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Implicit Racial Biases in Preschool Children and Adults From Asia and Africa

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This research used an Implicit Racial Bias Test to investigate implicit racial biases among 3- to 5-year-olds and adult participants in China (N = 213) and Cameroon (N = 257). In both cultures, participants displayed high levels of racial biases that remained stable between 3 and 5 years of age. Unlike adults, young children's implicit racial biases were unaffected by the social status of the other-race groups. Also, unlike adults, young children displayed overt explicit racial biases, and these biases were dissociated from their implicit biases. The results provide strong evidence for the early emergence of implicit racial biases and point to the need to reduce them in early childhood.
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Implicit Racial Biases in Preschool Children and Adults From
Asia and Africa
Miao K. Qian
Hangzhou Normal University and University of Toronto
Gail D. Heyman
University of California,
San Diego and Zhejiang Normal University
Paul C. Quinn
University of Delaware
Francoise A. Messi
University of Yaound
eI
Genyue Fu
Hangzhou Normal University
Kang Lee
University of Toronto and University of California,
San Diego and Zhejiang Normal University
This research used an Implicit Racial Bias Test to investigate implicit racial biases among 3- to 5-year-olds and
adult participants in China (N=213) and Cameroon (N=257). In both cultures, participants displayed high
levels of racial biases that remained stable between 3 and 5 years of age. Unlike adults, young childrens
implicit racial biases were unaffected by the social status of the other-race groups. Also, unlike adults, young
children displayed overt explicit racial biases, and these biases were dissociated from their implicit biases. The
results provide strong evidence for the early emergence of implicit racial biases and point to the need to
reduce them in early childhood.
Extensive research has investigated racial biases in
adults (Baron & Banaji, 2006; Dunham, Baron, &
Banaji, 2006, 2007; Dunham, Chen, & Banaji, 2013;
Nosek, Banaji, & Greenwald, 2002; Nosek, Haw-
kins, & Frazier, 2011). This research has revealed
that many adults, though not displaying overt
racial prejudices, nonetheless show robust implicit
racial biases. When left unchecked, these biases can
have serious negative consequences at both individ-
ual and societal levels (Greenwald, Poehlman, Uhl-
mann, & Banaji, 2009; Hardin & Banaji, 2013;
Williams, Neighbors, & Jackson, 2003; see Pascoe &
Smart Richman, 2009, for a review). For example,
there are serious consequences for the justice sys-
tem, for equity of educational opportunities, and
for public health (Green et al., 2007).
At what point in development do implicit racial
biases rst emerge? Almost all the research on this
topic has focused on individuals over 6 years of
age. This work has demonstrated that implicit racial
biases are robust starting at this age (Baron &
Banaji, 2006; Dunham, Newheiser, Hoosain, Merrill,
& Olson, 2014; Dunham et al., 2006, 2007; Rutland,
Cameron, Milne, & McGeorge, 2005). Moreover, the
limited research that has been done on younger
children suggests that these biases may emerge at
an age substantially earlier than 6 years (Anzures,
Quinn, Pascalis, Slater, & Lee, 2013; Dunham et al.,
2013; Quinn et al., 2013; Xiao et al., 2015). For
example, infants as young as 3 months prefer to
look at own-race faces over other-race faces
(Anzures et al., 2013). Dunham et al. (2013) and
Xiao et al. (2015) found that preschoolers catego-
rized racially ambiguous faces with a happy expres-
sion as own race and the same faces with an angry
expression as other race. However, it is entirely
unclear whether children younger than 6 years of
This research is supported by grants from the National Insti-
tutes of Health (R01 HD046526), the Natural Science and Engi-
neering Research Council of Canada, and the National Science
Foundation of China (31371041 and 31470993).
Correspondence concerning this article should be addressed to
Kang Lee, Dr. Eric Jackman Institute of Child Study, University of
Toronto, 45 Walmer Road, Toronto, ON, Canada M5R 2X2 or Gen-
yue Fu, Department of Psychology, Hangzhou Normal University.
No. 58 Haishu Road, Hangzhou, 311121 PR China. Electronic mail
may be sent to fugy@zjnu.cn or kang.lee@utoronto.ca.
©2015 The Authors
Child Development ©2015 Society for Research in Child Development, Inc.
All rights reserved. 0009-3920/2015/xxxx-xxxx
DOI: 10.1111/cdev.12442
Child Development, xxxx 2015, Volume 00, Number 0, Pages 112
age, like older children, have implicit racial biases
whereby they would associate positive attributes
with own-race faces and negative attributes with
other-race faces.
Documenting whether or not implicit racial
biases are in place before 6 years of age is impor-
tant because the preschool period is formative in
the development of intergroup attitudes (Bigler &
Liben, 2007). Additionally, attempts at reducing
racial biases in older children are often ineffective
(Aboud, 2013; Bigler, 2013) and may be more effec-
tive and longer lasting if they are implemented ear-
lier rather than later in childhood (Killen, Rutland,
& Ruck, 2011; Xiao et al., 2015).
The primary goal of this study was to examine
implicit racial biases among children from 3 to
5 years of age using a new measure, which we refer
to as the Implicit Racial Bias Test (IRBT). This test is
based the principles of the Implicit Association Test
(IAT). The IAT assesses how quickly positive and
negative attributes are associated with own versus
other races (Greenwald, McGhee, & Schwartz, 1998;
Greenwald, Nosek, & Banaji, 2003). The IRBT also
measures positive and negative associations with
own- versus other races, but does so by directly
looking at associations between faces of different
races and positive versus negative attributes that are
represented by smiling or frowning faces. The logic
is that if participants differ in their response times to
smiles versus frowns for different races, then this
outcome provides evidence of bias. The primary
advantage of this method over the IAT for young
children is reduced cognitive demand. This is
because children only have to learn one set of associ-
ations at a time and can respond with intuitively
labeled buttons on a touch screen (Figure 1). In
addition, our inclusion of only pictorial stimuli elim-
inated the need for participants to read any of the
test materials (Cvencek, Greenwald, & Meltzoff,
2011; Cvencek, Meltzoff, & Greenwald, 2011; Tho-
mas, Burton Smith, & Ball, 2007). The adaptations
are similar to what other researchers have done to
examine other kinds of implicit association in young
children, such as the association between gender
and mathematics (Cvencek, Meltzoff, et al., 2011)
and between positive words and thin body shape
(Thomas et al., 2007).
A second major goal of the present research was
to examine how implicit racial biases change over
the course of early development and how they
compare to adult levels. To date, the evidence sug-
gests that implicit biases are stable after 6 years of
age (Baron, 2015; Baron & Banaji, 2006). However,
it is unclear whether before 6 years of age, chil-
drens implicit racial biases might also be stable or
show age-related change (see Baron, 2015, for
detailed discussion).
A third major goal of our study was to investi-
gate whether the implicit racial biases of 3- to 5-
year-olds were related to their explicit racial biases.
In the existing adult literature, there has been
debate about whether the two types of biases are
dissociated. Some researchers have argued for a
linkage between them based on ndings of a mod-
erate correlation between explicit and implicit atti-
tude measures generally (Cunningham, Preacher, &
Banaji, 2001; Hofmann, Gawronski, Gschwendner,
Le, & Schmitt, 2005). In contrast, others have sug-
gested that implicit racial biases are dissociated
with explicit racial biases due to the fact that adults
may suppress explicit racial biases because their
overt expression is not socially desirable (Green-
wald et al., 1998; Greenwald et al., 2003; Rutland
et al., 2005). This suggestion is additionally consis-
Figure 1. Childs view of the screen for the ChineseBlack Implicit Racial Bias Test. Participants responded by tapping a smile or a
frown logo, and the only stimuli they were asked to respond to were Chinese faces or Black faces. On congruentpairings, partici-
pants were told to touch a smile when they saw an own-race Chinese face and to touch a frown when they saw an other-race Black
face. On incongruentpairings, they were told to touch a frown when they saw a Chinese face and to touch a smile when they saw a
Black face.
2 Qian et al.
p=.150, likely due to the relatively greater variabil-
ity among this age group relative to the older ones.
We conducted a 4 (age groups: 3-, 4-, 5-year-old,
and adult) 92 (race: ChineseBlack vs. Chinese
White) analysis of variance (ANOVA) and found a
main effect of race, F(1, 195) =16.18, p<.001, par-
tial g
2
=.08, and a main effect of age group, F(3,
195) =2.84, p=.04, partial g
2
=.04. Also, we found
an interaction between race and age group, F(3,
195) =5.65, p=.001, partial g
2
=.08. Post hoc test-
ing (least signicant difference test [LSD]) revealed
that this signicant interaction was due to the fact
that children did not show a signicant difference
in their implicit racial biases against Blacks and
Whites, but adults had a signicantly greater bias
against Blacks than Whites.
These results provide evidence that Chinese chil-
dren have implicit racial biases in favor of their
own race starting at as early as 3 years of age and
that this pattern differed from that observed in
adults, who exhibited a bias against Blacks but not
against Whites. One likely explanation for the dif-
ferent patterns we observed in young children ver-
sus adults is that adults show patterns of bias that
reect the effects of social status. This explanation
is especially plausible in light of evidence that
social status has a well-documented inuence on
implicit racial biases (Axt, Ebersole, & Nosek, 2014;
Baron, 2015). In order to conrm that there were
indeed perceived social status differences in the
population, we conducted a new study with a new
group of participants that included only Chinese
adults. Participants were given two questionnaires
we developed to measure the perceived relative
social status of Whites, Chinese, and Blacks. The
results of both the questionnaires showed that Chi-
nese participants tended to perceive Whites to have
higher status than Chinese and Blacks, and Chinese
to have higher status than Blacks (all ts>3.36 and
ps<.01; see online Appendix S1 for details).
Explicit Racial Biases
Childrens choice of the own-race adult over the
other-race adult was coded as 1, and their choice of
the other-race adult over the own-race adult was
coded as 0 for each of the three scenarios in each
condition. The scores were added up and divided
by 3 to derive a proportion score with .50 as the
no-bias score. Thus, for each participant, we
obtained an explicit bias score against Blacks and
an explicit bias score against Whites.
Means and standard errors of the explicit pro-
portional bias score for Chinese over Blacks are pre-
sented in Figure 3. We performed one-sample t
tests to compare each age groups mean explicit
score against .5 (no bias) and found that all child
groups (all ts>2.871, ps<.01), but not adults,
showed explicit racial biases against Blacks and
Whites.
We conducted a 4 (age groups: 3-, 4-, 5-year-old,
and adult) 92 (race: ChineseBlack vs. Chinese
White) ANOVA and found a main effect of age
group, F(3, 195) =16.01, p<.001, partial g
2
=.20.
Post hoc testing (LSD) showed no signicant differ-
ence among 3-, 4-, and 5-year-olds, but did show a
signicant difference between these age groups and
the adult group (ps<.001).
We also compared implicit and explicit attitudes
using correlation analysis (see Baron & Banaji,
2006). We combined data from the three child age
groups to examine the correlation between implicit
and explicit racial biases with partial correlation
analyses controlling for age and found no signi-
Figure 2. Implicit race attitudes of the four age groups in Study
1. A positive value of Dindicates a preference for Chinese rela-
tive to Black or White. Error bars represent standard errors. The
no-bias score is zero.
Figure 3. Explicit race preference for the four age groups in Study
1. Error bars represent standard errors. The no-bias score is .50.
Implicit Racial Biases 5
beards, glasses, or facial makeup. Furthermore, the
faces were chosen according to the results of a rat-
ing experiment in which all faces in the database
were rated in terms of attractiveness and distinc-
tiveness by Caucasian and Chinese adults who did
not participate in the current study. We only
selected the faces that were judged similarly by
Caucasian and Chinese adults, and that were
judged by the two groups to be in the average
range on these dimensions. All faces were overlaid
with the same elliptical shape so that hair was not
visible.
Procedure
Children were tested individually in a quiet
room at their school with the child seated within
comfortable reach of the laptop computer. Partici-
pants received verbal instructions in age-appropri-
ate language. Adults were tested in the same
manner as children.
Implicit racial bias measure. Participants were
assessed for their racial attitudes toward either
Blackor White,as a between-subject factor. In
the ChineseBlack IRBT, there were 8 practice trials
and 40 test trials for each of the congruent and
incongruent pairings, allowing for familiarization
with the procedure. On congruenttrials, partici-
pants were told to touch the smile when they saw a
Chinese face and to touch the frown when they
saw a Black face, while for incongruenttrials,
they were told to touch the frown when they saw a
Chinese face and to touch the smile when they saw
a Black face. The ChineseWhite IRBT was identical
to the ChineseBlack IRBT except that the White
faces were used in place of the Black faces. Partici-
pants were told to touch the frown when they saw
a White face on the congruent trials, and the smile
when they saw a White face on the incongruent tri-
als.
Explicit racial bias measure. In this task, two sets
of three brief scenarios were read to children. In the
ChineseBlack set, children were asked to choose
either an own-race Chinese adult or an other-race
Black adult to be their summer camp counselor in
Scenario 1, a swimming coach in Scenario 2, and a
tour guide in Scenario 3. For example, in the swim-
ming story they were told, This summer, your
mother will take you to a swimming class. In the
class, you could choose one person to coach you to
swim, which one would you like to choose?These
particular examples were selected to be culturally
appropriate for Chinese children. For each scenario,
a photo of a Chinese adult was paired with that of
a Black adult. Photos of different adult pairs were
used for the three scenarios. For each scenario, chil-
dren had to choose either the own-race or the
other-race adult. In the ChineseWhite set, the sce-
narios were the same except that the photos of Chi-
nese adult faces were paired with those of White
adult faces. All faces were novel and children had
not seen them previously.
The implicit measures were always presented
rst because these were of greatest theoretical inter-
est and because prior research suggests that there
are no order effects on these measures (Nosek,
Greenwald, & Banaji, 2007).
Results and Discussion
Implicit Racial Biases
We used the conventional Dscores to indicate
whether children and adults showed a systematic
implicit bias against other-race faces (Black and
White) and for own-race faces. The Dscore is the
difference between the average of response latencies
between contrasted conditions divided by the stan-
dard deviation of response latencies across the con-
ditions (Greenwald et al., 2003). Consistent with
procedures from previous IAT studies with adults
(Greenwald et al., 2003) and children (Cvencek,
Greenwald, et al., 2011), data were excluded from
participants on the basis of three criteria: (a) 10%
of responses faster than 300 ms, (b) error rate of
35%, or (c) average response latency 3 SD above
the mean response latency for the whole sample. In
accord with Greenwald et al. (1998), practice trials
were excluded, as were response latencies above
10,000 ms. These criteria excluded 10 (7.2%) chil-
dren due to excessive errors, leaving 129 children
and 74 adults for analysis.
Preliminary analyses revealed no differences in
overall latencies as a function of participant gender
or order of trial types (congruent rst or incongru-
ent rst); thus, the data were combined on these
two factors in subsequent analyses.
The mean Dscores and standard errors for dif-
ferent age groups in the ChineseBlack IRBT and
ChineseWhite IRBT are shown in Figure 2. We
performed one-sample ttests to compare each age
groups mean Dscore against zero (no bias). This
analysis revealed that all four age groups showed
reliable implicit racial biases against Blacks, all
ts>4.306 and ps<.001, and that 4- and 5-year-olds
showed signicant implicit racial biases against
Whites, all ts>4.634 and ps<.001. The biases of 3-
year-olds against Whites were not signicant,
4 Qian et al.
p=.150, likely due to the relatively greater variabil-
ity among this age group relative to the older ones.
We conducted a 4 (age groups: 3-, 4-, 5-year-old,
and adult) 92 (race: ChineseBlack vs. Chinese
White) analysis of variance (ANOVA) and found a
main effect of race, F(1, 195) =16.18, p<.001, par-
tial g
2
=.08, and a main effect of age group, F(3,
195) =2.84, p=.04, partial g
2
=.04. Also, we found
an interaction between race and age group, F(3,
195) =5.65, p=.001, partial g
2
=.08. Post hoc test-
ing (least signicant difference test [LSD]) revealed
that this signicant interaction was due to the fact
that children did not show a signicant difference
in their implicit racial biases against Blacks and
Whites, but adults had a signicantly greater bias
against Blacks than Whites.
These results provide evidence that Chinese chil-
dren have implicit racial biases in favor of their
own race starting at as early as 3 years of age and
that this pattern differed from that observed in
adults, who exhibited a bias against Blacks but not
against Whites. One likely explanation for the dif-
ferent patterns we observed in young children ver-
sus adults is that adults show patterns of bias that
reect the effects of social status. This explanation
is especially plausible in light of evidence that
social status has a well-documented inuence on
implicit racial biases (Axt, Ebersole, & Nosek, 2014;
Baron, 2015). In order to conrm that there were
indeed perceived social status differences in the
population, we conducted a new study with a new
group of participants that included only Chinese
adults. Participants were given two questionnaires
we developed to measure the perceived relative
social status of Whites, Chinese, and Blacks. The
results of both the questionnaires showed that Chi-
nese participants tended to perceive Whites to have
higher status than Chinese and Blacks, and Chinese
to have higher status than Blacks (all ts>3.36 and
ps<.01; see online Appendix S1 for details).
Explicit Racial Biases
Childrens choice of the own-race adult over the
other-race adult was coded as 1, and their choice of
the other-race adult over the own-race adult was
coded as 0 for each of the three scenarios in each
condition. The scores were added up and divided
by 3 to derive a proportion score with .50 as the
no-bias score. Thus, for each participant, we
obtained an explicit bias score against Blacks and
an explicit bias score against Whites.
Means and standard errors of the explicit pro-
portional bias score for Chinese over Blacks are pre-
sented in Figure 3. We performed one-sample t
tests to compare each age groups mean explicit
score against .5 (no bias) and found that all child
groups (all ts>2.871, ps<.01), but not adults,
showed explicit racial biases against Blacks and
Whites.
We conducted a 4 (age groups: 3-, 4-, 5-year-old,
and adult) 92 (race: ChineseBlack vs. Chinese
White) ANOVA and found a main effect of age
group, F(3, 195) =16.01, p<.001, partial g
2
=.20.
Post hoc testing (LSD) showed no signicant differ-
ence among 3-, 4-, and 5-year-olds, but did show a
signicant difference between these age groups and
the adult group (ps<.001).
We also compared implicit and explicit attitudes
using correlation analysis (see Baron & Banaji,
2006). We combined data from the three child age
groups to examine the correlation between implicit
and explicit racial biases with partial correlation
analyses controlling for age and found no signi-
Figure 2. Implicit race attitudes of the four age groups in Study
1. A positive value of Dindicates a preference for Chinese rela-
tive to Black or White. Error bars represent standard errors. The
no-bias score is zero.
Figure 3. Explicit race preference for the four age groups in Study
1. Error bars represent standard errors. The no-bias score is .50.
Implicit Racial Biases 5
cant correlation (all ps>.330). We also found no
signicant correlation between implicit and explicit
racial biases in adults (p=.39).
In summary, we examined the implicit and
explicit biases of Chinese children and adults
toward out-groups (Blacks and Whites) and found
evidence of early-emerging implicit and explicit
racial biases against other-race faces by children as
young as 3 years of age. These biases were at sim-
ilar levels for the three child age groups. In con-
trast, whereas Chinese adults displayed a similar
level of anti-Black bias to children in implicit bias,
they showed no implicit bias against Whites, sug-
gesting that adults, but not young children,
showed sensitivity to the differences in social sta-
tus between the two other-race groups. Also, as
found in previous studies with adults, adults did
not display explicit anti-Black or anti-White biases.
Furthermore, as is the case for children older than
6 years of age and adults, the implicit and explicit
racial biases in young children were not related to
each other.
Study 2
In Study 1, we discovered evidence of strong racial
biases in Chinese 3- to 5-year-olds. However, one
possible alternative explanation is that these effects
could be driven by the specic face stimuli chosen.
For example, the Black faces we selected might, for
some reason, be perceived to be negative, whereas
the Chinese faces might be perceived positively. In
Study 2, we sought to cross-validate these nd-
ings by using the exact same face stimuli with
Cameroonian children and adults. We selected par-
ticipants from Cameroon because, as in Study 1, we
were especially interested in the effects of lack of
contact with other races on young childrens racial
biases, and Cameroon is a racially homogeneous
society. In the area of Cameroon where we con-
ducted our testing, children are almost exclusively
exposed to own-race individuals, as was conrmed
by interviews of teachers, administrators, and child
participants.
A second reason why Cameroon is of particular
interest is because it offers an interesting contrast to
South Africa, where previous research on implicit
racial bias has been conducted (Dunham et al.,
2014; Newheiser, Dunham, Merrill, Hoosain, &
Olson, 2014). That work suggested that young
South African children do not have in-group racial
biases. However, the generalizability of this result
to other Blacks in Africa can be questioned because
the effect may be due to exposure to Caucasian
people or to factors associated with the specic his-
torical context of South Africa. Notably, South
Africa had a legacy of apartheid that dominated
from 1948 through 1994. In contrast, Cameroonians
have been in charge of their country for over
50 years.
We used the same paradigm as that used in
Study 1 to assess implicit and explicit racial atti-
tudes of Cameroonian children and adults toward
Chinese and Whites.
Method
Participants
The sample consisted of 257 Cameroonian partic-
ipants (129 males, 128 females). Data were collected
between April 2014 and October 2014. More
detailed information regarding the age distribution
of the participants is provided in Table 2. Children
were recruited from a preschool in Yaound
e, the
political capital city of Cameroon where Blacks
makeup more than 99% of the population. Sixty
percent of the childrens parents belonged to the
middle class, 20% to the higher class, and 20% to
the lower class. As in Study 1, participants never
directly interacted with any individuals from the
out-groups we tested (as established by interviews
of adults in the community and by child participant
reports). Adults were undergraduates at the
University of Yaound
e I in Cameroon. Ninety-ve
percent of the adult participants were from
Yaound
e, and 5% were from Douala, the economic
capital of Cameroon. The ethics review and consent
processes were the same as in Study 1.
Apparatus, Materials, Procedure, and Analyses
The apparatus, materials, procedure, and analy-
ses were the same as in Study 1, except that (a) the
instructions were translated into French; (b) there
were two implicit tasks: the BlackChinese IRBT
and the BlackWhite IRBT; and (c) the same three
Table 2
The Distribution of Cameroonian Participants in Study 2
Age groups N(male) M
age
Age range
3-year-old 62 (30) 3.6 2.94.2
4-year-old 66 (30) 4.5 3.85.3
5-year-old 70 (42) 5.5 5.16.4
Adults 59 (27) 23.1 18.029.9
6 Qian et al.
community studies. American Journal of Public Health,
93, 200208. doi:10.2105/AJPH.93.2.200
Xiao, W. S., Fu, G., Quinn, P. C., Qin, J., Tanaka, J. W.,
Pascalis, O., & Lee, K. (2015). Individuation training
with other-race faces reduces preschoolersimplicit
racial bias: A link between perceptual and social repre-
sentation of faces in children. Developmental Science,18,
655663. doi:10.1111/desc.12241
Supporting Information
Additional supporting information may be found in
the online version of this article at the publishers
website:
Appendix S1. Perceived Social Status Differences
Among Different Races in Chinese Adults
12 Qian et al.
examine the correlation between implicit and expli-
cit racial biases with partial correlation analysis
controlling for age and found no signicant correla-
tion (all ps>.103). We also found no signicant
correlation between implicit and explicit racial
biases in adults (p=.21).
Thus, the results with Cameroonian children repli-
cated those with Chinese 3- to 5-year-olds in Study 1,
suggesting cross-cultural generality of the early
emergence of both implicit and explicit racial biases.
Like the Chinese children in Study 1, the racial biases
of Cameroonian children were unaffected by the
social status of the other-race groups. However,
unlike Cameroonian children, Cameroonian adults
displayed implicit racial biases in favor of the other-
race Chinese faces and White faces, suggesting the
impact of social status on implicit racial biases. Also,
unlike Cameroonian children, Cameroonian adults
showed no overt explicit racial biases against other-
race faces. Furthermore, similar to the ndings of
previous adult studies (Baron & Banaji, 2006; Dun-
ham et al., 2006), the implicit and explicit racial
biases were dissociated with each other in both
Cameroonian children and adults.
General Discussion
In the present research, we examined the following
four hypotheses: (a) the implicit racial bias hypothe-
sis that 3- to 5-year-olds would show implicit racial
biases and that these biases would be different from
adults, (b) the explicit racial bias hypothesis that
3- to 5-year-olds would show explicit racial biases
that would not be present in adults, (c) the social
status hypothesis that only the implicit racial biases
of adults would be affected by the relative social
status of their own- versus other-race groups, and
(d) the implicit and explicit racial bias hypothesis
that implicit racial biases would be correlated with
explicit racial biases in 3- to 5-year-olds, but not
among adults. As described next our results are
consistent with the rst three hypotheses, but not
the nal one.
Consistent with the implicit racial bias hypothesis,
we found robust implicit racial biases against other
races among 3- to 5-years-old children on an IRBT in
which three target race groups (Chinese, Black, and
White) and two participant populations (Chinese
and Cameroonians) were included. These results
extend previous ndings demonstrating implicit
racial bias among Caucasian children 6 years of age
and older (Baron & Banaji, 2006; Dunham et al.,
2006, 2013; Newheiser & Olson, 2012). No age differ-
ences were found in the implicit biases between 3-,
4-, and 5-year-olds. Given our evidence of robust and
stable implicit racial biases between 3 and 5 years of
age, we speculate that such biases may emerge in
toddlerhood or even earlier.
Consistent with the explicit racial bias hypothe-
sis, the present study revealed that 3- to 5-year-olds
in China and Cameroon had strong biases against
other-race groups. As was the case with their impli-
cit racial biases, there were no signicant age effects
over this period. Our ndings contrast with the pat-
tern observed in children older than 6 years of age,
whose explicit biases underwent a steady decline
with increased age (Baron & Banaji, 2006; Castelli,
De Amicis, & Sherman, 2007; Dunham et al., 2006;
Rutland et al., 2005; see Raabe & Beelmann, 2011,
for a meta-analysis). Consistent with prior work on
adult explicit bias Baron & Banaji, 2006; Dunham
et al., 2006; Dunham et al., 2013; Rutland et al.,
2005; see Raabe & Beelmann, 2011, for a meta-anal-
ysis), we found that adults did not show explicit
racial biases.
Consistent with the social status hypothesis, we
found that young childrens implicit racial biases
were insensitive to relative social status, but that
adult implicit racial biases were sensitive to relative
social status. This nding contrasts with the appar-
ent sensitivity to the social status of other races
observed in children older than 6 years of age
(Dunham et al., 2006; Dunham et al., 2013;
Dunham et al., 2014; Newheiser & Olson, 2012;
Newheiser et al., 2014; Shutts, Kinzler, Katz,
Tredoux, & Spelke, 2011). For example, in Japan,
childrens implicit racial bias against Caucasians
declined with age but their bias against Africans
remained robust and persistent (Dunham et al.,
2006). One possibility is that the 3- to 5-year-olds in
our experiments might have insufcient knowledge
Figure 5. Explicit race preference in the four age groups in Study
2. Error bars represent standard errors. The no-bias score is .50.
8 Qian et al.
about social status differences between their own-
race group and the other-race groups. In contrast,
adults clearly have such knowledge, as was evident
from the results of our social status questionnaires,
and these patterns were consistent with their impli-
cit biases. For example, in China, Chinese adults
perceived Whites to have higher social status than
both Chinese and Blacks, and Chinese to have
greater social status than Blacks. Their implicit
biases matched such social status differences, with
implicit racial biases in evidence against Blacks, but
not Whites. In contrast, Cameroonian adults per-
ceived Whites to have higher social status than both
Chinese and Blacks, and Chinese to have higher
social status than Blacks. The implicit racial biases
of Cameroonian adults also reected the social sta-
tus differences among the three racial groups; there
was positive implicit racial bias for both Whites
and Chinese against own race.
Taken together with previous ndings (Baron,
2015; Dunham et al., 2013; for a review, see Dun-
ham, Baron, & Banaji, 2008), our research suggests
that while implicit racial biases have an early devel-
opmental emergence, such biases may not be sensi-
tive to the social status of different racial groups
until later in development, perhaps resulting from
childrens increased exposure to the world beyond
their own culture via formal schooling and informal
learning (e.g., reading). It is also possible that the
timing of status effects may emerge earlier in soci-
eties in which status differences between groups
are highly salient as they are in South Africa (see
Olson, Shutts, Kinzler, & Weisman, 2012, for evi-
dence that South African children as young as
3 years of age may perceive Caucasians to have
higher social status than Blacks). Future research is
needed to directly study the relation between chil-
drens recognition of social status and the develop-
ment of implicit racial biases, as well as other
factors such as exposure to the media and class-
room curricula that might help explain differences
between patterns of bias observed in young chil-
dren versus adults. It will also be important to
assess whether the results from our college adults
generalize to other adults (e.g., parents).
Although we found strong implicit and explicit
racial biases among 3- to 5-year-old children in China
and Cameroon, we did not nd evidence supporting
the implicit and explicit racial bias hypothesis.
Specically, we found no evidence that the two
biases were signicantly related to each other in
either study. This lack of relation is consistent with
prior studies with children older than 6 years of age
(Augoustinos & Rosewarne, 2001; Dunham et al.,
2006; McConnell & Leibold, 2001; McGlothlin et al.,
2005). One possible interpretation of the lack of cor-
relation between implicit and explicit biases in older
children and adults is that once children are aware of
the social desirability of appearing racially unbiased,
they suppress the expression of their biases (Green-
wald et al., 1998; Greenwald et al., 2003; Rutland
et al., 2005). However, this explanation is very un-
likely to explain the lack of correlation between these
measures in children in the present study given that
they displayed strong negative biases against other
races both implicitly and explicitly. This observation
raises the possibility that different kinds of social
experience may affect the formation of the two forms
of racial bias differently. For example, implicit racial
biases may be inuenced more by childrens direct
perceptual experiences (Xiao et al., 2015), whereas
explicit racial biases may be more inuenced by
socialization processes (e.g., Adult 9Child interac-
tion, or peer interaction).
Collectively, our ndings of early implicit and
explicit racial biases run counter to the suggestion
by Allport (1979) that such biases emerge only after
an extended period of socialization. Our ndings
are more consistent with the suggestion by Aboud
(2013) that such biases are strong even in early
childhood. Future research with additional mea-
sures will be needed to understand the extent to
which the patterns we observed here can be
explained in terms of different developmental theo-
ries that have been proposed. For example, it has
been suggested that racial feature saliency (Bigler &
Liben, 2007), asymmetrical exposure to same race
versus other-race faces (Xiao et al., 2015), cognitive
maturity (Aboud, 2013), and self-esteem and in-
group identication (Cvencek, Greenwald & Melt-
zoff, 2013; Nesdale, 1999) may play important roles
in engendering the development of implicit and
explicit biases. Future research may assess children
on these factors along with their implicit and expli-
cit racial biases to test the validity of the predictions
based on these theoretical proposals.
The present research also makes a methodologi-
cal contribution to the study of implicit biases in
young children. In developing the IRBT, we
adapted it in several ways to reduce the cognitive
demands of the procedure. Some of these ways,
such as using pictures rather than words and
reducing the number of trials, have been used in
previous studies (Cvencek, Greenwald, et al., 2011;
Cvencek, Meltzoff, et al., 2011). What is new in
our research is that children could respond on a
touch screen and only have to remember to clas-
sify items associated with the theoretical construct
Implicit Racial Biases 9
of interest (in this case, race), thereby dramatically
reducing the cognitive demands of the task. Fur-
thermore, through the use of this method with
Cameroonian and Chinese 3- to 5-year-olds, we
further validated the effectiveness of our procedure
by showing that the measure of implicit associa-
tions between races and attitudes was not inu-
enced by idiosyncratic characteristics of the face
stimuli chosen: When responding to the same
faces, Cameroonian children showed implicit
biases against Chinese faces over Black faces,
whereas Chinese children showed implicit biases
against Black faces over Chinese faces. The mirror
pattern of response seen in the two races of chil-
dren indicates that 3- to 5-year-olds in our study
were responding to the general racial attributes of
the faces, rather than to individual-specic facial
characteristics (e.g., attractiveness). It will be of
interest in future research to explore other uses of
this methodology in more diverse populations and
to examine how it might be used to assess other
types of implicit biases (e.g., gender biases).
In summary, the present research along with pre-
vious investigations paints a picture of early emerg-
ing implicit racial biases that are robust and present
in diverse cultures. These biases are unrelated to
explicit biases and over time show sensitivity to rel-
ative social status. Our results point to the need to
design early interventions as early as 3 years of age
that can address these biases before they become
reinforced and entrenched.
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Supporting Information
Additional supporting information may be found in
the online version of this article at the publishers
website:
Appendix S1. Perceived Social Status Differences
Among Different Races in Chinese Adults
12 Qian et al.
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... That is, children by the age of 6 (the earliest age at which the IAT can be administered) seem to exhibit the same magnitudes of implicit social group bias as adult samples recruited from the same communities. Other methods capable of eliciting reliable data from younger children confirm the presence of implicit intergroup bias in samples from the North America, East Asia, and Africa already at age 4 (Dunham, Chen & Banaji, 2013; Qian et al., 2016) The features of early emergence and stability over the lifespan seem to characterize implicit attitudes not only among members of dominant groups, such as White Americans, but even among stigmatized groups, such as Black Americans (Dunham et al., 2013). What is more, children already seem to exhibit spontaneous gender biases in their speech patterns even at ages when they are too young to complete an IAT (Charlesworth, Yang, Mann, Kurdi, & Banaji, in press). ...
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... Compared with White adults with the lowest implicit racial biases, those with the highest implicit biases favoring their own race fixated more at the bridge of the nose for Black and White faces when asked to visually examine face images (Hansen et al., 2015). Additionally, both White and Asian adults have been shown to demonstrate biases favoring their own race when measured implicitly, but not always when measured explicitly Dunham et al., 2006;Qian et al., 2016). Such implicit racial biases have also been shown to influence the early stages of face processing -particularly for other-race faces -as evident by event-related potential responses (Anzures & Mildort, 2021;Anzures et al., 2022). ...
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... A fourth, and considerably smaller, set of studies includes those that tackle the two-way intersections of these three features (implicit/explicit, multiple countries, multiple years). For instance, a handful of studies have measured both implicit and explicit attitudes across a small set of countries (e.g., China, Canada, Cameroon), revealing systematic patterns of implicit ingroup preferences across multiple cultures (Qian et al., 2016;Steele et al., 2018). However, such studies include data from only a single moment in time. ...
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... With this task, Baron and Banaji (2006) originally found that White American 6-and 10-year-olds showed faster reaction times when White faces were paired with positive emotions/traits (e.g., happy, good, nice, fun) and Black faces were paired with negative emotions/traits (e.g., mad, yucky, bad, mean), compared to the inverse pairings (see also, Rutland et al., 2005). Strikingly, these implicit associations are stable for White American children as young 3 to 4 years of age (see also, Perszyk et al., 2019;Qian et al., 2016). In another implicit association task, Dunham et al. (2013) found that White American 3-to 14-year-olds were more likely to categorize racially ambiguous faces displaying "anger" as Black, rather than White, highlighting this same learned association with Blackness and negative emotion. ...
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This chapter highlights current research on the problem of prejudice among children, adolescents, and adults. Its manifestations, developmental patterns, health consequences, and solutions are discussed. A substantial body of evidence documents that prejudice persists in myriad forms among children, youth, and adults despite widely accepted norms regarding diversity and equality. Intergroup bias has early roots and children's attitudes are deeply responsive to their social environments. People who are targeted by prejudice are at an elevated risk for a host of mental and physical health challenges for both structural and psychological reasons. Interventions to promote intergroup respect among children and those professionals who work with them are reviewed. There is qualified support for the use of carefully structured intergroup contact, diversity and anti-bias education, cognitive practices, and more general supports for personal and community health. To be most effective, these initiatives need to be coupled with social justice work and implemented by those who themselves appreciate equity and diversity. Parents and professionals who work with children have an opportunity to harness and cultivate their early prosocial leanings before the roots prejudice take hold. Finally, some of the initiatives to challenge prejudice and promote respect backed by psychological research are compatible with supports for public health more broadly.
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The present study examined whether perceptual individuation training with other-race faces could reduce preschool children's implicit racial bias. We used an ‘angry = outgroup’ paradigm to measure Chinese children's implicit racial bias against African individuals before and after training. In Experiment 1, children between 4 and 6 years were presented with angry or happy racially ambiguous faces that were morphed between Chinese and African faces. Initially, Chinese children demonstrated implicit racial bias: they categorized happy racially ambiguous faces as own-race (Chinese) and angry racially ambiguous faces as other-race (African). Then, the children participated in a training session where they learned to individuate African faces. Children's implicit racial bias was significantly reduced after training relative to that before training. Experiment 2 used the same procedure as Experiment 1, except that Chinese children were trained with own-race Chinese faces. These children did not display a significant reduction in implicit racial bias. Our results demonstrate that early implicit racial bias can be reduced by presenting children with other-race face individuation training, and support a linkage between perceptual and social representations of face information in children.
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