Educationism and the irony of meritocracy: Negative attitudes of higher educated people towards the less educated

Abstract

Social psychology has studied ethnic, gender, age, national, and other social groups but has neglected education-based groups. This is surprising given the importance of education in predicting people's life outcomes and social attitudes. We study whether and why people evaluate education-based in-groups and out-groups differently. In contrast with popular views of the higher educated as tolerant and morally enlightened, we find that higher educated participants show education-based intergroup bias: They hold more negative attitudes towards less educated people than towards highly educated people. This is true both on direct measures (Studies 1-2) and on more indirect measures (Studies 3-4). The less educated do not show such education-based intergroup bias. In Studies 5-7 we investigate attributions regarding a range of disadvantaged groups. Less educated people are seen as more responsible and blameworthy for their situation, as compared to poor people or working class people. This shows that the psychological consequences of social inequality are worse when they are framed in terms of education rather than income or occupation. Finally, meritocracy beliefs are related to higher ratings of responsibility and blameworthiness, indicating that the processes we study are related to ideological beliefs. The findings are discussed in light of the role that education plays in the legitimization of social inequality.

Full text

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Educationism and the irony of meritocracy: Negative attitudes of higher
educated people towards the less educated
Toon Kuppens
University of Groningen
Russell Spears
University of Groningen
Antony S. R. Manstead
Cardiff University
Bram Spruyt
Vrije Universiteit Brussel
Matthew J. Easterbrook
University of Sussex
This paper has been accepted for publication in the Journal of Experimental
Social Psychology. Doi: 10.1016/j.jesp.2017.11.001
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Abstract
Social psychology has studied ethnic, gender, age, national, and other social groups
but has neglected education-based groups. This is surprising given the importance of
education in predicting people’s life outcomes and social attitudes. We study whether
and why people evaluate education-based in-groups and out-groups differently. In
contrast with popular views of the higher educated as tolerant and morally
enlightened, we find that higher educated participants show education-based
intergroup bias: They hold more negative attitudes towards less educated people than
towards highly educated people. This is true both on direct measures (Studies 1-2)
and on more indirect measures (Studies 3-4). The less educated do not show such
education-based intergroup bias. In Studies 5-7 we investigate attributions regarding a
range of disadvantaged groups. Less educated people are seen as more responsible
and blameworthy for their situation, as compared to poor people or working class
people. This shows that the psychological consequences of social inequality are worse
when they are framed in terms of education rather than income or occupation. Finally,
meritocracy beliefs are related to higher ratings of responsibility and
blameworthiness, indicating that the processes we study are related to ideological
beliefs. The findings are discussed in light of the role that education plays in the
legitimization of social inequality.
Keywords: educationism, attribution, intergroup bias, education-based groups
Word count: 17468 (without abstract and references)

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Now that people are classified by ability, the gap between the classes has
inevitably become wider. The upper classes are […] no longer weakened by
self-doubt and self-criticism. Today the eminent know that success is just
reward for their own capacity, for their own efforts, and for their own
undeniable achievement. They deserve to belong to a superior class.
–Michael Young, in The rise of the meritocracy (1958), p. 106
Education, education, education
–British Prime Minister Tony Blair, on his three priorities ahead of the 1997
General Election
As Tony Blair pointed out, education matters, and emphasizing this helped to
sweep him to power in his first of three consecutive UK election victories. Why, then,
is education arguably the most important social division that has not been
significantly studied in social psychology? This is all the stranger because the
relation between education and health and social attitudes is at least as strong as for
other demographic characteristics such as gender, ethnicity, or income (Easterbrook,
Kuppens, & Manstead, 2016; Marmot & Wilkinson, 2005). In spite of this, social
psychology textbooks address prejudice based on race, ethnicity, gender, sexual
preference, age, religion, body shape, physical or mental disability, nationality, and
study major (Aronson, Wilson, & Akert, 2013; Hewstone, Stroebe, & Jonas, 2012;
Hogg & Vaughan, 2008), yet education is conspicuous by its absence. The reasons
for this are interesting in themselves; we argue that attitudes to those with few
educational qualifications have become one of the last bastions of ‘acceptable’
prejudice, to the extent that it may not be seen by many as prejudice at all, and that

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these views are shared in important respects by the target group itself. Here we
present the first experimental evidence of education-based intergroup attitudes and in
the process challenge the popular view, supported by previous research, that more
highly educated people are morally enlightened and thus less prejudiced compared to
their less educated counterparts (see also Kuppens, Easterbrook, Spears, & Manstead,
2015; Kuppens & Spears, 2014). We also compare attitudes towards the less
educated with attitudes towards the poor and the working class in order to investigate
what is special about the less educated as a group, and how this might contribute to
the legitimization of social inequality.
The case for studying education-based groups
Why are education-based groups worthy of investigation? First, people’s level
of education matters because educational differences are one of the major divides in
contemporary societies. Education is related to outcomes such as unemployment,
income, health, and well-being (Grusky & DiPrete, 1990; Marmot, Ryff, Bumpass,
Shipley, & Marks, 1997), and also to a wide range of social attitudes such as racism,
lack of trust, and political cynicism, for which it is a more consistent predictor than
income is (Easterbrook et al., 2016). In addition, education is considered to be a
solution for these individual and societal problems (Depaepe & Smeyers, 2008;
Labaree, 2008), demonstrating its perceived importance. The societal importance of
education is perhaps best illustrated by noting that education is the best demographic
predictor of people’s opinion on current political conflicts such as those surrounding
Donald Trump and the Brexit (Goodwin & Heath, 2016).
Second, contrary to the belief that education is a vehicle for social mobility,
opportunities for academic achievement—the gateway to all education’s
advantages—are distributed very unequally. There is a strong relation between social

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background and academic achievement (OECD, 2013), and longitudinal data show
that these effects of social background are not merely due to differences in
intelligence (Bukodi, Erikson, & Goldthorpe, 2014; Bukodi, Goldthorpe, Waller, &
Kuha, 2015; Damian, Su, Shanahan, Trautwein, & Roberts, 2014). In experimental
studies, students taking the role of teachers discriminate against pupils from lower
socio-economic backgrounds (Autin, Batruch, & Butera, 2016) and widespread
normative testing has been shown to increase the SES achievement gap (Smeding,
Darnon, Souchal, Toczek-Capelle, & Butera, 2013). Tertiary education institutions in
the US have also been shown to adopt language and customs that are biased in favor
of the middle (vs. working) classes, causing stress and performance deficits among
first-generation scholars (Stephens, Fryberg, Markus, Johnson, & Covarrubias, 2012;
Stephens, Townsend, Markus, & Phillips, 2012). Clearly, the path to academic
achievement is a high-speed freeway for some but a rocky road for others. Thus,
differences in educational achievement cannot be considered completely fair and the
educational system partly reproduces and legitimizes existing social differences
(Bourdieu & Passeron, 1990). Yet even social psychological theories that are directly
concerned with the justification of inequality, such as System Justification Theory
(Jost & Banaji, 1994), pay scant attention to the role played by educational outcomes.
The combination of the importance of education and the unequal access to
educational opportunities makes the neglect of educational differences in social
psychological research all the more surprising.
Attitudes towards education-based groups. Given that educational
differences are large and at least partly unfair, a central question for social psychology
is how educational differences are subjectively perceived. From the point of view of
the less educated, this amounts to whether this is the basis of stigma (see Kuppens et

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al., 2015). From the point of view of the more highly educated, the question is how
they evaluate and respond to the less educated. Are their attitudes toward educational
groups likely to make things better or worse for the less educated? Large proportions
of the population recognize the unfair situation or treatment of disadvantaged groups
such as the physically disabled, women, and ethnic minorities, and support social
justice via equality legislation. However, we propose that the ideological and
motivational foundations of attitudes about education-based groups are somewhat
different to these other social groups.
Existing research on attitudes toward education-based groups
Perhaps unsurprisingly, students see educated people as very competent but
also quite warm (Fiske, Cuddy, Glick, & Xu, 2002). In a representative sample, and
consistent with the Stereotype Content Model (Cuddy, Fiske, & Glick, 2008), Spruyt
and Kuppens (2015b) found that the higher educated saw themselves as more
competent than the less educated, while the less educated saw themselves as warmer
than the higher educated. Less educated people also rated the conflict between
educational groups to be more important than higher educated people did (Spruyt,
2014; Spruyt & Kuppens, 2015a; Stubager, 2009), which may be an example of a
dominant group downplaying intergroup conflict in order to avoid having to address it
(Jackman, 1994; Livingstone, Sweetman, Bracht, & Haslam, 2015).
To our knowledge, these are the only studies on attitudes toward education-
based groups. One basic question we investigate here is whether education-based
intergroup bias exists, and whether this goes beyond stereotypes of warmth and
competence that are partly based on the social reality of educational qualifications.
Education-based intergroup bias is the topic of Studies 1-4 and we now discuss our
predictions for those studies.

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Education and moral enlightenment
What kind of attitudes should we expect between education-based groups?
There are reasons to expect that the higher educated will show less intergroup bias
than the lower educated. First, in naturally occurring groups, members of low status
groups generally show more intergroup bias than those of high status groups (Mullen,
Brown, & Smith, 1992). This makes sense from the perspective of social identity
theory (Tajfel & Turner, 1979) because members of low status groups need to strive
harder than members of high status groups to achieve a positive identity and social
change (Scheepers, Spears, Doosje, & Manstead, 2006b). Second, higher levels of
education could be expected to promote tolerance, therefore reducing the intergroup
bias displayed by the higher educated. A popular idea is that high levels of education
are related to moral enlightenment and better moral judgment, a notion first
articulated by Stouffer (1955) and Lipset (1959). The reasoning is that people with
higher levels of education have developed a more sophisticated way of thinking, and
an understanding that certain values should be universally applied to all groups. There
is indeed evidence that higher educated people are more tolerant of some minority or
low-status groups (Carvacho et al., 2013; Easterbrook et al., 2016; Wagner & Zick,
1995). According to the moral enlightenment perspective, the tolerant worldview of
the more highly educated is a consequence of their superior moral reasoning
facilitated by education.
However, research has long shown that the effect of education on egalitarian
attitudes often does not translate into support for concrete measures aiming to achieve
greater equality (Jackman & Muha, 1984; Stember, 1961; Weidman, 1975). Yet, the
notion of moral enlightenment still persists. A recent resurrection has come in the
form of two longitudinal studies that presented negative correlations between

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children’s scores on an intelligence test and their level of self-reported prejudice two
decades later, a relation partially mediated by educational qualifications (Deary,
Batty, & Gale, 2008; Schoon, Cheng, Gale, Batty, & Deary, 2010). According to
these authors, the relation between education and tolerance is due to the common
influence of intelligence on both, rather than to the effect of education itself on moral
reasoning. The underlying idea, however, is the same: The higher educated are more
tolerant because of their superior moral reasoning. Based on this research, one could
expect the higher educated to show less education bias than the less educated do.
Moral enlightenment should prevent the higher educated from showing negative
reactions to outgroups, including the less educated.
However, rather than being due to moral enlightenment, the self-reported
tolerance of the higher educated may reflect sophisticated ideological discourses that
ultimately mask the self-interest of the higher educated (Jackman & Crane, 1986;
Jackman & Muha, 1984). For example, the fact that the higher educated defend
principles of tolerance and equality while opposing actual measures that could
achieve equality has been argued to reflect ideological refinement in defense of self-
interest (Jackman & Muha, 1984). Tolerant attitudes appear positive but do not
actually help to change anything about the situation of inequality. Furthermore, this
allows a dominant group to appear friendly and fair without risking the loss of its
advantaged position (Jackman, 1994).
Similar mechanisms could be at play in the attitudes towards the lower
educated. Emphasizing the inherent value of education and being educated could also
be a way to justify and legitimize social inequality and the advantaged position of the
higher educated. In a world where inequality and discrimination based on gender,
race, and class are now less acceptable, emphasizing the meritocracy of education

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may still be an acceptable way to justify one’s high status position. In this way,
stressing the importance of education could be a way to legitimize social differences
(Bourdieu & Passeron, 1990). Following this conflict-based approach, one could
argue that there is no compelling reason why the higher educated would show less
education bias compared to the less educated; indeed, they may even show greater
bias because it justifies their position. Furthermore, a conflict-based approach could
predict that identification enhances education bias because the highly identified are
more invested in the intergroup conflict. Investigating these issues is one of the main
goals of this paper. We also investigate possible reasons behind any education-based
intergroup bias. In particular, we look at the role that attributions of responsibility for
educational achievement play in the legitimization of social inequality.
Education and the legitimization of social inequality
Perceived individual responsibility for educational achievement is likely to be
a key factor affecting how people evaluate economic and social inequality. Given the
strong relation of education to income and unemployment in contemporary societies
(a relation that has become stronger, see Featherman & Hauser, 1976; Grusky &
DiPrete, 1990), the nature of educational differences might contribute to a
meritocratic view of inequality. We take a first step towards addressing these issues
by investigating attributions and emotions towards low-status socio-economic groups
based on education, wealth, and occupation (in Studies 5-7). We borrow from
Weiner’s attribution-emotion model (Weiner, Perry, & Magnusson, 1988) but apply
this to the group level to investigate attributions made about educational groups. This
builds on research on the “ultimate” attribution error, in which groups are seen as
responsible for their own outcomes, which are attributed to internal properties of the
group (Pettigrew, 1979). Specifically, we predict that educational differences will be

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seen as more deserved than income or class differences, and thus high and low
educated groups will be seen as more responsible for their respective outcomes than is
merited (the “ultimate” attribution error), and this will also have consequences for the
emotions felt towards those groups.
Overview of Studies
Studies 1 and 2 use a thermometer measure to assess attitudes to less educated
and highly educated people to test whether education bias is openly expressed.
Studies 3 and 4 investigate whether minimal information about someone’s
educational background affects how others evaluate them. In these studies, we create
short descriptions of people who differ in educational and ethnic background, and ask
participants to evaluate them. Studies 5-7 assess attributions and emotions towards
the lower educated and compare these to other groups low in socio-economic status
(poor, working class), as well as other disadvantaged groups. All studies apart from
Studies 1 and 6 have a socially diverse sample so that we are able to compare the
viewpoints of less and higher educated people. All studies were conducted in
Western societies (UK, US, Belgium, and Netherlands).1 We report all measures,
manipulations, and exclusions in these studies.
Study 1
In Study 1 we used a simple, explicit self-report measure of education bias, a
thermometer measure of attitudes to both more highly and less highly educated
people. In Study 1a participants were UK students, in Study 1b they were Dutch
students, and in Study 1c participants were mostly German students studying in the
Netherlands. Most of these university students will end up with a degree
qualification, but they are strictly speaking not yet part of the group of higher
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1 The data for all studies are available at https://osf.io/v6a8x.

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educated people. This potential limiting is addressed by recruiting an older sample in
Study 2.
Method
Participants. Study 1a. Sixty-six2 people at Cardiff University (62 bachelor
students and 4 recent graduates, about two-thirds from psychology) participated in
this study in exchange for a small payment (48 women, mean age = 21.1, SD = 2.58).
Three people indicated they were not born in the UK but only one of these three
considered themselves to be part of an ethnic minority.
Study 1b. Two hundred and ten3 psychology students at the University of
Groningen participated in this study in return for course credit (151 women, mean age
= 19.3, SD = 1.47). All participants were born in the Netherlands but five indicated
they belonged to an ethnic minority.
Study 1c. Two hundred and seven4 psychology students (mostly Germans) at
the University of Groningen participated in this study in return for course credit (142
women, mean age = 20.2, SD = 1.88). One hundred and forty-six were born in
Germany, fourteen were born in the Netherlands, six were born in the UK, and the
others were born in a variety of European and non-European countries. For the
analyses based on national groups, we only used the 146 German participants.
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2 We did not perform a power analysis but collected as much data as possible prior to
the end of the academic year.
3 The sample size was based on a power calculation for manipulations and measures
that are not reported here, but came after the measures that we analyze here.
4 The sample size was based on a power calculation for manipulations and measures
that are not reported here, but came after the measures that we analyze here.

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Procedure. Participants first indicated their parents’ education level and field
of study. They then evaluated 10 film genres (not analyzed here). Participants
continued with a thermometer measure of feelings towards a series of groups, which
is the dependent variable of interest here. Participants went on to complete further
measures, but these are not relevant here.
Parental education. Categories for the parental education level question in
Study 1a were ‘No qualifications,’ ‘GCSE,’ ‘A-level,’ ‘City and guilds level 4,’
‘Bachelor’s degree,’ ‘Master’s degree,’ and ‘Ph.D.’ Studies 1b and 1c had similar
categories, but adapted to the nationality of the participants. The full lists used in all
three studies can be found in Tables S1-S3 in the supplemental material. We
averaged the two ratings (r = .49 in Study 1a, .52 in Study 1b, and .46 in Study 1c)
into a single measure of parental education.5
Education bias. A series of groups (11 in Study 1a, 9 in Study 1b, and 12 in
Study 1c) were evaluated on a thermometer measure. In Study 1a, the groups
‘British,’ ‘English,’ and ‘Welsh’ were evaluated first, in random order. Then eight
further groups were evaluated, again in random order (‘French,’ ‘Indian,’ ‘Polish,’
‘Muslims,’ ‘old people,’ ‘young people,’ ‘people who go to higher education,’ and
‘people who leave school after their GCSEs’). In Study 1b, ‘Dutch’ were evaluated
first. Then eight further groups were evaluated in random order (‘Belgians,’ ‘French,’
‘Indonesian,’ ‘Polish,’ ‘old people,’ ‘young people,’ ‘lowly educated,’ and ‘highly
educated’). In Study 1c, ‘students,’ ‘Dutch,’ and ‘Germans’ were evaluated first, in
random order. Then nine further groups were evaluated, again in random order
(‘French,’ ‘Indian,’ ‘Polish,’ ‘Muslims,’ ‘old people,’ ‘young people,’ ‘people who
have studied at university,’ and ‘people who drop out from school before getting their
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5 In Study 1c we had information on parents’ education for only 174 participants.

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secondary school diploma’). Participants indicated how warm or cold they generally
felt towards each group, on a scale from 0 to 100.
Results
In Study 1a, higher educated people (M = 78.8, SD = 14.6) were evaluated
more positively than less educated people (M = 59.1, SD = 19.6), t(65) = 8.29, p <
.001, Hedges’ gav = 1.12 , 95%CI [0.85, 1.39]. In Study 1b, highly educated people
(M = 74.25, SD = 14.3) were evaluated more positively than less educated people (M
= 57.58, SD = 16.4), t(65) = 12.91, p < .001, Hedges’ gav = 1.08 , 95%CI [0.91, 1.24].
In Study 1c, higher educated people (M = 70.9, SD = 15.46) were again evaluated
more positively than less educated people (M = 53.05, SD = 21.22, t(206) = 10.84, p <
.001, Hedges’ gav = 0.96, 95%CI [0.78, 1.13].
Figure 1 shows education bias alongside other types of bias. The error bars
represent Cousineau-Morey confidence intervals that allow within-subject
comparisons (Baguley, 2012). Overall, education-based intergroup bias seems similar
in magnitude to intergroup bias based on nationality, and larger than intergroup bias
based on age. We tested whether education bias differed from bias based on ethnic or
national groups. Because we also wanted to be able to present evidence for no
difference between education and ethnicity as a source of bias (i.e., evidence for a null
effect for the interaction), we used Bayesian repeated measures for these analyses.
Each analysis had a 2 (type of group: education versus ethnic/national) by 2 (ingroup
versus outgroup) design. A JASP Bayes factor ANOVA (JASP Team, 2017; Rouder,
Morey, Speckman, & Province, 2012) with default prior scales revealed the Bayes
Factors presented in the last column of Table 1. These are Bayes Factors against the
interaction between type of group and in-group/out-group. The Bayes Factors
therefore indicate how much more likely the data are under the assumption of no

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interaction than under the assumption of an interaction. As is already evident in
Figure 1, results depend on the specific national or ethnic out-group that is being
investigated. In Study 1a there is moderate evidence against an interaction for Indians
and French, but only anecdotal evidence against an interaction for Muslims and
Polish. In Study 1b there is moderate and strong evidence for an interaction in the
cases of French and Polish, respectively. These are the only two instances in Study 1
where there is evidence for an interaction showing stronger national/ethnic bias than
education bias; all other comparisons either favor the null hypothesis of no
interaction, or show stronger education bias. For Belgians and Indonesians, there is
anecdotal and moderate evidence against an interaction. In Study 1c there is
moderate evidence against an interaction for Polish, French, and Muslims. However
there is strong evidence for an interaction when Spanish and British are concerned,
meaning that for Germans education bias was stronger than national intergroup bias
of Germans against Spanish and British people. In sum, out of 14 tests 6 provide
moderate evidence against an interaction, 2 provide evidence that education bias is
stronger than national bias, and 2 provide evidence that national bias is stronger than
education bias. Overall then, education bias seems to be similar in size to
national/ethnic bias.

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Figure 1: Differences between thermometer ratings (Study 1). Error bars are
Cousineau-Morey within-subject 95% CIs for comparisons within one sample.
,
In Studies 1a and 1c, parental education was not related to the evaluation of the
less educated (Study 1a: r = .05, p = .72; Study 1c: r = -.02, p = .81), the evaluation of
the higher educated (Study 1a: r = .12, p = .35; Study 1c: r = .003, p = .97), or a score
reflecting the difference between evaluations of the two educational groups (Study 1a:
r = .04, p = .73; Study 1c: r = .02, p = .81). However, in Study 1b parental education
was positively related to the evaluation of the highly educated (r = .16, p = .02),
negatively related to the evaluation of the lower educated (r = -.13, p = .052), and
positively related to the difference score (r = .24, p < .001). It is unclear why these
relations only show for the Dutch sample and not for the British and German samples.
Further research will have to determine whether the result in Study 1b is a false
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positive, whether the effect is small and differs between studies due to sampling error,
or whether there are reliable differences between countries.
Table 1: Comparison of bias based on different types of social categories (Study 1)
Means
HE
LE
In-
group
Out-
group
Bayes
Factor
against
interact
ion
Study
1a
HE/LE versus British/Indians
78.8
59.1
82.2
62.0
5.494
HE/LE versus British/French
78.8
59.1
82.2
61.6
4.907
HE/LE versus British/Muslims
78.8
59.1
82.2
57.8
2.559
HE/LE versus British/Polish
78.8
59.1
82.2
56.7
1.525
Study
1b
HE/LE versus Dutch/Belgians
74.3
57.6
77.4
64.1
1.558
HE/LE versus Dutch/Polish
74.3
57.6
77.4
47.2
0.000
HE/LE versus Dutch/French
74.3
57.6
77.4
55.4
0.144
HE/LE versus Dutch/Indonesians
74.3
57.6
77.4
58.4
4.396
Study
1c
HE/LE versus German/Polish
69.8
53.1
72.3
57.4
5.715
HE/LE versus German/Muslim
69.8
53.1
72.3
58.1
4.922
HE/LE versus German/Greeks
69.8
53.1
72.3
60.4
1.700
HE/LE versus German/Spanish
69.8
53.1
72.3
65.4
0.014
HE/LE versus German/British
69.8
53.1
72.3
67.8
0.000
HE/LE versus German/French
69.8
53.1
72.3
59.0
3.502
Note. HE=higher educated. LE=less educated.
Discussion
Education bias in explicit, self-reported evaluation of groups is present in
university students: Participants in these studies evaluated highly educated people
more positively than lowly educated people. Across samples of British, Dutch, and
German students, the effect size was large, consistent, and approximately the same
size as bias based on nationality. That education bias is not smaller overall than
ethnic/national bias adds weight to the question of why education bias has not
previously been studied.
In Study 1 we only assessed the attitudes of students, who are destined to
occupy a relatively high rung on the education ladder. However, Study 1 does not

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inform us about education bias among lowly educated people. Study 2 therefore
includes participants from a wider range of educational backgrounds.
Study 2
Method
Participants. 466 Mechanical Turk workers (56.7 % female, Mage = 37.2, SD
= 12.7) completed an online study. Fifteen participants did not disagree with the item
“The word ‘political’ has twenty letters,” and three did not select ‘Strongly disagree’
on the item “Please select ‘Strongly disagree’ to indicate you are paying attention”.
These 18 inattentive participants were excluded, leaving 448 in the sample.
Respondent’s education. Participants were asked to indicate their highest
educational qualification. Responses were recoded into five categories: ‘High school
diploma or less,’ ‘Some college but no degree,’ ‘2-year college degree,’ ‘4-year
college degree,’ and ‘Post-graduate degree.’
Education bias. As in Study 1, a series of groups were evaluated on a
thermometer measure. The focal groups were ‘Lowly educated people (people who
dropped out or stopped studying after high school)’ and ‘Highly educated people
(people with at least a Bachelor’s degree).’ The 14 other groups included Christian
fundamentalists, liberals, the military, Trump supporters, disabled people, and
entrepreneurs. Groups were presented in a random order.
Procedure. The thermometer measures for lowly and highly educated people
were embedded in a larger, unrelated study. Participants first answered items about
whether they were independent thinkers or tended to follow social norms. Depending
on condition, they then completed an 18-item scale about attitudes towards political
correctness and received bogus information about the relation between political
correctness and prejudice, or between political correctness and independent thinking.

!"#$%&'()'*+,,,,,-4,
,
Next, measures of symbolic racism, attitudes towards Muslims, and benevolent
sexism were presented in random order. Then participants filled out all the
thermometer measures, and provided demographic information.
Results
We conducted a mixed ANOVA in which thermometer ratings were modeled
as a function of participant education, group (lowly versus highly educated people,
varied within-subjects), and their interaction. Overall the higher educated (M = 70.7,
SD = 19.7) were evaluated more positively than the less educated (M = 49.7, SD =
25.6), F(1,447) = 204.14, p < .001, ηp2 = .31. This main effect was qualified by an
interaction with participant education, F(4,443) = 6.06, p < .001, ηp2 = .05.
Participants from all education levels made more positive evaluations of the higher
educated than the less educated, but this difference was larger for higher educated
participants (for means and effect sizes split by respondent’s education, see Table 2).
The fact that education bias is stronger among higher educated participants seems
primarily due to their relatively more negative evaluation of the less educated,
compared to less educated participants.
Table 2: Education bias on thermometer ratings, by respondent’s education (Study 2)
Mean thermometer rating
(SD)
Respondent's education
N
Lowly
educated
Highly
educated
Hedges’
gav
p
High school or less
40
62.8 (24.6)
69.2 (19.9)
0.30
.08
Some college, no degree
111
52.9 (26.1)
68.4 (21.8)
0.64
< .001
2-year college degree
48
53.3 (24.9)
68.1 (18.0)
0.67
< .001
4-year college degree
174
43.8 (24.3)
71.6 (19.2)
1.26
< .001

!"#$%&'()'*+,,,,,-5,
,
Post-graduate degree
75
49.2 (25.5)
74.2 (18.3)
1.12
< .001
Discussion
Confirming the results of Study 1, higher educated participants showed strong
education-based intergroup bias on a feeling thermometer measure and evaluated the
higher educated much more positively than the less educated. Less educated
participants, however, did not evaluate their own educational group (i.e., the less
educated) more positively than the out-group (i.e., the higher educated). Indeed, even
participants with only a high school diploma or less tended to evaluate their own
group less positively than the group of higher educated people. In sum, higher
educated participants showed more intergroup bias than did less educated participants,
and this was mainly due to their more negative evaluation of the group of less
educated people. This is a first indication that the supposed moral enlightenment of
the higher educated is not reflected in evaluations of education-based groups.
The thermometer measure used in Studies 1 and 2 is a direct self-report
measure of the evaluation of groups. Such measures are important because they index
attitudes that are openly expressed and that reflect aspects of the current discourse
about education-based groups. However, less direct measures are also important
because they reveal less explicit attitudes and biases that can also feed into behavior.
We therefore used a less direct measure of education bias in Studies 3 and 4. We also
used a measure of identification with education-based groups to investigate whether
high identifiers show more education bias.
Study 3
The goal of Study 3 was to investigate whether minimal information about a
person’s educational background affects how others evaluate that person. We created

!"#$%&'()'*+,,,,,.6,
,
short descriptions of individuals who differed in educational and ethnic background,
and this allowed us to calculate measures of education bias and ethnic bias. For
present purposes ethnic bias serves as a comparison.6
As explained above, the moral enlightenment hypothesis leads one to expect
that higher educated participants would express tolerance towards people with a
different educational background. By contrast, a conflict-based model would predict
that the higher educated show as much education bias as the less educated do, or even
more. In relation to predictions for our measure of ethnic bias, there is a lot of
evidence that less educated people generally hold more negative self-reported
attitudes towards ethnic minorities.
We included a measure of identification with education-based groups and a
between-subjects manipulation of the salience of education. Both high identification
and the salience of people’s educational level could be expected to lead to higher
education bias (especially for the highly educated), because these should make the
education category more relevant (see Kuppens et al., 2015; Spears, Doosje, &
Ellemers, 1999).
Method
This study had a 2 (target education: target individual highly versus lowly
educated) by 2 (target ethnicity: target individual Muslim versus non-Muslim) by 3
(participant education: No secondary school diploma, Secondary school or vocational
higher education diploma, or University degree) by 2 (education salience: education
salient versus not salient) by continuous (identification) design. Target education and
ethnicity were manipulated within participants; the other factors vary between
participants.
,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
6 Other data from this study were reported as Study 2 in Kuppens et al. (2015).

!"#$%&'()'*+,,,,,.-,
,
Participants. Initially 208 participants were recruited through a research
assistant’s social network. Thirty-seven participants who did not provide information
about their educational level or did not answer the identification questions were
excluded from analyses. Three participants who were 15/16 years old and still in
secondary education were also excluded; 168 remained (age M = 24.5, SD = 5.7; 65
male, 97 female, 6 gender unknown). A further 314 participants were recruited
through an online loyalty program (www.maximiles.co.uk); by way of compensation,
they received points that could be exchanged for consumer purchases. Forty
participants who did not provide information about their educational level or did not
answer the identification questions were excluded from analyses. One participant was
excluded because he responded ‘1’ to 42 consecutive questions; 273 participants
remained. Thus in total there were 441 participants (293 female, 129 male, 19 gender
unknown; age M = 32.78; SD = 11.50). Nine further participants were excluded from
analyses because they indicated they were Muslim, leaving 432 participants.
Participants completed an online questionnaire.
Education bias and Muslim bias. As an indirect measure of bias due to
group membership, participants were asked to evaluate four individuals who differed
in education level and ethnicity. We told participants that we were interested in how
people form first impressions on the basis of limited information. We presented four
individuals in a 2 (ethnicity: native British versus Muslim) by 2 (education: less
versus higher educated) within-subjects design. Presentation order of the four
individuals was determined by a balanced Latin square design such that each
individual was presented once in each location (first, second, etc.) and was preceded
by each of the other individuals once. Information not relevant to education or
ethnicity was counterbalanced with the education and ethnicity information, but

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,
presented in a fixed order. For example, the first individual who was presented always
lived in London, had a dog, and played cricket (regardless of education and ethnicity).
Here is an example of a higher educated Muslim individual: “Mohammed Hussain is
25 years old and currently lives in London, where he works as a doctor. He lives in
rented accommodation with a work colleague. People who know him would describe
him as a chatty kind of character. He was born and grew up in Bournemouth, but
moved to London to go to university. This is where he studied medicine and he
continued to reside after completing his degree. Mohammed likes playing cricket on
the weekends and his favourite hobby is walking his dog, which helps him to relax
after a busy day at work.”
For each individual, three questions assessed liking (e.g., “Do you like this
person?”). Two questions assessed similarity (e.g., “Do you feel you are similar to
this person?”) and one final question read “To what extent do you think you could be
friends with this person?”. All these items correlated highly but because liking is
conceptually different from similarity and because the possibility of friendship
depends on both the self and the other, we used the three liking questions as the main
measure of evaluation (α = .91 for Muslim higher educated, .92 for Muslim less
educated, .90 for non-Muslim higher educated, and .90 for non-Muslim less
educated). The similarity items also formed a reliable scale (rs = .76 for Muslim
higher educated, .75 for Muslim less educated, .71 for non-Muslim higher educated,
and .76 for non-Muslim less educated).
Education. Participants were asked to indicate the highest educational level
they had achieved. Responses were recoded into three categories: No secondary
school diploma (n = 97), Secondary school or vocational higher education diploma (n
= 101), and University degree (n = 234). Because we had a young sample and 19.3%

!"#$%&'()'*+,,,,,./,
,
were still in full-time education, we categorized those who were currently students as
holding the degree or certificate for which they were studying.
Identification. Identification was assessed immediately after the question
about participants’ level of education. We used 10 items (α = .91) from Leach et al.’s
(2008) multidimensional identification scale, two items from each subscale (e.g., “I
feel a bond with people who have had the same education as me”).
Education salience. We manipulated the salience of participants’ own
education level by varying the question order. In the ‘education salient’ condition,
questions about their parents’ and their own education (including the identification
question) preceded the dependent variables. In the ‘education not salient’ condition,
these questions followed the dependent variables.
Results
Analytic strategy. We conducted a mixed ANOVA, where liking and
similarity ratings were modeled as a function of the education of the target person, the
ethnicity of the target person, participant education, education salience, and all
interactions. However, because the participant education variable is not balanced
(does not have equal numbers in each category), main effects are estimated without
the interaction term with participant education in the model. Because we estimated
parallel models for similarity and liking, we used a Bonferroni correction by only
considering effects to be statistically significant when the p-value is .025 or smaller.
Education bias, anti-Muslim bias, and education level. As expected, there
was an interaction between the education of the target and participants’ own
education both for similarity, F(2,385) = 25.72, p < .001, ηp2 = .12, and liking,
F(2,386) = 5.38, p = .005, ηp2 = .03. Simple effects indicated that higher educated
participants judged the higher educated target to be more similar to themselves (M =

!"#$%&'()'*+,,,,,.0,
,
3.94, SD = 1.23) than the less educated target (M = 3.35, SD = 1.24), F(1,385) =
48.92, p < .001, ηp2 = .11, and also liked the higher educated target (M = 4.57, SD =
0.99) more than the less educated target (M = 4.32, SD = 1.00), F(1,386) = 25.40, p <
.001, ηp2 = .06. The least educated participants judged the less educated target to be
more similar to themselves (M = 3.78, SD = 1.24) than the higher educated target (M
= 3.30, SD = 1.21), F(1,385) = 12.76, p < .001, ηp2 = .03. In contrast to the higher
educated participants, however, for the least educated participants the education of the
target did not affect liking, F(1,386) = 0.002, p = .96, ηp2 < .001. This means that
although the least educated group perceived that they were more similar to the less
educated target, they did not evaluate it more positively.
There was a main effect of target ethnicity, indicating that participants saw
Muslim targets (M = 3.48, SD = 1.24) as less similar to themselves than non-Muslim
targets (M = 3.84, SD = 1.16), F(1,389) = 49.38, p < .001, ηp2 = .11, and they also
liked Muslim targets less (M = 4.37, SD = 1.14) than non-Muslim targets (M = 4.54,
SD = 1.06), F(1,390) = 13.23, p < .001, ηp2 = .03. There was no interaction between
target ethnicity and participant education for similarity, F(2,385) = .05, p = .95, ηp2 <
.001, nor liking , F(2,386) = 2.18, p = .11, ηp2 = .01. Although the latter interaction
was not significant, ethnic intergroup bias in liking was highest among the least
educated group.
Education salience did not have any main or interaction effects.
Identification. Identification with one’s educational group was higher among
the higher educated (M = 4.80) compared to the intermediate educated (M = 4.33) and
the least educated (M = 3.94) group, F(2,429) = 22.77, p < .001, η2 = .10. For a
detailed analysis of identification based on the data of Studies 3-4, see Kuppens et al.
(2015). We added identification as a predictor to the previous model. For similarity

!"#$%&'()'*+,,,,,.1,
,
ratings, there was a three-way interaction between identification, target education, and
participant education, F(2,379) = 4.47, p = .01, ηp2 = .02. Higher educated
participants who were low in identification (1SD below the mean) did not see
themselves as more similar to highly educated targets (M =3.40) compared to less
educated targets (M = 3.30), F(1,379) = 0.38, p = .54, ηp2 = .001. By contrast, higher
educated participants who were high in identification (1SD above the mean) saw
highly educated targets as more similar to themselves (M = 4.25) than less educated
targets (M = 3.36), F(1,379) = 66.47, p < .001, ηp2 = .15. Identification had a weaker
relation with the similarity judgments of the least educated. Participants without a
secondary school diploma rated the less educated target as more similar to themselves
regardless of whether they were low, Ms = 3.56 and 3.11, F(1,379) = 8.71, p = .003,
ηp2 = .02, or high in identification with their education group, Ms = 4.39 and 3.82,
F(1,379) = 5.21, p = .02, ηp2 = .01.
For liking, there was a two-way interaction between identification and target
education, F(1,380) = 8.37, p = .004, ηp2 = .02. Among low identifiers there was no
education bias, F(1,380) = 0.31, p = .58, ηp2 = .001. However, highly identified
participants liked the higher educated target more (M = 4.96) than the lower educated
target (M = 4.75), F(1,380) = 10.11, p = .002, ηp2 = .03. Figure 2 shows that this
pattern is more pronounced among higher educated participants, although the 3-way
interaction with participant education is not significant, p = .42. This makes the
pattern for ratings of liking very similar to that of the similarity ratings reported in the
previous paragraph.

!"#$%&'()'*+,,,,,.2,
,
Figure 2: Liking of target individual: interaction between identification and target
education, plotted separately for three educational groups (Study 3). Error bars are
95% CIs.
Although there was also a two-way interaction between ethnicity of the profile
and identification both for similarity, F(1,379) = 8.80, p = .003, ηp2 = .02, and for
liking, F(1,380) = 5.82, p = .02, ηp2 = .02, this is not relevant for the current paper
because there was no interaction with participant education.
Discussion
Participants with a university degree showed educational intergroup bias in the
liking of otherwise identical profiles of less and higher educated target individuals:
they liked higher educated targets more than less educated targets. In contrast, the
less educated did not show educational intergroup bias, even if they perceived
themselves to be more similar to the less educated profiles, which was especially the
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case for those without a secondary school diploma. The education bias of the higher
educated therefore goes beyond mere similarity. Furthermore, the education bias is
evident on a dimension (liking) that is not close to the status-defining dimension, so it
is not simply a reflection of social reality (which could be said of the similarity
ratings). The fact that the higher educated showed more intergroup bias than the less
educated did is inconsistent with the notion that the higher educated engage in
superior moral reasoning. In this particular intergroup context, higher educated
people are more biased than their less educated counterparts.
Education bias among the higher educated was stronger for those who
identified highly with other higher educated people; it was absent for those who
identified less. Thus, education bias only occurs for those higher educated people for
whom education is an important part of their identity. This is further evidence that
these effects do not simply reflect social reality but are based in people’s motivation
to have a positive social identity (Tajfel & Turner, 1979).
The higher educated did not show significantly less anti-Muslim bias than the
less educated did. This is not surprising, given that education effects on racial
attitudes have been shown to be weaker when indirect measures are used (Kuppens &
Spears, 2014).
Study 4
Study 4 is very similar to Study 3 but was run with U.S. rather than British
participants. Studies 4a and 4b were run as independent studies with participants
from Amazon Mechanical Turk. The main difference was that whereas Study 4a used
the same Muslim and non-Muslim profiles as Study 3, in Study 4b we used profiles of
Black and White people instead. We wanted to be able to generalize the findings to
other ethnic minority groups, and Black people are one of the most visible ethnic

!"#$%&'()'*+,,,,,.4,
,
minority groups in the U.S. These are the same studies as those reported as Studies
3a and 3b in Kuppens et al. (2015).
Method
Participants. In Study 4a 420 MTurk workers (157 female, Mage = 30.7,
SDage = 11.1) completed an online questionnaire. Nineteen participants did not
answer “Agree strongly” to the question “Please select the ‘Agree strongly’ answer”
and a further 18 did not disagree with the item “I am an elephant and I live in Africa.”
These 37 inattentive participants were excluded from all analyses. A further five
participants indicated they were Muslim and were excluded from analyses; 378
participants remained.
In Study 4b 532 MTurk workers (340 female, Mage = 34.7, SDage = 12.4)
completed an online questionnaire. Forty participants failed similar attention checks
to those used in Study 4a and were excluded from analyses. A further 35 participants
self-identified as African American and were also excluded; 457 participants
remained.
Education bias and Muslim bias. In Study 4a the four profiles were identical
to those used in Study 3, but we adapted them to a U.S. context. The names implying
that the individual was Muslim or non-Muslim individuals were the same as in Study
3. Here is an example of a less educated non-Muslim individual: “William King is 30
years old and works as a convenience store clerk in the Northwest of the country. He
lives alone in a rented apartment, but has many friends who visit him and is known to
be very amusing. He has always lived in the Northwest and after getting a job in a
shop and enjoying his time there, he decided to settle there. William is an avid
basketball fan and player and regularly plays for a local team. His favorite hobby to
pursue when he has time off work is going camping in the countryside.”

!"#$%&'()'*+,,,,,.5,
,
In Study 4b the four profiles were identical to Study 4a, but we changed the
typically Muslim names to typically Black names (Tyrone Banks and DeShawn
Jefferson) and the non-Muslim names were now typically White names (Dylan
Johnson and Bradley Smith).
For each individual, the same three questions as in Study 3 assessed liking (α
= .88 for higher educated ethnic outgroup, α = .90 for less educated ethnic outgroup,
α = .87 for higher educated ethnic in-group, and α = .88 for less educated ethnic in-
group). Two new questions assessed perceived competence (“How competent do you
think this person is?” and “How hard-working do you think this person is?”) and they
formed a reliable scale (rs = .78 for higher educated ethnic outgroup, .68 for less
educated ethnic outgroup, .76 for higher educated ethnic in-group, and .65 for less
educated ethnic in-group).
Salience of education. Participants were randomly assigned to the “Education
salient” or the “Education not salient” condition and the manipulation was the same as
in Study 3.
Education. Participants’ highest educational level was recoded into three
categories: High school or less (n = 100), Some college or 2-year degree (n = 309),
and At least a 4-year college degree (n = 426).
Identification. We used the same identification scale as used in Study 1
(Leach et al., 2008), but now included all 14 items (α = .93).
Results
Analytic strategy. We conducted a mixed ANOVA, where liking and
competence ratings were modeled as a function of the education of the target person,
the ethnicity of the target person, participant education, education salience, and all
interactions. However, because the participant education variable is not balanced

!"#$%&'()'*+,,,,,/6,
,
(does not have equal numbers in each category), main effects are estimated without
the interaction term with participant education in the model.
Education bias, ethnic bias, and education level. In Study 4 we measured
competence rather than similarity. We first discuss competence and then liking
judgments. Unsurprisingly, higher educated targets (M = 4.89, SD = 0.87) were seen
as more competent than less educated targets (M = 4.24, SD = 0.94), F(1,832) =
419.72, p < .001, ηp2 = .34. This large main effect was qualified by an interaction
with participant education, F(2,828) = 13.28, p < .001, ηp2 = .03: higher educated
targets were evaluated as more competent, but this effect was stronger for the higher
educated, F(1,828) = 327.59, p < .001, ηp2 = .28 than for the intermediate educated,
F(1,828) = 115.74, p < .001, ηp2 = .12, or for the least educated group, F(1,828) =
13.9253, p < .001, ηp2 = .02. There was also an interaction between the ethnicity of
the target and participant education, F(2,828) = 3.92, p = .02, ηp2 = .01. Higher
educated participants judged ethnic outgroups (M = 4.51, SD = 0.88) to be more
competent than ethnic in-groups (M = 4.43, SD = 0.85), F(1,828) = 4.25, p = .04, ηp2
= .005. This pattern was absent for the intermediate educated group, F(1,828) = 0.05,
p = .83, ηp2 < .001, and reversed for the least educated group, where ethnic outgroups
were judged to be less competent (M = 4.65, SD = 1.03) than ethnic in-groups (M =
4.81, SD = 0.84), F(1,828) = 3.97, p = .05, ηp2 = .005. In sum, higher educated
participants show ethnic out-group bias and less educated participants show ethnic in-
group bias in their competence ratings.
For liking judgments, consistent with the results of Study 3, higher educated
targets were evaluated more positively than less educated targets, F(1,833) = 26.42, p
< .001, ηp2 = .03, but this main effect was qualified by an interaction with participant
education, F(2,829) = 5.67, p = .004, ηp2 = .01. Simple effects indicated that, as in

!"#$%&'()'*+,,,,,/-,
,
Study 3, higher educated participants liked the higher educated target more (M = 4.06,
SD = 0.91) than the less educated target (M = 3.86, SD = 0.97), F(1,829) = 29.73, p <
.001, ηp2 = .03, but the least educated participants had similar liking for the higher
educated (M = 3.94, SD = 1.17) and less educated (M = 4.02, SD = 1.17) targets,
F(1,829) = 1.09, p = .30, ηp2 = .001. As in Study 3, ethnic in-group individuals (M =
4.01, SD = 0.95) were liked more than ethnic outgroup individuals (M = 3.94, SD =
1.05), but this difference was not significant, F(1,833) = 1.76, p = .18, ηp2 = .002.
There was no significant interaction with participant education, F(2,829) = 1.92, p =
.15, ηp2 = .005, but, again as in Study 3, ethnic intergroup bias was highest among the
least educated participants.
Education salience did not have any main or interaction effects.
Identification. We added identification to the previous model for competence
judgments. There was a three-way interaction between identification, education of the
target, and participant education, F(2,822) = 3.78, p = .02, ηp2 = .01. Among higher
educated participants, the highly identified (1SD above the mean) showed a stronger
education bias in competence ratings (F(1,822) = 262.55, p < .001, ηp2 = .24) than did
the less identified (1SD below the mean, F(1,822) =56.80, p < .001, ηp2 = .06).
Among the less educated, all groups also evaluated the higher educated targets as
more competent than the less educated targets (i.e., showing out-group bias).
However, less educated participants who highly identified with their education group
showed less education out-group bias (F(1,822) = 1.72, p = .19, ηp2 = .002) in
competence ratings than did their counterparts who identified less highly (F(1,822) =
16.23, p < .001, ηp2 = .02).
For liking judgments there was the same three-way interaction between
identification, education of the profile, and participant education, F(2,823) = 3.70, p =

!"#$%&'()'*+,,,,,/.,
,
.03, ηp2 = .01 (see Figure 3). Among low identifiers there was no education bias
among higher educated (F(1,823) = 0.13, p = .02, p = .72, ηp2 < .001), intermediate
educated (F(1,823) = 2.53, p = .11, ηp2 = .003), or lowly educated participants
(F(1,823) = 0.15, p = .70, ηp2 < .001). However, higher educated participants who
identified highly liked the higher educated target more (M = 4.34) than the less
educated target (M = 4.04), F(1,823) = 44.95, p < .001, ηp2 = .05. This effect was
smaller for the intermediate educated group, Ms = 4.50 and 4.33, F(1,823) = 5.80, p =
.02, ηp2 = .007, and absent for the least educated group, Ms = 4.47 and 4.59, for
higher and less educated target respectively, F(1,823) = 0.79, p = .38, ηp2 = .001.
Figure 3: Liking of target individual: interaction between target education,
participant education, and identification (Study 4). Error bars are 95% CIs.
Discussion
Results replicated those from Study 3. Higher educated participants showed
education intergroup bias in their liking of otherwise identical individuals, liking
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higher educated targets more than lower educated targets. Less educated participants
did not show education intergroup bias. Intergroup bias was more pronounced for
higher educated participants who identified highly with people who have a similar
level of education as their own, compared to those who identified less highly.
That the higher educated show more intergroup bias than the less educated do
(Studies 2-4), is inconsistent with the supposed moral enlightenment of the higher
educated. If intelligence or sophisticated moral reasoning were responsible for the
often-reported tolerance of the higher educated, then this should also apply to
attitudes towards the less educated. Instead, the higher educated show clear and
strong intergroup bias and the less educated do not. In fact, given their vulnerable and
low-status position the less educated could benefit most from showing intergroup
bias. Usually low-status groups indeed show more intergroup bias than high-status
groups do, especially when judgments are made on a dimension other than the status-
defining dimension (Mullen et al., 1992), as is the case in all our studies. This is
because they have more to gain from such intergroup bias (Scheepers, Spears, Doosje,
& Manstead, 2006a). In contrast, the less educated do not show intergroup bias at all,
and this adds to previous research that already found that the less educated have great
difficulty in creating a positive identity (Kuppens et al, 2015).
Regarding competence, higher educated individuals were perceived as much
more competent than less educated individuals by both highly educated and less
highly educated participants. This is not surprising given that perceived competence
is part of the status-defining dimension. The effect of education on competence was
stronger among higher educated participants, especially among those who identified
highly with their level of education. Among the least educated participants who
identified highly with their level of education, the out-group bias in competence

!"#$%&'()'*+,,,,,/0,
,
ratings was small and not statistically significant. This is consistent with a previous
study (Spruyt & Kuppens, 2015b) in which similar effects of identification and
participant education on explicit self-report ratings of the competence of less educated
and higher educated people were found.
Whereas higher educated participants showed intergroup bias with respect to
lower educated groups and the less educated did not, the reverse was the case for
ethnic intergroup bias in competence: Less educated participants evaluated the ethnic
in-group more positively than the ethnic out-group but the higher educated evaluated
the out-group more positively than the in-group. For liking, there was a non-
significant trend for less educated participants to show more bias than higher educated
participants. The same trend was found in Study 3 and when the data from Studies 3
and 4 are pooled, the interaction between target ethnicity and participant education is
significant, F(1, 1215) = 4.15, p = .02, ηp2 = .01; the least educated participants like
ethnic in-group members more (M = 4.33) than ethnic out-group members (M = 4.06),
F(1, 1215) = 17.58, p < .001, ηp2 = .01, and there is no bias among the intermediate or
higher educated group (both ps > .09).
Thus, although the least educated appear to be more prejudiced towards the
classic targets of prejudice compared to those who are more highly educated, a
noteworthy point is that for the higher educated prejudice toward the lower educated
seems to be acceptable, whereas it is not for the classical targets. In short, it seems
that the claim that the lower educated are more prejudiced is only part of the story. It
is rather that the targets of prejudice are different. Indeed, the inability of the less
educated to show intergroup bias on the education dimension, due to reality
constraints, fits with notions of prejudice displaced to other target groups (Glick,
2008; Leach & Spears, 2008) in order to achieve a positive social identity (Tajfel &

!"#$%&'()'*+,,,,,/1,
,
Turner, 1979), although investigating this issue is beyond the scope of the current
paper.
In four studies we have shown that participants who are relatively high on the
education ladder, and especially those who identify with their education group, show
medium to large education intergroup bias, both on a self-report and on a more
indirect measure. In Studies 5, 6, and 7 we investigate possible reasons underlying
this education intergroup bias. Our main interest lies in the perceived responsibility
for educational outcomes. Attribution of responsibility (Weiner, 1995; see Weiner et
al., 1988) is very important for education-based groups. As explained earlier,
educational achievement is often seen as the consequence of individual effort. The
implied role of individual responsibility is a factor that distinguishes the less educated
from many other disadvantaged groups, and is what sets them apart from other groups
with low socio-economic status. By comparison with being poor or working class,
having a low level of education might be more likely to be perceived as something
that individuals could have avoided. Moreover, the increased importance of
education for life outcomes may have led to an increased perception that existing
socio-economic differences are based on merit. In other words, the role of perceived
responsibility for being less educated may have consequences that extend far beyond
the evaluation of less educated people. We address this in Study 5 and develop it
further in Studies 6-7.
Study 5
In this study we aimed to examine the possibility that attributional differences
underlie the education intergroup bias observed in Studies 1-4. Specifically, we asked
about the importance of talent, hard work, and luck for being successful in an
academic versus a professional context. We expected that academic achievement

!"#$%&'()'*+,,,,,/2,
,
would be seen as due more to hard work and less to luck, in comparison with
professional achievement. We expected the less educated to at least partly endorse
this meritocratic view of academic achievement.
An important advantage of Study 5 is that it uses a sample that is
representative of the population. This means that any differences found between
higher and lower educated participants are representative of the differences in the
general population.
Method
Participants. The sample of 1575 respondents is representative for the
population aged 18-75 in Flanders (the Northern part of Belgium) and is described in
detail in De Keere, Vandebroeck, and Spruyt (2015). The sample used in the current
analysis is somewhat smaller due to missing values on the education variable (n = 55)
and the attribution questions (up to n = 106).
Attributions. Six questions about attributions to talent, hard work, and luck
were asked regarding academic achievement and professional achievement. For
example, a question about the importance of hard work read “Anyone can get a
degree if they work hard enough” for academic achievement and “Anyone can be
successful in their job if they work hard enough” for professional achievement. A
question about the importance of luck read “Getting a degree strongly depends on
coincidence” for academic achievement and “Being successful professionally strongly
depends on coincidence” for professional achievement. All items were answered on a
scale from 1 (= “Completely disagree”) to 5 (= “Completely agree”). The two items
assessing talent (r = .46 and r = .45 for academic and professional achievement,
respectively), hard work (r = .48 and r = .39 for academic and professional
achievement, respectively), and luck (r = .42 and r = .30 for academic and

!"#$%&'()'*+,,,,,/3,
,
professional achievement, respectively) were averaged. There were also some
questions about attributions to structural factors (i.e., the labor market or schools), to
people’s family situation, to globalization, and to new technologies, but these were
less relevant here. The survey also contained a wide range of measures not relevant
to attributions for success.
Results
Analytic strategy. We estimated separate models for talent, hard work, and
luck as dependent variables, and therefore applied a Bonferroni correction to control
for multiple testing, by considering effects to be statistically significant when their p-
value is .0167 or smaller. Predictors were the domain of achievement (academic
versus professional), the education level of the respondents, and their interaction.
Academic versus professional achievement. As expected, respondents
believed that academic achievement was less due to luck, F(1, 1426) = 665.65, p <
.001, ηp2 = .32, and more due to hard work, F(1, 1433) = 183.92, p < .001, ηp2 = .11,
compared to professional achievement (see Figure 4). Talent was also seen as more
important for academic than professional success, F(1, 1438) = 11.32, p < .001, ηp2 =
.01), although this effect was much smaller than those for hard work or luck.
Respondent’s education. Main effects of education (ηp2 = .01, .07, and .06
for hard work, luck, and talent, respectively) showed that the less educated tended to
agree more with all items. More interestingly, there was an interaction between
domain and respondent education for hard work, F(2, 1433) = 6.82, p = .001, ηp2 =
.01, but not for talent, F(2, 1438) = 1.45, p = .24, ηp2 = .002, or luck, F(2, 1426) =
0.44, p = .64, ηp2 = .001 (see Figure 4). The fact that hard work was seen as more
important for academic compared to professional achievement was less pronounced
among the least educated respondents compared to other respondents. However, even

!"#$%&'()'*+,,,,,/4,
,
the least educated respondents found hard work more important for academic (M =
3.15) than for professional achievement (M = 2.94), 95% CI for the difference [.10,
.32].
Figure 4: Importance of hard work, luck, and talent for academic and professional
achievement (Study 5). Error bars are 95% CIs.
,
Discussion
In a sample representative of the adult population, academic success was
attributed more to hard work and less to luck, compared to professional achievement.
This highlights a possible reason for the negative attitudes toward less educated
people (found in Studies 1-4).
Interestingly, results were quite similar for higher educated and less educated
respondents. Although differences in attributions to hard work were less pronounced
among less educated participants, even the least educated clearly found hard work
more important for academic than for professional achievement. Our use of a
representative sample means that these results for respondent’s education cannot be
-,
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!"#$%&'()'*+,,,,,/5,
,
attributed to a different selection process of higher versus lower educated participants.
In other words, this is good evidence that the less educated do not seem to contest the
legitimacy attached to their low educational status.
The possible difference in the attribution of responsibility to the less educated
as compared to other disadvantaged groups is addressed in more detail in Studies 6
and 7. In Study 5 we found initial evidence that educational achievement carries
more attributions of responsibility than professional achievement does. In Studies 6-7
we measure attributions about and emotions towards a range of disadvantaged groups.
Study 6
In Study 6 we investigated further the factors underlying the negative
evaluation of the less educated. We used the attribution-emotion model (Weiner et
al., 1988), according to which attributions about why people have ended up in a
adverse situation shape our emotional reactions (primarily anger and pity) and
behavioral intentions towards them.
Specifically, if people’s adversity is caused by external factors, we are likely to
feel pity and help them. However, to the extent that people are perceived to be
responsible for a stigma or low achievement, this evokes emotional reactions of anger
rather than pity, and decreases willingness to help them (Weiner, 1995; Weiner et al.,
1988). Here we apply this framework to disadvantaged groups. In previous research
guided by this model (Dijker & Koomen, 2003; Weiner, 1995; Weiner et al., 1988)
participants typically evaluated one particular individual; here we focus on
evaluations of social groups.
We assessed attributions, emotions, and attitudes about government
intervention related to less educated people, and compared these to the same
evaluations of other disadvantaged groups. Attitudes toward government intervention

!"#$%&'()'*+,,,,,06,
,
are relevant because they assess a general inclination that might feed into specific
political or policy preferences. The poor are an important comparison group because
it is also a group with low socio-economic status but a different status dimension
defines the group (i.e., income rather than education). Socio-economic disadvantage
has many dimensions but, as we argued earlier, education has become more important
in recent decades. We expect the less educated to be evaluated more negatively than
the poor on all dependent variables because lack of education is likely to be seen by
many as a controllable factor, and therefore as something for which the less educated
can be blamed. Thus, we expect the less educated to be seen as more responsible, to
be less likely to be perceived as being treated unfairly, and to elicit less positive and
more negative emotions, compared to the poor. We expect that this will also lead to
less favorable attitudes towards helping the less educated through government
intervention.
Obese people were selected as another comparison group because they are
another stigmatized group that is often blamed for its own disadvantage (Crandall et
al., 2001; Wirtz, van der Pligt, & Doosje, 2015). For attributions of responsibility, we
therefore expect both less educated people and obese people to attract higher ratings
than the other groups.
Blind people, the fourth group we included, are usually not seen as
accountable for their situation so should score low on responsibility. Finally, people
of Turkish descent living in Western Europe are one of the most visible low-status
ethnic minority groups for our participants. We expected at least some
acknowledgment of discrimination against Turks, because this is sometimes reported
in the media and is a topic of ongoing political debate. Therefore, we expect that less

!"#$%&'()'*+,,,,,0-,
,
educated people are less likely to be perceived as victims of discrimination compared
to Turkish people (as well as compared to poor people).
Liking is the only variable that is similar to the dependent variables of Studies
1-4. Given the results in those studies, we expected the less educated to be liked less
than the other disadvantaged groups.
Method
Participants. We recruited 75 student participants (42 women, age M = 21.6,
SD = 2.7) at the University of Groningen. Five participants were excluded from
analyses because they were not from European Union countries. Most remaining
participants were either Dutch (n = 36) or German (n = 31).
Procedure. After giving demographic information, participants completed
measures of Social Dominance Orientation (SDO) and authoritarianism.7 They then
responded to the attributions, emotions, and behavior questions for the five
disadvantaged groups (less educated, poor, blind, Turks, obese). Order of the groups
was randomized. At the end there were some questions about the participant’s own
educational career.
Attributions. Two items were about the group’s responsibility: “To what
extent are [group] responsible for the fact that they are [group]?” (with a 7-point
response scale from “Not at all responsible” to “Entirely responsible) and “To what
extent can [group] be blamed for their situation?” (with a 7-point response scale from
“Not at all” to “Completely”). To measure perceived discrimination and treatment in
,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
7 SDO was measured using six items (α = .75) from the SDO scale (Pratto, Sidanius,
Stallworth, & Malle, 1994). To measure authoritarianism (α = .84) we used eight
items from Duckitt (2010) and two from Zakrisson (2005). Results for these
measures are reported in the supplemental online material (Tables S5-S8).

!"#$%&'()'*+,,,,,0.,
,
society we asked “To what extent are [group] treated unfairly by others?” (with a 7-
point response scale from “Not at all unfairly” to “Very unfairly”) and “To what
extent does society value [group]?” (with a 7-point response scale from “Not at all”
to “Very much”).
Emotions. We measured the emotions pity (pity, feel sorry for, r = .72), anger
(anger, irritation, resentment, α = .84), sympathy, contempt, and how much
participants liked the group (all on 11-point scales from 0 = “Not at all” to 10 =
Extremely”).
Government intervention. We asked whether the government should help a
particular group (“Do you think [group] should be helped by the government to
improve their situation?,” rated on a 7-point scale from 0 = “No help” to 6 = “A lot of
help”) and whether participants thought that helping would improve the group’s
situation (“If the government provided help to [group], would that be likely to
improve their situation?,” rated on a 7-point scale from “Very unlikely” to “Very
likely”).
Results
Analytic strategy. We used multilevel modeling to analyze these data
because ratings of groups (level-1 units) were nested within individual participants
(level-2 units). The model controlled for the correlations between the ratings of all
groups and possible differences in variances between the groups by fitting an
unstructured covariance matrix. Comparisons between groups are investigated using
planned contrasts. We specified the contrasts so that unstandardized coefficients (the
bs reported below) reflect the difference in means between two groups. They can
therefore be interpreted directly as unstandardized effect sizes (and the standard errors
that we report allow the calculation of confidence intervals).

!"#$%&'()'*+,,,,,0/,
,
Overall patterns of attributions. We used planned contrasts to test the
predictions that we developed in the introduction to Study 6. As predicted, less
educated people and obese people were together judged to be more responsible, b =
2.10, SE = .12, p < .001, and blameworthy, b = 2.04, SE = .11, p < .001, compared to
the three other groups combined (see Figure 5, and Table S4 in the supplemental
material for all means). However, the less educated were unexpectedly seen as less
responsible, b = -0.91, SE = .16, p < .001, and less blameworthy, b = -0.72, SE = .16,
p < .001, than obese people. Blind people were seen as less responsible, b = -1.47,
SE = .13, p < .001, and blameworthy, b = -1.71, SE = .13, p < .001, than poor and
Turkish people combined.
Figure 5: Blameworthiness, liking, pity, and anger in relation to five disadvantaged
groups (Study 6). Error bars are Cousineau-Morey 95% CIs that allow within-subject
comparisons between the five groups.
,
6,
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!"#$%&'()'*+,,,,,00,
,
In line with our predictions, the less educated were perceived as being treated
unfairly less often than poor and Turkish people (combined), b = -0.81, SE = .15, p <
.001. Finally, the less educated were liked less than any other group (all four mean
differences > .50 and ps < .031).
These results for attributions and liking are in line with our hypotheses. The
results for liking confirm the results of Studies 1-4 showing that higher educated
people do not like less educated people. We now turn to a more specific comparison
between less educated people and the poor.
Comparison of the less educated with the poor. For all variables the less
educated attracted significantly more negative scores than the poor: They were seen
as more responsible (b = .89, SE = .17, p < .001), blameworthy (b = .87, SE = .17, p <
.001), and less unfairly treated (b = -.54, SE = .17, p = .002); they were liked less (b =
-.51, SE = .23, p = .03); they elicited much less sympathy (b = -1.76, SE = .22, p <
.001), much less pity (b = -1.94, SE = .26, p < .001), more anger (b = .69, SE = .19, p
< .001), and more contempt (b = .61, SE = .23, p = .009); and they were seen as less
deserving of government help (b = -.76, SE = .16, p < .001). As expected, socio-
economic disadvantage in term of education was judged more negatively than socio-
economic disadvantage in terms of wealth.
Finally, we tested whether differences in liking of and emotions towards the
less educated versus the poor were mediated by differences in attributions. We tested
mediation by examining the joint significance of the IV to mediator path and the
mediator to DV path (Fritz, Taylor, & MacKinnon, 2012; Hayes & Scharkow, 2013;
MacKinnon, Lockwood, Hoffman, West, & Sheets, 2002). A confidence interval
around the indirect effect estimate was calculated with PRODCLIN (MacKinnon,

!"#$%&'()'*+,,,,,01,
,
Fritz, Williams, & Lockwood, 2007; Tofighi & MacKinnon, 2011). The results are
presented in Table 3. We did this by estimating regression models in which
responsibility, blameworthiness, and perceived unfair treatment were simultaneously
entered as possible mediators of the difference between less educated and poor on
liking, pity, anger, sympathy, and contempt. The unstandardized coefficients and
associated standard errors for all paths in the mediation models are reported in Table
3. Consistent with Weiner (1988), the effect of group (less educated versus poor) on
anger (see Figure 6) was mediated by responsibility (indirect effect = .32, 95% CI =
[0.08, 0.60]); the corresponding effect on pity was mediated by perceived unfair
treatment (indirect effect = -.31, 95% CI = [-0.61, -0.09]). Lower sympathy towards
the less educated was mediated by judgments of greater blameworthiness for the less
educated compared to the poor (indirect effect = -.40, 95% CI = [-0.81, -0.06]). The
lower liking of the less educated compared to the poor (see Figure 7) was mediated by
the higher perceived responsibility of the less educated (indirect effect = -.31, 95% CI
= [-0.68, -0.001]) and a lower level of perceived unfair treatment against the less
educated, compared to the poor (indirect effect = -.15, 95% CI = [-0.36, 0.01]). It
should be noted, however that the relations between the mediators and liking were
only marginally significant, ps < .08.
Table 3: Unstandardized coefficients (and standard errors below) for the mediation
models where the difference between the less educated and the poor in liking and
emotions is mediated by the attributions (Study 6).
Dependent variable
Pity
Anger
Sympathy
Contempt
Liking
IV to mediator (a)
Responsible
.89***
.89***
.89***
.89***
.89***
(.17)
(.17)
(.17)
(.17)
(.17)
Blameworthy
.87***
.87***
.87***
.87***
.87***
(.17)
(.17)
(.17)
(.17)
(.17)

!"#$%&'()'*+,,,,,02,
,
Unfairly treated
-.54**
-.54**
-.54**
-.54**
-.54**
(.17)
(.17)
(.17)
(.17)
(.17)
Mediator to DV (b)
Responsible
-.09
.36**
.13
.20
-.35†
(.19)
(.13)
(.18)
(.18)
(.18)
Blameworthy
-.05
.08
-.46*
.13
.01
(.22)
(.14)
(.20)
(.20)
(.20)
Unfairly treated
.58***
-.02
.18
.06
.27†
(.16)
(.11)
(.15)
(.15)
(.15)
Total effect (c)
-1.94***
.69***
-1.76***
.61**
-.51*
(.26)
(.19)
(.22)
(.23)
(.23)
Direct effect (c')
-1.50***
.29
-1.37***
.36
-.07
(.29)
(.20)
(.26)
(.26)
(.26)
Indirect effect (ab)
Responsible
-0.08
0.32**
0.11
0.18
-0.31†
Blameworthy
-0.04
0.07
-0.40*
0.11
0.01
Unfairly treated
-0.31**
0.01
-0.10
-0.03
-0.15†
Note. The coefficients related to the IV (a, c, c’, and ab paths) can be read as mean
differences between less educated and working class. IV=independent variable.
DV=dependent variable. *** p < .001. ** p < .01. * p < .05. † p < .10.

!"#$%&'()'*+,,,,,03,
,
Figure 6: Mediation of the difference in anger towards less educated versus the poor,
by attributions (Study 6). Parameters are unstandardized regression coefficients (and
standard errors).
,
,

!"#$%&'()'*+,,,,,04,
,
Figure 7: Mediation of the difference in liking between the less educated and the
poor, by attributions (Study 6). Parameters are unstandardized regression coefficients
(and standard errors).
Discussion
Less educated people were seen as more responsible and blameworthy than
poor people, and as less unfairly treated. These differences mediated the lower liking
of the less educated and the stronger anger felt towards the less educated, compared to
the poor. They also mediated the lesser pity and sympathy felt for the less educated
compared to the poor. For pity and sympathy, a large direct effect of group remained
after taking into account the mediators. This might be due to the fact that poverty
more directly implies suffering, which could elicit pity and sympathy.

!"#$%&'()'*+,,,,,05,
,
The broader implication of these findings is that it matters how low socio-
economic status groups are characterized. Describing them in terms of their
education level leads to more negative evaluations than describing them in terms of
their income. At a societal level, the increased importance of education (Grusky &
DiPrete, 1990) and the suggestion that education is a universal social problem solver
(Depaepe & Smeyers, 2008) may increase the risk that groups with low levels of
socio-economic status will be especially negatively evaluated while strengthening the
ideology of meritocracy. We investigate this idea more directly in Study 7, where we
include measures of meritocratic ideology.
Study 7
Study 7 was similar to Study 6 but was conducted in the U.S. and included
some important changes. First, we replaced ‘the poor’ with ‘the working class’ in
order to have a comparison with a different low socio-economic status group. We
also replaced Turkish with Black people to adapt to the U.S. context, and dropped the
blind as a target group. Our predictions were similar to those for Study 6. We
expected the less educated and the obese to be seen as more responsible and
blameworthy than the other groups. Furthermore, we expected less educated people
to be seen as less unfairly treated than Black people and working class people. We
also expected the less educated to be liked less than other groups. Importantly, in the
comparison with the working class, we expected the less educated to be evaluated
more negatively on all dependent variables.
We added measures of meritocratic ideology in order to investigate the extent
to which the results of Study 6 reflect ideological beliefs about inequality. Measuring
meritocratic ideology enables us to relate ideological beliefs to processes of
attribution and emotions regarding the less educated. Because those who believe in

!"#$%&'()'*+,,,,,16,
,
meritocracy assume that people get what they deserve, we expected that meritocracy
beliefs would be related positively to judgments of responsibility and
blameworthiness, and negatively to perceptions of unfairness and deservingness of
help.
We also measured the extent to which participants thought they deserved their
own level of educational achievement and had had to work hard for it. People who
thought that they had to work hard to obtain their educational qualification might be
more likely to think that educational differences are fair. Similarly, believing that
your own educational achievement was mainly due to hard work is likely to be related
to meritocratic ideology and to judgments of responsibility for educational outcomes.
To investigate the construct validity of our measures of attributions, emotions,
and liking of the less educated, we added a self-report measure of bias against lower
educated people. We predicted that this self-reported education bias would be related
to evaluations of the less educated, especially the measure of liking.
A final change is that we recruited a diverse sample. Doing so enabled us to
investigate (as in Study 5) the extent to which the lower educated also make negative
attributions and feel negative emotions about those with low levels of education.
Method
Participants. We recruited 290 MTurk workers (129 women, age M = 35.9,
SD = 11.9). Nine participants did not disagree with the attention check question
“Seven plus five equals twenty-nine”. A further two participants did not answer
“Agree strongly” to the question “Please select ‘agree strongly’ for this item.” These
11 inattentive participants were excluded from analyses.

!"#$%&'()'*+,,,,,1-,
,
Procedure. After giving demographic information, participants completed
measures of Social Dominance Orientation (SDO) and authoritarianism.8 They then
responded to the attributions, emotions, and behavior questions for the four
disadvantaged groups (less educated, working class, Blacks, obese). Order of
presentation of the groups was randomized. Finally, participants completed the
meritocracy scales and responded to questions about their own educational career.
Attributions. Items assessing responsibility and blameworthiness were the
same as those used in Study 6. To measure perceived discrimination, we asked “To
what extent are [group] treated unfairly by [others]?” For the item about less
educated people, these “others” were “higher educated people,” for working class
they were “middle and upper class people,” for obese they were “non-obese people”,
and for Black people we used “people from other races.” The 7-point response scale
for these items was anchored at 0 (= “Not at all unfairly”) and 6 (= “Very unfairly”).
We also added a measure of perceived suffering: “How much do [group] suffer due to
their situation?” Responses were given on a 7-point scale from 0 (= “Do not suffer at
all”) to 6 (= “Suffer very much”).
Emotions. We measured the emotions pity (pity, feel sorry for, r = .78), anger
(anger, irritation, resentment, α = .90), sympathy, contempt, and how much
participants liked the group in the same way as in Study 6.
Help. Attitudes towards helping were measured with the item “Do you think
[group] deserve help to improve their situation?” Responses were given on a 7-point
scale from 0 (= “No help”) to 6 (= “A lot of help”).
,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,
8 We used the same scales for SDO (α = .88) and authoritarianism (α = .89) as in
Study 6. Results for these scales are reported in the supplemental material (Tables
S10-S14).

!"#$%&'()'*+,,,,,1.,
,
Meritocracy measures. We included measures of individual mobility (4
items, α = .84) (McCoy & Major, 2007), protestant work ethic (5 items, α = .91)
(Quinn & Crocker, 1999), and belief in a just world (8 items, α = .94) (Lipkus,
Dalbert, & Siegler, 1996). Because the three measures correlated highly (all rs > .67),
we constructed a single meritocracy scale (α = .88).
Education. Participants’ highest educational level was recoded into three
categories: High school or less (n = 35), Some college or 2-year degree (n = 112), and
At least a 4-year college degree (n = 131).
Identification. We assessed participants’ identification with their educational
group using 11 items (α = .94) from Leach et al. (2008), excluding the in-group
homogeneity subscale and the item “I often think about the fact that I am [education
group]”.
Own education difficulty. Two items (e.g., “I have had to make big efforts
for my education”, r = .73) assessed how difficult participants thought their own
educational achievements had been.
Own education merit. Two items (e.g., “What I have achieved in my
education is mostly due to my own effort”, r = .65) assessed the extent to which
participants thought their own educational achievements were due to their own effort
and qualities.
Self-reported education bias. We formulated six items (α = .87) to measure
the extent to which participants reported preferring higher over lower educated
persons. Example items are “I think less of someone when they haven’t finished their
education,” and “I evaluate less and higher educated people in the same way”
(reverse-coded).

!"#$%&'()'*+,,,,,1/,
,
Results
The same model as that used in Study 6 was used to analyze the data.
Overall patterns of attributions. As predicted, less educated and obese
people were together judged to be more responsible, b = 1.49, SE = .07, p < .001, and
blameworthy, b = 1.15, SE = .08, p < .001, compared to the other groups combined
(see Figure 8, and Table S9 in the supplemental material for all means). However, as
in Study 6, the less educated were seen as less responsible, b = -0.47, SE = .09, p <
.001, and less blameworthy, b = -0.38, SE = .09, p < .001, than obese people. None
of these effects were qualified by a significant interaction with participant education
(all ps > .06).
Figure 8: Blameworthiness, liking, pity, anger, and deservingness of help in relation
with four disadvantaged groups (Study 7). Error bars are Cousineau-Morey 95% CIs
that allow within-subject comparisons between the four groups.
,
For perceptions of unfair treatment there were only very small differences
between groups and no main or interaction effects of education. In contrast to
expectations and the results of Study 6, the less educated were not perceived as being
6,
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2,
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!"#$%&'()'*+,,,,,10,
,
treated unfairly significantly less than working class and Black people (combined), b
= -0.07, SE = .09, p = .46.
The less educated were liked less than Blacks, b = -2.28, SE = .16, p < .001,
and the working class, b = -1.54, SE = .18, p < .001, but not significantly less than the
obese, b = -0.24, SE = .16, p = .13. In line with the results of Studies 1-4 and Study
6, this again illustrates that the less educated are not liked.
Comparison of less educated with working class people. In Study 6, the
comparison of less educated and poor people showed that less educated people were
evaluated more negatively than the poor on all variables. Here we compare the less
educated with the working class, and we also take participant education into account.
For some outcome variables, there was only an effect of group (less educated
versus working class) but no main effect or interaction with participant education.
The less educated were seen as more responsible (b = .43, SE = .09, p < .001) than
working class people. They were also liked much less (b = -2.28, SE = .16, p < .001)
and elicited more anger (b = 1.09, SE = .12, p < .001). Unexpectedly, the less
educated were perceived to suffer more (b = 0.76, SE = .10, p < .001), and elicited
more pity (b = 0.65, SE = .19, p < .001), but less sympathy (b = -0.30, SE = .21, p =
.16) than the working class. This contrasts somewhat with Study 6, where more pity
was reported towards the poor than the less educated. We return to this point in the
Discussion.
There were interactions between group (less educated versus working class)
and participant education for blameworthiness, F (2,275) = 4.76, p = .009, and
contempt, F (2,275) = 3.46, p = .03. All education groups blamed the less educated
more than the working class, but surprisingly the effect size was larger for
participants with only a high school diploma (ΔM = 1.29, SE = .26, p < .001) than for

!"#$%&'()'*+,,,,,11,
,
those with a 4-year degree (ΔM = 0.46, SE = .13, p < .001), with the intermediate
educated group taking an intermediate position (ΔM = 0.87, SE = .15, p < .001). In
other words, those with less education were the ones who blamed the group of less
educated people most, showing a striking internalization of negative opinions about
their group. Higher educated participants felt more contempt for the less educated
than for the working class (ΔM = 0.83, SE = .20, p < .001), an effect that was smaller
for the intermediate educated group (ΔM = 0.63, SE = .22, p = .004) and reversed,
albeit non-significantly so, for the least educated group of participants (ΔM = -0.31,
SE = .39, p = .42). Finally, there were no effects of group or participant education on
perceived unfair treatment, sympathy, or deservingness of help (all ps > .15).
In sum, and as expected, socio-economic disadvantage in terms of education
was judged more negatively than socio-economic disadvantage in terms of
occupation. Overall, this pattern did not differ much between participants with lower
or higher levels of education.
As in Study 6, we tested whether differences in liking of and emotions towards
the less educated versus the working class were mediated by differences in
attributions. We estimated regression models in which responsibility,
blameworthiness, unfair treatment, and suffering were simultaneously entered as
possible mediators of the difference between less educated and working class people
on liking, pity, and anger. Responsibility and blameworthiness correlated highly (r =
.81) and were therefore averaged and added as a single mediator to the models. The
stronger pity towards the less educated (compared to the working class) was mediated
by the fact that the lower educated were perceived as suffering more than the working
class, indirect effect = .62, 95% CI [0.42, 0.83] (see Table 4). The stronger anger
towards the less educated was mediated by increased perceptions of responsibility,

!"#$%&'()'*+,,,,,12,
,
indirect effect = .14, 95% CI [0.07, 0.22], and suffering, indirect effect = .16, 95% CI
[0.07, 0.26]. However, the lower liking of the less educated was not mediated by
perceptions of responsibility, unfair treatment, or suffering.
Table 4: Differences between perceptions of the less educated and the working class.
Unstandardized coefficients (and standard errors) for the mediation models where the
difference in liking and emotions is mediated by perceptions of responsibility, unfair
treatment, and suffering (Study 7).
Dependent variable
Pity
Anger
Liking
IV to mediator (a)
Responsible
0.58***
0.58***
0.58***
(0.09)
(0.09)
(0.09)
Unfairly treated
0.03
0.03
0.03
(0.10)
(0.10)
(0.10)
Suffer
0.76***
0.76***
0.76***
(0.10)
(0.10)
(0.10)
Mediator to DV (b)
Responsible
-0.14
0.24***
0.01
(0.08)
(0.05)
(0.08)
Unfairly treated
0.41***
-0.04
0.16*
(0.08)
(0.05)
(0.07)
Suffer
0.81***
0.21***
-0.002
(0.08)
(0.06)
(0.08)
Total effect (c)
0.65***
1.09***
-2.28***
(0.19)
(0.12)
(0.16)
Direct effect (c')
0.10
0.79***
-2.29***
(0.18)
(0.12)
(0.18)
Indirect effect (ab)

!"#$%&'()'*+,,,,,13,
,
Responsible
-0.08
0.14***
0.01
Unfairly treated
0.01
-0.001
0.01
Suffer
0.62***
0.16***
-0.002
Note: The coefficients related to the IV (a, c, c’, and ab paths) can be read as mean
differences between less educated and working class. IV=independent variable.
DV=dependent variable. *** p < .001. * p < .05.
Beliefs about meritocracy, own education, and education bias. As
expected, meritocracy beliefs were strongly related to attributions of responsibility (r
= .47, p < .001) and blameworthiness (r = .48, p < .001) in relation to the less
educated, and this was the case regardless of participants’ own educational group.
Meritocracy beliefs were related to a similar degree to attributions of responsibility
and blameworthiness for the other four disadvantaged groups (see Table S10 in the
supplemental material). This is consistent with the fact that meritocratic beliefs
include beliefs that people deserve their own outcomes.
Meritocracy beliefs were also moderately negatively related to judgments of
unfair treatment (r = -.34, p < .001), suffering (r = -.21, p < .001), and deservingness
of help (r = -.35, p < .001) in relation to the less educated, and this was similar when
working class people and obese people were the target group. However, these
relations were stronger in relation to Black people (all rs > .53, see Tables S11-S12 in
the supplemental material). With respect to emotions, meritocracy beliefs were
related to less sympathy (r = -.23, p < .001) and less pity (r = -.19, p = .001) towards
the less educated. Again, correlations were similar for working class people and
obese people, but stronger in relation to Black people (see Tables S12-S14 in
supplemental material). Thus, apart from the responsibility and blameworthiness
ratings, meritocracy beliefs were especially related to attributions, emotions, and

!"#$%&'()'*+,,,,,14,
,
liking with regard to Black people compared to the three other disadvantaged groups
we investigated.
Turning to participants’ beliefs about their own educational achievement, we
found that internal attributions for own achievement and difficulty of own
achievement were both positively related to judgments of responsibility (r = .23 and
.14, respectively, ps < .05) and blameworthiness (r = .27 and .13, respectively, ps <
.05) in relation to the less educated. Meritocracy beliefs were also related to internal
attributions for participants’ own achievement, r = .31, p < .001, but not to difficulty
of own achievement, r = .10, p = .11. Although these correlational data do not
warrant strong conclusions, they suggest that people’s own experiences in the
educational system might predispose them to perceive others as being responsible for
their educational outcomes. Note, however, that these relations are similar for the
other three target groups, so further research is needed to clarify the direction of
causal processes involved in these relations.
Overall, self-reported education bias was low, with a mean of 1.85 (SD = 1.36)
on a 0 to 6 scale. Nevertheless, 24.1 percent of participants scored at or above the
midpoint of the scale, which is remarkable given the blatantly discriminatory nature
of the items. As predicted, self-reported education bias was positively related to anger
(r = .44, p < .001) and contempt (r = .29, p < .001) felt towards the less educated, and
negatively related to liking of the less educated (r = -.47, p < .001). As well as
showing that education bias is expressed openly, this demonstrates convergent
validity for the emotion measures used in Studies 6-7.
None of the above relations regarding meritocracy beliefs, participants’ own
educational achievement, and self-reported education bias were moderated by
participant education. We did find that higher educated participants showed more

!"#$%&'()'*+,,,,,15,
,
education bias, F(2,271) = 3.89, p = .02, and felt they had had to work harder for their
educational achievement, F(2,272) = 6.01, p = .003, compared to less educated
participants (the mean of the intermediate educated group fell between those of the
other groups).
Discussion
Compared to the working class, the less educated were perceived to be more
responsible and more blameworthy, they elicited more anger, and they were liked
less. In sum and as predicted, less educated people were evaluated more negatively
than other groups with low socio-economic status.
In Study 6, the poor elicited much more pity than the less educated did, but in
the current study the working class elicited less pity than the less educated did. The
high level of pity towards the poor found in Study 6 probably has more to do with the
inherent suffering associated with being poor than with something specific about less
educated people. Participants in the current study seemed to acknowledge that the
less educated suffer more than the working class, and they felt more pity—but not
more sympathy—for the less educated, compared to the working class. The greater
pity felt towards the less educated compared to the working class should not be
interpreted positively because the higher educated also felt more contempt for the less
educated, compared to the working class. The pity felt towards the less educated
therefore seems to reflect the negative, patronizing side of pity rather than its positive
side (Florian, Mikulincer, & Hirschberger, 2000; Nadler, Harpaz-Gorodeisky, & Ben-
David, 2009).
Interestingly, there were few differences between the perceptions of less and
more highly educated participants. However, these similar responses represent very
different psychological perspectives between these two groups: The more highly

!"#$%&'()'*+,,,,,26,
,
educated showed out-group derogation whereas the less educated showed in-group
derogation. Lower educated participants also judged the less educated to be more
responsible for their situation. To a large extent, therefore, lower educated people
endorse the negative evaluations that are made about them. Indeed, the one
moderation by participant education that we did find was that lower educated
participants blamed less educated people to an even greater extent than higher
educated people did. Bearing in mind that our sample of people with no more than a
high school degree was modest in size, we conclude that there are no indications that
less educated people resist the negative attributions made about them and even seem
to internalize them. This interpretation is rendered more plausible by the consistent
results observed in Study 5, which used a representative sample (albeit from a
different country).
Meritocracy beliefs were strongly related to making internal attributions for
the situation of disadvantaged groups, including less educated people. Given that the
less educated are seen as particularly blameworthy for their own situation, this
suggests a link between the ideology of meritocracy and people’s opinions about
educational inequality.
General Discussion
Across seven studies we (1) reported the first evidence of education-based
intergroup bias, (2) showed that, contrary to popular ideas, the higher educated show
more education intergroup bias than do the less educated, (3) found that less educated
people are evaluated more negatively than the poor or the working class, two other
groups with low socioeconomic status, and (4) argued and demonstrated that
perceived personal responsibility for one’s educational level plays an important role
in evaluations of less educated people.

!"#$%&'()'*+,,,,,2-,
,
Regarding education bias, Studies 1-2 showed that higher educated people
show strong education-based intergroup bias on a feeling thermometer: They feel
much warmer towards highly educated people than towards their less highly educated
counterparts. In Studies 3-4 higher educated participants evaluated otherwise
identical target individuals more positively when they were more highly educated
rather than less highly educated. This education bias among the higher educated was
stronger for those who identified strongly with the group of higher educated people,
implying that social identity processes are operating. In contrast, less educated
participants did not show such education-based intergroup bias (but they did show
more ethnic intergroup bias). In Studies 5-7 we went beyond studying evaluation and
found that the less educated are seen as responsible and blameworthy for their
situation, even by the less educated themselves. Importantly, the less educated are
liked less and are seen as more blameworthy than poor people and working class
people, two other groups defined by low socioeconomic status.
Are the higher educated more tolerant?
These findings appear to be at odds with the moral enlightenment hypothesis,
which states that higher educated people show less negative attitudes towards out-
groups because they have superior moral reasoning. First, in Studies 3-4 the higher
educated showed more education-based intergroup bias than did the less educated
when we used indirect measures of bias. Second, in Study 7 the higher educated had
higher explicit self-reported education bias than did the less educated. Such findings
are incompatible with the idea that the superior moral reasoning of the higher
educated prevents them from forming negative opinions about out-groups. At the
very least, this particular intergroup relation (i.e., attitudes toward less educated)

!"#$%&'()'*+,,,,,2.,
,
constitutes an exception, one for which the moral enlightenment idea cannot provide
an explanation.
Similar to the case of the higher educated, political liberals in the U.S. were
also thought to be more tolerant than political conservatives (Farwell & Weiner, 2000;
Sears & Henry, 2003). However, recent evidence shows that they are not more
tolerant, but rather are intolerant of different groups than conservatives are. Both
liberals and conservatives are intolerant of groups with whom they perceive an
ideological worldview conflict (Brandt, Reyna, Chambers, Crawford, & Wetherell,
2014; Crawford, 2014). In this light it is important to note that the higher educated
are not in a direct worldview conflict with the less educated. They might of course
have values or political views that are, on average, different from those of the less
educated, but being less educated does not directly entail such views and therefore
cannot be an explanation for our results. Indeed, if anything the lower educated
reinforce the privileged position of the higher educated, rather than being in conflict
with it. Interestingly, a recent longitudinal study also found that enlightenment is an
unlikely explanation for the effect of education on social liberalism (Surridge, 2016).
Future research should investigate whether education-based groups are the only
exception to the rule of tolerance among the higher educated. This would enable us to
reach more definite conclusions about the moral enlightenment hypothesis and the
nature of the education effect on traditional forms of prejudice.
In our studies there was always an explicit reference to the educational level of
the target person or group. How likely is it that we will see similar effects when
education is not explicitly mentioned, for example in day-to-day social interactions?
We know that people are able to judge another’s social background from observing
brief social interactions (Kraus & Keltner, 2009), and that this can influence their

!"#$%&'()'*+,,,,,2/,
,
interactions with others (Kraus, Horberg, Goetz, & Keltner, 2011; Kraus, Park, &
Tan, 2017). These processes likely exist for the more specific case of educational
background as well. Therefore, the attitudes toward education-based groups that we
investigated here potentially affect many social interactions.
Intergroup bias among the less educated
In contrast to the higher educated, the less educated do not show education-
based intergroup bias. This is noteworthy because the less educated could actually
benefit most from intergroup bias. Intergroup bias is instrumental for low-status
groups because it is part of a process of social change (Scheepers et al., 2006a), and
intergroup bias is indeed common among low-status groups (Mullen et al., 1992). So,
education-based intergroup bias is not merely another demonstration of the existence
of intergroup bias, but it reveals that the less educated stand out because they are a
low-status group that does not evaluate their own group more positively than an out-
group. This adds to other evidence that the less educated occupy a very special and
vulnerable psychological position (Kuppens et al, 2015), which is often reinforced
through societal institutions (Bourdieu & Passeron, 1990; Depaepe & Smeyers, 2008;
Labaree, 2008; Meyer, 1977; Stephens, Markus, & Phillips, 2014).
Regarding classic targets of prejudice, such as Muslims and Blacks, we did
find evidence of more intergroup bias among the less educated than among the higher
educated in Studies 3-4. However, this relation was weak, which may be partly due
to the indirect measure used in those studies (see also Kuppens & Spears, 2014).
A comprehensive explanation for these findings regarding education bias and
ethnic bias might be found in social identity theory (Tajfel & Turner, 1979).
Education bias can be safely used by the higher educated to construct a positive social
identity because higher education is both positive and legitimate. This is supported

!"#$%&'()'*+,,,,,20,
,
by our finding that identification is related to higher education bias among the higher
educated. For the less educated it is difficult to use their educational level to attain a
positive identity. Therefore, denigrating out-groups such as ethnic minorities might
be an attempt by the less educated to use another dimension (i.e., ethnicity) to
distinguish themselves positively. As noted earlier, this fits with the idea of displaced
prejudice (Glick, 2008; Leach & Spears, 2008).
Education-based groups and social inequality
These results have important consequences for the changing nature of social
inequality, and citizens’ attitudes towards inequality. Given the increased importance
of education for many life outcomes, education has become a key aspect of social
inequality in recent decades. The attributions associated with high and low
educational levels may therefore have changed the way that people view social
inequality. If education is regarded as being an individual’s own responsibility, then
people are likely to be less critical of social inequality that stems from differences in
education. Relatedly, more highly educated high-status groups can use references to
education as a means to justify and legitimize their position. If educational outcomes
are seen as largely deserved, then their consequence are, too. Michael Young (1958)
(sarcastically) coined the term ‘meritocracy’ to refer to a dystopian future society in
which power and status was believed to fairly reflect differences in intelligence and
education. He predicted that this would lead to strong and initially uncontested social
inequality, and a negative view of those with lower levels of education. Our evidence
suggests that his warning was correct. Ironically, his term ‘meritocracy’ is now
generally used in an uncritically positive way (Young, 2001).
Emphasizing the importance of education could therefore be the last bastion of
acceptable prejudice among the higher educated (see also Jackman, 1994).

!"#$%&'()'*+,,,,,21,
,
Remember that across Studies 6 and 7 the obese were seen as even more responsible
and blameworthy than the less educated, but the less educated were still liked slightly
less than the obese. This could reflect a vested interest on the part of the higher
educated to denigrate the lower educated, which does not exist in the case of the
obese. With respect to the denigration of the less educated it is important to note, as
we did in the Introduction, that there is a wealth of evidence that educational
achievement is not simply the result of talent and hard work (e.g., Bukodi et al.,
2014). This means that negative attitudes toward the less educated cannot be justified
in terms of the greater merit of those with higher education.
In Studies 5-7 we made use of Weiner’s attribution-emotion model to gain
insight into the bases of these negative attitudes towards the less educated. Results
showed that perceived responsibility was high for the less educated, but there could of
course be other judgment dimensions that set the less educated apart from other social
groups. Differences in liking between the less educated and the poor/working class
were not always fully explained by the attributions (such as responsibility) that we
assessed. One question for future research is therefore what these remaining
differences in liking are based on.
Theoretically our work extends Weiner’s attribution model to explanations for
intergroup differences and integrates with research on group-based emotions as
explanations of prejudice towards social groups. The results also provide some
support for what Pettigrew (1979) termed the “ultimate attribution error,” whereby
groups are blamed for negative outcomes but also given credit for positive outcomes
(in the current context, the higher educated regard themselves as responsible for their
own educational level). However, the present research goes beyond simply defining a
new area of application for these ideas, in the sense that it focuses on a target group,

!"#$%&'()'*+,,,,,22,
,
the lower educated, that has thus far gone unnoticed as a victim of prejudice, and
identifies an unlikely perpetrator group, the higher educated. We argue that this
particular combination of an overlooked target group and an overlooked perpetrator
group represents a lacuna in the literature that needs to be explained. We believe that
the lack of attention to education-based groups until now has served to justify social
inequality, although we do not wish to undermine the efforts of those who have
focused on groups (based on ethnicity, gender, age) that are now acknowledged to be
unacceptable targets of prejudice and discrimination. We argue that the key social
psychological theories of intergroup inequality (relative deprivation theory, social
identity theory, resource mobilization theory, social dominance theory, system
justification theory) need to accord educational intergroup bias more theoretical
scrutiny if they are to provide a full account of how social inequality persists and is
reproduced.
Why has the topic of education-based groups been neglected?
Scholars are almost by definition highly educated. No human being is free
from biases in judgment or attitudes, so it is likely that the lack of attention paid to
educational groups is partly due to the fact that the less educated have no ready means
of defending themselves in academic research and literature. Sexism, racism, and
other forms of prejudice in the social sciences have been contested by scholars
belonging to groups on the receiving end of these types of prejudice and
discrimination. In the case of education, however, this is not possible. Less educated
people are almost by definition excluded from the business of conducting research. If
you are reading this, you are almost certainly highly educated yourself. In other
words, it is possible that the issue of prejudice towards education-based groups has
not been studied because scholars all belong to the advantaged group.

!"#$%&'()'*+,,,,,23,
,
One could argue that the economy needs (highly) skilled workers, and that it is
therefore unavoidable that a positive value is accorded to education. While this is
obviously correct, it does not alter the fact that from a psychological point of view,
the study of education-based groups is long overdue (see also Spruyt & Kuppens,
2015a) and should yield theoretical as well as practical knowledge that, in the longer
term, could improve the well-being of the less educated.

!"#$%&'()'*+,,,,,24,
,
Acknowledgements
We would like to thank Namkje Koudenburg, Maja Kutlaca, Jolien van Breen,
Bibiana Armenta Gutiérrez, Justin Richardson, Babet LeKander-Kanis, and Simon
Dalley for their helpful comments on an earlier draft of this paper.
,

!"#$%&'()'*+,,,,,25,
,
Open practices
The research in this article earned Open Materials and Open Data badges for
transparent practices. Materials and data for the research are available at
https://osf.io/v6a8x.
,

!"#$%&'()'*+,,,,,36,
,
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