if Whites prefer
learning from peers of the same race (18), possess ingrained racial animosity (27), or
generally rely on stereotypes (23, 53, 54). These different theoretical causes would similarly
predict that this remedy proves futile.
Method-wise, participants in this condition encountered an extended form of the baseline
study, which encompassed three rounds rather than one. In the first round, the participant
followed the same procedure as in the baseline condition. After submitting their solution to
the puzzle, the participant could observe the accuracy of his or her choice — and the alwaysaccurate
choices of the peers, Black or White. In the next rounds, we presented puzzles of
similar nature but varied the information (Appendix). Each participant remained matched
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with the same peers throughout the session. After the last round of behavioral choices, we
collected peer evaluation, as in the other conditions.
Results
We validated the approach and instrument by documenting several expected results
(Appendix). Then, we proceeded to examine how race shapes attention to peers and the
evaluation of their skills.
Baseline
Although participants could only gain by learning from their peers, they exhibit a racial
attention deficit: In the Baseline condition, participants are 33% more likely to pay attention
to White peers (0.68) compared to Black ones (0.51) (?2=13.823, p<0.0002). Relatedly,
participants evaluate Black peers as less skilled than White ones (Fig. 2; t(488)=4.0022,
p<0.0001, d=0.362). We find no gender-related differences in attention. Specifically, here
and in the other conditions, the results remain after statistically adjusting (controlling) for
participants? gender, cognitive ability, education, and recollection of peer race (Appendix).
Some worry that online studies underestimate effect sizes (55). This may be particularly true
in this study: Research shows that, compared to face-to-face interaction, computer-mediated
communication shows less intergroup bias (56) and less consideration of irrelevant cues,
such as race (57). Thus, the bias we find online may be exacerbated in face-to-face
interaction.
Information Provision
In contrast to the baseline study, information provision erases racial disparity in the
assessment of peer skill (Fig. 2; t(483)=1.1096, p<0.2677). When it comes to behavior, the
deficit in attention narrows but remains substantial: Even with information, participants are
still 15% less likely to attend to Black peers compared to White ones (White = 0.68; Black =
0.59; ?2=4.808, p<0.0283). Information provision ameliorates, but does not eliminate, the
racial attention deficit. The disparities are proven robust in various statistical specifications
(Appendix).
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candidates vying for the Democratic presidential nomination, culminating in the nomination
of a mixed-race woman to the vice president office in the summer. Ultimately, the year was
shaped by the outbreak of Covid19, a pandemic that impacted billions and took a grim toll
on American minorities. (Data collection was completed before the presidential election
results were known).
To assess how such events may have affected the racial attention deficit, we turned to data
collected in the summer of 2017 using a similar method and sample (N=439).
Notwithstanding the focal events of 2020, we cannot reject the hypothesis that attention to
Black peers has remained unchanged: The likelihood of attending to Black peers in 2017 and
2020 are statistically indistinguishable (Appendix).
Discussion
Why Study Racial Attention Deficit?
Efforts at integration, decades in the making at organizational and societal levels, have been
slow to bear fruit. For example, in personal accounts, minority scientists sense feeling
“unwelcome, unheard, and unvalued” (10). In discussions and interviews, faculty often
lament that their competence is questioned due to their race (11). Even when firms seek to
recruit a more diverse cadre of employees, they dismayingly discover that minorities are
more likely to leave (58). Why? We highlight a less-discussed and less-studied cause:
inattention.
Much is known about disparities in the distribution of resources, but the racial attention
deficit is a form of inequality understudied to date (2). As a distinct form of discrimination,
racial attention deficit consists of underestimating, overlooking, or ignoring members of
certain groups (1, 2). It differs from other forms of disparity in at least four ways: It does not
require the presence of racial animosity, explicit or implicit. It is exhibited behaviorally,
through choices and decisions — as opposed to stated beliefs, perceptions, or intentions. It
is revealed as omission (of attention) rather than commission (of explicit antipathy). And it
harms minorities but also majorities, albeit differently.
Racial attention deficit may be the behavioral mechanism underlying a string of intriguing
findings: The dissertations of minority scientists are more innovative, but are less likely to be
noticed (3). Black employees are less likely to be nominated for award, presumably because
their achievements are more likely to be overlooked (4). Computer algorithms used to
allocate healthcare underestimate the needs of Black patients (5). Black infants are more
likely to survive when they share their physician?s race (6), and Black men are more likely to
take their physician?s recommendations when their race is concordant (7). Although some of
these examples can be explained by some form of perverse yet cloaked racism, greater trust
and/or better communication, all of them are consistent with single explanation — a racial
attention deficit.
Racial attention deficit may stem from stigmatization. Not overt, stigmatization can be subtle
(40, 59). Nonetheless, it goes to the very core of relations among individuals and groups in
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society because it is about the fundamental question of worth: What is valuable? Who is
worthy? (60, 61) Racial attention deficit is a product of social structures in which Blacks and
other minorities are stereotyped as less worthy. Devalued, their actions and choices are
disregarded. Overlooked in the structure of attention, they are robbed of opportunities; and
this lack of recognition undermines their self-worth. Racial attention deficit, moreover,
undermines performance for both minorities and majorities. While some forms of
discrimination harm primarily the victim, here society suffers doubly, as both the
discriminator and the discriminated suffer the consequences of bias.
This is evident in our baseline study, which shows that even when their self-interest should
steer them to learn from peers, Whites are less likely to pay attention to Black ones. When
we introduce the information provision treatment, Whites are less likely to underestimate the
skills of Black peers (Fig. 2). But merely providing information about peers is not enough.
True, it closes the gap in espoused sentiments, resulting in higher evaluations of the skills of
Black peers, but it does not eliminate the racial attention deficit. White participants exposed
to information about peers are still less likely to follow others? choices when those peers
were Black. Such a gap has been documented elsewhere: In a recent experiment, financial
investors rated some Black-led teams more favorably than White-led teams, but when it
came to acting on this positive sentiment, they showed no such intention (32). If biased
choices stem from a racial attention deficit, it is easier to understand the feeble outcomes
associated with diversity training sessions (33, 34), initiatives to reduce prejudice (35), or
implicit bias training (62). However well-intended, these cures may be treating the wrong
disease.
If stigmatization can be subtle and built into the organizational environment, it follows that
remedies should be deliberately designed as subtle and as close as possible to workplace
interactions. Experiential recognition thus directly takes up the challenge to develop
remedies that may not be quick or easy (35). But with such a remedy, inclusion can be
accomplished without the cynicism and backlashes sometimes triggered by efforts to
promote equal treatment (63-65).
The provision of information eliminates disparity in skill assessment and lessens the racial
attention deficit. Experiential recognition, the second intervention, not only erased the racial
attention deficit but also raised the perceived skill of Blacks above that of Whites. What is
more, it is evident that the two treatments increased attention to Black peers more than they
increased attention to White ones. Such a result is expected if the treatments dissipate
negative stereotypes (32).
We recognize that overcoming bias may be more demanding than it appears. Our design
introduced Black peers who were always accurate and placed them directly in front of the
White participants. But outside the experimental realm, no one is flawless. And Whites are
not required to gaze at minority peers, let alone generalize the observation to dissipate
stereotypes.
Our results cannot tell how long the remedy will last nor whether the Whites are generally
more willing to learn from Blacks (or just the Black peers they encountered). Future research
10
can assess these questions. Our remedy is not meant to cure bias once and for all, but it
shows that Whites are willing to learn from some Black peers at some point in time.
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Starting from the notion that attention is a cognitive resource, psychologists have recently
attempted to redirect the “attentional spotlight” (66) as a means to ameliorate social ills,
including interventions meant to bring people to pay more attention to what they post on
social media (67) and when they are supposed to appear in court (68).
We complement this individualistic perspective with one that places attention in a social
context: Who?s paying attention to whom? Who recognizes whom as worthy of attention?
(59, 60). This question is relevant for many aspects of social life. Our finding that attention is
allocated along racial lines has implications, to take one example, for our courts: If White
jurors pay less attention to Black as opposed to White witnesses, this could contribute to
unfair rulings in civil cases and unfair judgements in our criminal justice system. Or take
another example, from the medical field: If White physicians do not pay enough attention to
the behavior and communications of their Black patients, the results can be misdiagnoses
and inadequate treatments.
Our finding that attention is allocated along racial lines – causing learning opportunities to
be squandered, and hurting majority as well as minority members – has implications for
organizations, whether businesses or non-profits. By turning on an attentional spotlight to
illuminate peers? accomplishments, greater equity in the allocation of attention can bring
greater effectiveness in accomplishing our collective goals.
It can pay, our study shows, to pay attention. Whether in learning from co-workers or from
competitors, organizations amplify opportunities to benefit from paying attention to others.
Science, in particular, provides good examples of learning based on recognizing the
limitations of one?s viewpoint: We scientists submit our work to the review of peers, and in
turn, review our peers? work. We join workshops and conferences to learn from other
scientists, we recruit new members into our departments to bring fresh insights from
outside, and we encourage our colleagues to dissent when there is a danger of locking into a
myopic perspective.
As the institutional arena most organized around principles of open observation and
communication, science is the best example of a setting where we — as a society — should
be highly attentive to structures and practices that promote or obstruct peer learning. Science
is a collective enterprise. Individual genius might still play some role, but discoveries are
increasingly produced in teams. Bibliometric studies, for example, report a substantial
growth in the number of co-authors of scientific articles across almost all fields of
knowledge production (69). Beyond sheer numbers, teams can be more productive and have
a greater impact because they can bring greater diversity of backgrounds and perspectives to
bear on a problem (70-72).
If science is becoming more collective and collaborative, it is also becoming more
demographically diverse. Historically underrepresented categories — women and racial
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minorities — are gaining entry to and establishing careers in scientific fields that were once
homogenous. But for the benefits of diversity to be realized, scientists must learn from their
peers.
The question with which we opened is whether racial attention deficit undermines such
learning. In an uncertain environment, we documented, White decision-makers are more
likely to disregard information emanating from Black peers, even if objectively essential. By
failing to recognize the perspective of the racial other and clinging to their observational
viewpoint alone, they miss opportunities to learn, thus undermining their own performance.
The unmistakable implication of the findings of our baseline study is that policymakers must
recognize that that one legacy of a racially divided society is a bias in attention.
Although an essential first step, recognizing racial attention deficit in one?s organization is, of
course, not enough. For this reason, we further explored interventions that might remove
this obstruction to learning. We found that providing information about the past
accomplishments improved Whites? explicit evaluations of Black peers. But although it
reduced, it did not eliminate the biased behavior in patterns of attention. The findings
indicate that racial attention deficit can be remedied when the accomplishments of Black
peers receive ongoing recognition that is embedded in practice.
Taken together, these findings have crucial lessons for grantors, university presidents, senior
administrators, deans, department chairs, principal investigators, postdocs, PhD students,
research assistants — yes, everyone engaged in the world of science. They are lessons as well
for line supervisors, team leaders, engineers, project managers, professional staff, C-suite
executives, agency heads, members of boards, and members of cabinets — yes, everyone
engaged in organizational affairs whether that be in the fields of business, culture, nonprofits,
or government. Our study evidences that achieving the full benefits of racial diversity
requires policies and practices of inclusion (73). As part of such a strategy, our specific
contribution points to inclusive recognition as a critical component of organizational life.
What our study reveals is that recognition gaps can be corrected. Closing them is crucial.
First, a climate of inclusive recognition, where minority members are respected for their
accomplishments and contributions, improves their well-being (2, 54). Recognition
ultimately matters because human dignity and a sense of worth have intrinsic value. Second,
our research also shows that, by mitigating the attention deficit, recognition enhances
problem solving. Thus, more attention can improve everyone?s performance. If you want to
do right and do better, pay attention to who?s paying attention to whom.
Materials and Methods
To capture the willingness to pay attention to peers, we relied on a familiar experimental
instrument — information cascades (74, 75). Here, as in past research, each participant was
asked to use observational and private information to determine the true state of the world
in hopes of winning a cash prize. Each participant received private information that was
known to be incomplete, had a chance to contemplate it, and then observed the decisions
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(but not the information) of two fictitious peers, identified only by their typical Black or
White names, who answered an identical question.
Since a participant knew that their private information was incomplete, they could benefit
from paying attention to peer choices. Moreover, with the accumulation of information
about peer choices, participants would have been wise to overrule their own guess and
follow the peers. The puzzle is designed such that if both peers make the same choice, the
participant would be right to ignore the private information he or she possesses — and
follow the peers (76, 77). The design allowed us to measure whether participants heeded
peers? choice and whether attention is affected by the peers? race.
The Experimental Task
The task was used as in prior research: All the experimental conditions commenced with the
participant shown two buckets that contained an unequal number of red and blue marbles
(Fig. 3). Each participant was told that one of the buckets was randomly selected as the
winner. To ascertain which bucket it was, the participant received some information:
Marbles were randomly drawn from the winning bucket, shown to the peers and the
participant, and then returned to the bucket. One marble was privately shown to the first
peer, and then that peer publicly guessed the winning bucket. Then, another marble was
drawn and shown to the second peer, who made an identical guess. Finally, a marble was
shown to the participant. The color of that marble always contradicted the information
conveyed through the peer choices. But given the contents of the buckets and the number of
peers, each participant should have overruled their own observation and embrace the peers?
choice (Appendix).
Fig. 3. The puzzle, as shown to the participants. Details in Appendix and Experimental
Instructions.
Racial Cues
The study revolves around race, but an evident manipulation of race conditions can raise a
host of methodological problems, including social desirability and demand characteristics.
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Such concerns have become especially severe since it is no longer socially acceptable to
disclose prejudice or discrimination (16, 31, 35, 78). An explicit manipulation of race is not
only risky, but also unnecessary: Sizeable evidence shows that (a) social categorization of
others based on race and ethnicity is an automatic, implicit, unconscious, and highly accurate
cognitive process (79-81); and (b) mere perception or categorization of racial or ethnic
diversity is sufficient to exert considerable influence on how people behave (82, 83).
To mitigate risks while preserving potency, the experimental design relies on indirect racial
cues: identifying peers? race through typically American Black or White first names. Such
manipulation has been often used in audit and correspondence studies (e.g., 30, 84-87). We
draw upon the name lists used in prior research on racial and ethnic disparities, considering
the objective distinctiveness of racial affiliation, the subjective perception of the name, and
racial differences in socioeconomic status (Appendix).
Before settling on the use of names, we considered alternatives such as face-to-face
interaction or the provision of photos (40, 78). However, visual or verbal cues would have
introduced non-racial cues, such as gender, age, physical attractiveness, and language styles.
These are known to affect the perception of others and thus may confound the effects of
race. Further, the use of face-to-face interaction would have curbed sample size and may
necessitate the use of students, who would have made the study sample younger and less
educated than the working-age population we sought. And had we provided photos of peers,
then we would have needed to ask participants likewise to upload their own images, raising a
host of privacy and technical issues.
In addition to indirect racial cues, we further addressed demand characteristics in several
ways: We asked everyone to provide their first name, so the availability of peer names
appears plausible. In the information provision condition, we required the participants to
start with a test of cognitive ability, so that the grades they subsequently received appeared
legitimate. Finally, we asked participants to submit their answers only after the peers made
their choices. An alternative we considered, asking the participants to report their answers
before and after the peers? choices, risked appearing as if we expected them to mimic the
peers. Similarly, in the experiential recognition condition we chose not to highlight the peers?
accomplishments, but merely report them alongside the participants?.
Sample and Preregistration
Experiments excel in determine causality, and audit and correspondence studies have
become a popular method for studying discrimination (31). Yet, our research question is not
well answered by either method since learning cannot directly be observed or incentivized.
To answer questions about race and learning while preserving the generalizability of the
results, we designed a sample that resembles Whites in the American workforce and
recruited participants from Prolific Academic, a research service that screens participants on
criteria of residency, race, ethnicity, gender, and age (on the benefits and drawbacks of online
experiments, see Appendix).
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Before recruitment began, we preregistered the criteria for participation and exclusion,
together with a statistical power analysis used to determine the sample size. Later, we
deposited in the same location research materials and data
(https://j.mp/OSFRacialAttentionDeficit)
As discussed, an evident treatment of race could raise a host of methodological problems, so
we avoided mentioning race or ethnicity during recruitment. Instead, we relied on
demographic information that participants had provided upon joining the research service to
reach the target population. We took steps to mitigate contamination of the participant pool
(Appendix). Finally, we limited participants to a single session, tracking them to verify that
none attempted to participate more than once. Additionally, the research service uses
financial and phone records to assure that individuals do not hold more than one participant
account.
To corroborate our filters, we asked participants at the end of the experimental session
about their country of residence, race, and ethnicity. Their responses indicate that 99%
resided in the US and 95% describe themselves as White, 4% as Latino (which may be
White), and 1% as neither.
Exclusion Criteria. After reading the experiment?s instructions, each participant was
presented with a rigorous set of comprehension questions to assess their understanding of
the task. Only those who answered all perfectly on the first trial were allowed to participate
in the study. Out of the initial sample of 2,116 participants, 22% did not pass the
comprehension test, 8% did not complete the study, and 1% attempted to participate more
than once, resulting in a usable sample of 1,449 participants. Since participants were rejected
before assignment to experimental conditions, we do not observe differential attrition
(?2=0.67; p>0.98).
Compensation. At a minimum, participants earned the equivalent of $11.49/hour, and
those who answered correctly received up to $26.43/hour, quadruple the minimum wage on
Prolific Academic ($6.50/hour).
Statistical Power. Before commencing data collection, we conducted a priori analysis of
statistical power relying on Fisher?s Exact Test (proportion inequality, two independent
groups) with power (1-? error probability) of at least 0.8 at p=0.05 (88).
Manipulation Checks. As discussed, race and ethnicity are often manipulated indirectly to
mitigate risks while preserving potency. In such a design, a manipulation check can
constitute a treatment in itself, for example by priming participants to focus on peers? race
and not their advice (89). To balance competing demands, we chose to query recollection,
but did not use it as an exclusion criterion, in line with current recommendations and the
preregistration . Specifically, in a post-study questionnaire, after participants have revealed
their behavioral choices and assessment of peers, we presented an open-ended item: “Can
you guess the other players? ethnicity or race? Type anything you can think of.”
Reassuringly, we find no difference in recollection of peer race/ethnicity between the
experimental conditions (accurate recall when peer was White = 0.625; Black = 0.614; t-test
15
p>0.67; Wilcoxon p>0.67). We did not expect that recollection would affect behavior, in line
with the evidence showing that categorization of others based on their race and ethnicity is
an automatic, implicit, and unconscious cognitive process (79-81). As expected, recollection
of peer race/ethnicity does not predict behavior. In other words, whether one remembers a
peer?s race or ethnicity hardly indicates whether they will pay attention to the peer
(Appendix).
The 2017 Study
The earlier study uses the same experimental task, names, and treatments. It relies on a
similar approach to recruitment and exclusion, although it uses a smaller sample, collected
on Amazon Mechanical Turk. The studies were conducted sequentially, rather than
simultaneously, but robustness tests demonstrate no indication of participant contamination
(Appendix).
Ethical Considerations
All the studies have been approved by the relevant ethics committees and institutional
review boards. We have complied with all relevant ethical regulations and obtained informed
consent from all participants in the manner prescribed in the ethics reviews.
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Acknowledgements
This research has been conceived through conversations with many colleagues, including
Xuan Zhou, Janet Xu, Dave Rand, Gary Bolton, Ed Bertschinger, Mark Bernard, and Daniel
Balliet. We value the questions and comments of Amanda Agan, Modupe Akinola, Margarita
Boyarskaya, Birgit Boykin, Prudence Carter, Jana Gallus, Natalia Levina, Jonathan McBride,
Apollinaria Nemkova, and Kathy Phillips.
We are especially grateful for conversations with Sylvester James Gates, Jr., David J. Gross,
Ted Hodapp, James Hollenhorst, and Vivian F. Incera during the 2019 retreat of the
American Physical Society at the Kavli Institute for Theoretical Physics. And for exchanges
with Jeff Flory, Yana Gallen, Judd Kessler, John List, Denise Lewin Loyd, and Neela
Rajendra at the Science of Diversity and Inclusion at the University of Chicago.
We are thankful to those who commented on early drafts, including Kim Böhm, Cancu
Canca, Elena Esposito, Giovanni Formilan, Kyle Hyndman, Shamus Khan, Jennifer Lee,
Felix Mauersberger, Florencio Portocarrero, Sandra Portocarerro, Simon Siegenthaler, and
Holger Spamann.
Our research benefited from comments at faculty seminars at The Rotterdam School of
Management at Erasmus University and the Jindal School of Management at the University
of Texas in Dallas.
We also benefited from comments at conferences: The Science of Diversity and Inclusion at
the University of Chicago; People and Organizations at the Wharton School of the
University of Pennsylvania; Collective Intelligence at Carnegie Mellon University; The
Society for the Advancement of Socio-Economics at the New School; EGOS and
Organization Studies in Kyoto, Japan; The Economic Science Association in Marina del Rey,
Calif. and Vancouver; The Coller Conference on Behavioral Economics at Tel Aviv
University; and the Texas Experimental Association Symposium at Baylor University.
Funding
SSL and DS are grateful for the collegiality and funding of the Jindal School of Management
at the University of Texas at Dallas and the Institute for Social and Economic Research and
Policy (ISERP) at Columbia University in the City of New York. SSL is thankful for an
appointment at the latter. DS acknowledges a grant from the European Research Council,
agreement no. 695256.
19
Author Contributions
SSL, CR, and DS designed the studies, which were conducted and analyzed by SSL and CR.
SSL and DS wrote the manuscript.
Competing Interests
The authors declare no competing interests.
Data and Materials Availability
All data needed to evaluate the conclusions in the paper are present in the manuscript,
Supplementary Materials, and/or deposited with the Open Science Framework.
S1
Appendix
Scale Reliability: Peer Skill
This scale assesses the perception of peer skill using six items, each rated on a 7-point Likert scale,
??????????????far below ?????????????????above ???????? (see Participant Instructions). The scale
demonstrates high reliability (????????????=0.9734). The reliability remains virtually unchanged,
even if excluding each of the items (Table S1).
Cronbach????
Entire scale 0.9734
Excluding ?r?????????? 0.9684
???????????????????? 0.9692
????????????????????? 0.9687
E??????????????????? 0.9673
E????????????????????? 0.9682
E????????????????????? 0.9674
Table S1: Reliability of the Peer Skill scale
The Experimental Puzzle and Its Solution
As discussed, each participant was told that one of the buckets was randomly selected as the winner.
To ascertain which bucket it was, the participant received some information: Marbles were randomly
drawn from the winning bucket, shown to the peers and the participant, and then returned to the
bucket. One marble was privately shown to the first peer, and then that peer publicly guessed the
winning bucket. Then, another marble was drawn and shown to the second peer, who made an
identical guess. Finally, a marble was shown to the participant. (Prior research and our own pilot
????????????????????????????????????????????????????????????????????????????????????????????????
anchoring on their private observations.)
The color of that marble always contradicted the information conveyed through the peer choices
(Table S2). But given the contents of the buckets and the number of peers, each participant should
have ?????????????????????????????????????????????????????????????.
Round ????????????????????
that the correct
choice is Bucket?
Private information
hints that the correct
choice is Bucket?
The correct
choice is
Bucket?
????????
1 A B A Baseline, Information
Provision, Experiential
Recognition
2 B A B Experiential
Recognition
3 B A B Experiential
Recognition
Table S2: The p????????????, ????????????????????????????????????????????????????????????????????????
S2
A?????????????????????????????????????????????????????????????????????????????????? observes a
blue one (with return), then the probability of Bucket A being the winner are 81.82%. Thus, to the
?????????????????????????????????????????????????????????????????????????????have chosen as they did.
Next, we calculate the odds that one bucket (e.g., Bucket A) is the winner and not the other bucket
(Bucket B) using the three observations (3 obs.) that each participant received: Their own, and one
from each of the two peers.
Pr (Bucket A = Winner | 3 obs.) = Pr (3 obs. | Bucket A = Winner) /
[ Pr (3 obs. | Bucket A = Winner) + Pr (3 obs. | Bucket B = Winner) ]
Therefore:
Pr (Bucket A = Winner | 3 obs.) = (0.144 / (0.144+0.032)) = 9/11 = 81.82%
The probably that the other Bucket B is the winner can be likewise calculated:
Pr (Bucket B = Winner | 3 obs.) = Pr (3 obs. | Bucket B = Winner) /
[ Pr (3 obs. | Bucket A = Winner) + Pr (3 obs. | Bucket B = Winner) ]
Therefore:
Pr (Bucket B = Winner | 3 obs.) = (0.032 / (0.144+0.032)) = 2/11 = 18.18%
The Selection of Peer Names: Considerations of Race, SES, and Gender
One challenge to using name-based instruments is that Black and White Americans not only tend to
possess racially distinct names, but also differ in their average socioeconomic status (SES) (1). So,
????????????????????????????????????????????????????????????????????????????????????????????????????
Blacks. At one hypothetical extreme, participants may be completely blind to race but discriminate
against people of low SES (2). We addressed this risk in several ways.
Social scientists (3-5) and legal scholars (6) have argued that race cannot be neatly disentangled from
other characteristics. That ?????????names, races, and SES are correlated is a reality in our society as
in many others. A research instrument should reflect this reality ? without exacerbating it. Such
magnification could occur, for instance, if a researcher uses Whites names that are associated with
very high SES and Black names associated with very low SES. Thus, in selecting which names to
use, we sought those that are racially distinct (i.e., provide an unambiguous racial cue), but not
extreme in their connotations of SES. In other words, as in prior research, we sought names that did
not exaggerate the racial SES differences that are presently occurring in American society (2, 7, 8).
Specifically, we followed prior research in seeking names that were racially distinct yet associated
with lower SES within their gender and racial group. We considered not only the objective racial
affiliation of a name, but also its perception by others (9). To compose a list of prospective names,
we reviewed evidence from the US Census and birth certificates and examined websites
recommending newborn names by racial groups. Then, we compared the list of prospective names
to three lists used in prior research. Two that relied on objective data on racial affiliation (2, 8) and
one that relied on a survey experiment to measure racialized perceptions of names (7). For each
name, we assessed the objective distinctiveness of racial affiliation (more racially distinct names were
preferred), the subjective perception of the name (names with clearer racial associations were
S3
preferred), and SES status (which should not be exaggerated beyond the existing difference in
present American society). After careful consideration, we selected four names that were in wide
consensus across the lists.
Name Racial Affiliation Racial Perception SES
Jermaine 89.45% Black
(8)
95% Black
(7)
Below median
(8)
Darnell 93.43% Black
(8)
75% Black
(7)
Below median
(8)
Matthew 83.97% White
(8)
95% White
(7)
Below median
(8)
Jay 99.99% White (2)
75% White (7) Below average (2)
Table S3: The names used in the studies, their racial affiliation, perceived race, and socioeconomic
status (SES). As recommended (2, 8), SES is measured as the average or median fraction of mothers
that have at least completed high school for the set of names listed in that gender-race group. As for
the name Jay, there are fewer than five births of Black babies bearing this name in the dataset
provided by Bertrand and Mullainathan (2).
We elected to use only male names for several reasons: One, there are non-obvious interactions
between race and gender because educational attainment differs across both (10). ???????????
???????????????????????????????????????????????????????????????????????????????????????????????????????
or her actions. Two, prior research has argued ????????????????????????????????????????????????????
so ??????names are expected to produce the strongest effects (11, 12). Three and relatedly: Female
names are weaker signals of race (7). Finally, including female names would require doubling the
already-large sample as we would have to control for both racial and gender effects. This task is left
for future research.
Measures of Cognitive Ability
Cognitive ability was assessed through an incentivized and compound measure of the cognitive
reflection test (CRT), a ?????????????????????????????????????????, which is well-established in
psychology and economics. This measure is composed of the original items (13) plus recent
refinements and extensions (14, 15).
In all its variations, CRT presents problems that seem to have intuitive ? but incorrect ?answers.
The test measures the extent to which one relies on simple heuristics, stemming from the cognitive
process known as System 1, which offers quick decisions with little conscious deliberation, versus
System 2, the more attentive and deliberative faculty (16-19). In addition to its theoretical value, the
test possesses a key practical feature: The responses to its few questions have been shown to be
highly predictive of more burdensome measures, such as SAT score (and its mathematical and
verbal subcomponents), ACT score, and the Wonderlic Personnel Test. It requires just a few
minutes yet offers predictive power that equals or exceeds those of much longer tests. In tasks of
S4
choice under uncertainty, CRT has been shown to be the best or second-best predictor of behavior,
and the only one that is related to all the decision-making domains tested (13).
In the Information Provision condition, we provided the participants with their true grades in the
test, together with the grades of their peers, which were invariably set at 100% for one peer and 75%
for the other, regardless of peer race.
Some Benefits and Drawbacks of Online Experiments
We turned to online experiments to alleviate a common concern: Findings obtained with student
participants may not generalize (20), for instance because students are more compliant and
cognizant (21). An online laboratory eases the task of collecting large and heterogenous samples and
allow examining actual behavior with real monetary incentives. Such methods have been used
extensively for economic, psychological, and management research (e.g., 22, 23-25).
Yet online experiments they are not free from risks. Through experimental design, we addressed
some potential drawbacks:
1. Concerns about participant dishonesty (26) were alleviated by examining actual behavior
side-by-side with self-reported opinions.
2. We addressed the risk of participants who are inattentive or overly experienced (27, 28) by
including a rigorous comprehension test and ejecting participants who failed it (detailed
below). Random assignment to conditions mitigated the effect of prior experience.
3. Some worry that online studies underestimate effect sizes (27). This may be particularly true
in this study: Research shows that, compared to face-to-face interaction, computer-mediated
communication shows less intergroup bias (29) and less consideration of irrelevant cues,
such as race (30). However, this is a cautious bias ? the results we present may be
exacerbated in face-to-face interaction.
Racial Attention Deficit over Time
To assess whether the deficit has changed over time, perhaps due to societal and political events, we
turned to data collected in 2017 using a similar method and sample (N=439). We find that that the
likelihood of attending to Black peers is statistically indistinguishable between the two samples.
Year
Condition
2017 2020
Baseline 48.28% 51.42%
Information Provision 58.21% 58.63%
Experiential Recognition 70.83% 71.19%
Table S4. The likelihood that participants attend to Black peers, by experimental condition and
year.
Mitigating Contamination of the Participant Pool
We have taken several steps to reduce the risk of contamination through the transmission of study
information between participants:
1. The research service keeps participants anonymous, and they have no way of communicating
with each other.
S5
2. We recorded participants? identification numbers and prevented them from participating
more than once.
3. Participants were recruited from the same pool using the same recruitment message and the
same level of compensation.
4. Further, we monitored websites and mailing lists that workers are known to frequent,
scanning for mentions of our study. We found none.
S6
Assessment of Peer Skill: Box and Contour Plots
As recommended (31, 32), we graphed the raw data to complement the summaries reported in the main text.
Fig. S1. Assessment of peer skill, by condition and race (n=1,449). Violin curves of equal area showing the distribution of responses across
the six experimental conditions.
S7
Fig. S2. Assessment of peer skill, by condition and race (n=1,449). Box plots comparing the six experimental conditions, showing
maximum and minimum as well as 25%, 50%, and 75% percentiles. In the Baseline ? White condition, the 25% and 50% lines are
overlapping. Outliers are omitted.