Finding (dis‐)advantaged system justifiers: A bottom‐up approach to explore system justification theory

Abstract

System Justification Theory (SJT) postulates that individuals are motivated to justify the status quo, including the paradoxical prediction that those who are disadvantaged (e.g., lower social status) by the prevailing system will justify the system more than those who are advantaged by the prevailing system. We test if this assumption holds in an entire sample, or only among subsets of a sample using a bottom‐up approach, Correlational Class Analysis. Using a representative sample from four European countries ( N total = 5157) we found six subpopulations. The first subpopulation ( Justifiers, n total = 1256; 24%) was consistent with SJT, that is, system justification and social status were negatively correlated. The second subpopulation ( Rejectors, n total = 1688; 33%), however, was characterized by a positive correlation between social status and system justification, which contrasts with the prediction of system justification theory. The other four subpopulations ( N total = 2211; 43%) were characterized by an ambivalent pattern. That is, at least one social status indicator, but not all, supported the prediction that disadvantaged individuals justified the system more than advantaged individuals. These heterogeneous patterns would be undetected using traditional approaches. Further, our results show that inequality salience is lower, trust in political institutions is higher, and support for political violence is higher among Justifiers compared to Rejectors . We discuss how understanding the interrelations between multiple indicators of social status and how they differ between subpopulations can help us to obtain a more comprehensive picture regarding under which circumstances and for whom system justification theory applies.

Full text

(Dis-)Advantaged System Justifiers
1
Finding (Dis-) Advantaged System Justifiers – A bottom-up approach to explore system
justification theory
Rebekka Kesberg, University of Sussex & University of Amsterdam
Mark J. Brandt, Michigan State University
Matthew J. Easterbrook, University of Sussex
Bram Spruyt, Vrije Universiteit Brussel
Felicity Turner-Zwinkels, Tilburg University
Corresponding author:
Rebekka Kesberg
Political Science Department
University of Amsterdam
r.kesberg@uva.nl
Funding information: This work is financially supported by the NORFACE Joint Research
Programme on Democratic Governance in a Turbulent Age and co-funded by ESRC, FWO,
NWO and the European Commission through Horizon 2020 under grant agreement No
822166. We do not have any potential competing interest.
Ethical approval for the main survey was obtained on 16 November 2021 (ref: PSY-2122-S-
0052). As per the ethical approval informed consent was gathered at the start of the survey
and no identifying information was gathered from participants.

(Dis-)Advantaged System Justifiers
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Abstract
System Justification Theory (SJT) postulates that individuals are motivated to justify the
status quo, including the paradoxical prediction that those who are disadvantaged (e.g., lower
social status) by the prevailing system will justify the system more than those who are
advantaged by the prevailing system. We test if this assumption holds in an entire sample, or
only among subsets of a sample using a bottom-up approach, Correlational Class Analysis.
Using a representative sample from four European countries (Ntotal = 5,157) we found six
subpopulations. The first subpopulation (Justifiers, ntotal = 1,256; 24%) was consistent with
SJT, that is system justification and social status was negatively correlated. The second
subpopulation (Rejectors, ntotal = 1,688; 33%), however, was characterised by a positive
correlation between social status and system justification, which contrasts with the prediction
of system justification theory. The other four subpopulations (Ntotal = 2,211; 43%) were
characterised by an ambivalent pattern. That is, at least one, but not all social status indicators
supported the prediction that disadvantaged individuals justified the system more than
advantaged individuals. These heterogeneous patterns would be undetected using traditional
approaches. Further, our results show that inequality salience is lower, trust in political
institutions is higher, and support for political violence is higher among Justifiers compared to
Rejectors. We discuss how understanding the interrelations between multiple indicators of
social status and how they differ between subpopulations, can help us to obtain a more
comprehensive picture regarding under which circumstances and for whom system
justification theory applies.
Words: 248
Key words: System Justification, Correlational Class Analysis, Social Status, Subjective
Inequality

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System Justification Theory (SJT; Jost, 2019; Jost & Banaji, 1994) postulates that
1
individuals are consciously or unconsciously motivated to justify the prevailing social
2
structure even when the system is unjust and, under certain conditions, when it disadvantages
3
them. The idea is that supporting the status quo can satisfy people’s basic psychological needs
4
(i.e., epistemic, existential, and relational), leading them to endorse attitudes that contradict
5
their groups or self-interest (for a demonstration, Jost et al., 2003). Like many theories, the
6
research examining SJT’s assumptions and predictions are sometimes contradictory (e.g.,
7
Brandt, 2013; Brandt et al., 2020; Owuamalam et al., 2018; Sotola & Credé, 2022; Trump &
8
White, 2018). Typically, contradicting evidence is counted as evidence against the theory,
9
whereas supporting evidence is counted as evidence in favor of the theory. Whether the theory
10
is supported in aggregate depends on whether contradicting or supporting evidence is more
11
convincing (e.g., rigorous method, consistent results, larger effect sizes). Here, instead of
12
testing (again) if SJT is a viable theory in aggregate, we take a different approach and
13
consider for whom the theory most strongly applies.
14
We aim to contribute to the literature by assessing whether it is possible to identify
15
people who support and contradict SJT within the same sample, using a bottom-up approach.
16
Specifically, we use a Correlational Class Analysis (CCA; Boutyline, 2017) to identify
17
subpopulations which differ in how their objective (i.e., education) and subjective social
18
status (i.e., relative deprivation, subjective income) are associated with system-justifying
19
attitudes. This analysis reveals that the predictions of SJT hold for some subpopulations, but
20
not for other subpopulations. Therefore, our findings neither unequivocally support nor reject
21
SJT. Instead, we show for whom the theory’s predictions hold.
22
Assumptions of SJT
23
System justification theory postulates that “people are motivated to defend, justify,
24
and bolster aspects of the status quo, including existing social economic and political systems,
25
institutions and arrangements” (Jost et al., 2015, p. 321). In support of this assumption,
26

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scholars have found, for example, that people engage in biased information processing in
1
support of the system (Hennes et al., 2012) and that criticism of the system elicits defence
2
mechanisms (Jost & Hunyady, 2005); but see Sotola & Credé, 2022). Further, justifying
3
prevailing systems has many implications for political attitudes and behaviors. System
4
justification attitudes are associated with high trust in institutions (Cichocka & Jost, 2014;
5
Hunyady, 2018; Intawan & Nicholson, 2018; Jost et al., 2003), support for established
6
political parties and candidates (Langer et al., 2022; Satherley et al., 2022), less support of
7
system-challenging movements (e.g., Occupy Wall Street, Jost, 2019), and more support for
8
conservative and/or right-wing ideologies (e.g., Jost et al., 2004).
9
Here, we focus on reviewing supporting and contradicting evidence for two key
10
claims of SJT: (1) disadvantaged groups report equal or more system-justifying attitudes than
11
advantaged groups, and (2) system-justifying attitudes are higher when inequalities are
12
salient.
13
Key claim 1: Disadvantaged groups tend to justify the system.
14
SJT postulates that the system motivation holds – at least to some degree – for
15
everyone, independent of their own position in the society. For advantaged groups, this
16
system justifying motivation aligns with self and group justification motives because
17
supporting the system maintains their high status. For disadvantaged groups, however, it
18
conflicts with self and group justification motives. This mismatch between motives for
19
disadvantaged groups is thought to induce cognitive dissonance, an aversive feeling of
20
uncertainty that people seek to avoid (Proulx et al., 2012). Disadvantaged groups can respond
21
to that cognitive dissonance by bolstering their support for the social system and the status
22
quo (Jost et al., 2003). This heightened cognitive dissonance experienced by disadvantaged
23
people and groups implies that they are equally or more strongly motivated to defend the
24
status quo and see the status quo as legitimate compared to advantaged groups (Jost, 2011;
25
Jost et al., 2004; Rudman et al., 2002). Indeed, cross-sectional surveys (Jost et al., 2003;
26

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Sengupta et al., 2015), interviews (Durrheim et al., 2014; Godfrey & Wolf, 2016), and
1
experimental approaches (van der Toorn et al., 2015) have found support for the claim that
2
disadvantaged, low-status, and low-power groups express more system-justifying attitudes
3
than advantaged, high-status, and high-power groups: “people are very good at making a
4
virtue out of necessity” (Jost, 2020, p. 3).
5
This prediction is controversial. For example, some scholars have critiqued the
6
cognitive dissonance assumption in SJT, suggesting that system justification serves as an
7
identity management strategy and is most prevalent in people who strongly identify with the
8
devalued group (Owuamalam et al., 2016). Empirically, others found little evidence that
9
disadvantaged groups in general show more system-justifying attitudes in analyses of large
10
and international datasets (Brandt, 2013; Brandt et al., 2020; Caricati, 2017; Davidai, 2018).
11
For example, Brandt (2013) did not find more system-justifying attitudes amongst
12
disadvantaged groups including people with lower income or education, and women. In
13
contrast, on average, high-status groups were found to be more likely to support, trust and
14
legitimise the prevailing system (Hetherington, 1998; Jost & Burgess, 2000). Buchel and
15
colleagues (2021) using the ladder measure of subjective social status found that objectively
16
disadvantaged individuals were more motivated to defend the system, while subjectively
17
disadvantaged individuals defended the system only in unequal contexts. Other studies also
18
found that disadvantaged groups are less supportive of unequal social conditions (Guimond et
19
al., 2003; Lee et al., 2011) and perceive the current society as less ideal (Zimmerman &
20
Reyna, 2013). In sum, there is contradicting evidence and it remains unclear if objective and
21
subjective social status predicts system-justifying attitudes positively, negatively, or not at all.
22
Key claim 2: Social inequality fosters system-justifying attitudes, especially in
23
disadvantaged groups
24
Contextual factors are thought to impact the motivation to justify the system (Jost &
25
Banaji, 1994; Kay & Friesen, 2011). Experiencing and/or being aware of inequalities in the
26

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surroundings increases cognitive dissonance and thus motivates people to justify the system.
1
Therefore, system justifying attitudes are assumed to be stronger in environments in which
2
“inequality in the system is made especially salient” (Jost et al., 2015, p. 322). While the
3
assumption is repeatedly mentioned in theoretical articles about system justification (e.g., Jost
4
et al., 2004, p. 910, Hypothesis 18), empirical tests of the assumption are rare. Moreover, the
5
existing empirical findings typically do not support the SJT assumption. For example, Trump
6
and White (2018) experimentally manipulated the level of inequality (here the Gini
7
coefficient) and measured overall perceived fairness of the system, trust in institutions, and
8
fairness of the economic system. Inequality did not significantly predict economic system
9
justification or institutional trust. Moreover, for general system justification, the opposite
10
effect emerged (i.e., system justification was lower in the high inequality condition).
11
Additionally, their results revealed a mixed pattern for the interaction between social status
12
and inequality. For general system justification a small effect supporting SJT claims was
13
found, while there was no effect for trust in institutions and a small effect for economic
14
system justification contradicting SJT claims. In sum, the authors conclude that across well-
15
powered representative sample and two replications there is no evidence supporting the claim
16
that inequality increases system justification.
17
Results from research using large representative data sets (i.e., American National
18
Election Studies, General Social Surveys, and World Value Survey, Brandt, 2013;
19
International Social Survey Program, Caricati, 2017) also mostly contradicts SJT
20
assumptions. For example, Caricati (2017) used the human freedom index and Gini
21
coefficient as measures of inequality and found that across 36 countries advantaged
22
individuals justify the status more, especially in equal contexts, compared to disadvantaged
23
individuals. Brandt (2013) found mixed results testing SJT assumptions with Gini and Gender
24
Inequality coefficients as measures of social inequalities. Results for the Gini coefficient were
25
not significant or opposed to the SJT assumptions. The findings for the Gender Inequality
26

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index revealed some weak support for the SJT claims, but only for social class, and not for
1
any other status indicator like education or income.
2
In sum, most existing findings do not support the assumption, however, less research
3
examined inequality and previous research exclusively focused on country-level indicators of
4
economic inequality (e.g., Gini coefficient) or manipulated inequality information. Country-
5
level indicators of inequality might be too broad to capture the potential impact of inequality
6
on system justification. Research focusing on political attitudes and voting patterns indicates
7
that to understand how economic inequality fosters political attitudes, it is important to not
8
just focus on macro-levels of inequality (e.g., Gini coefficient), but also consider meso- and
9
micro-levels of how individuals experience the places they live in (e.g., McKay et al., 2021;
10
Rodríguez-Pose, 2018). Considering that the proposed underlying mechanism for system
11
justification is reducing cognitive dissonance, salience of inequality in people’s surroundings
12
and their personal experience of inequality might be better indicators compared to ‘abstract’
13
country-level indicators.
14
Therefore, we focus on perceptions of inequality in everyday life. That is, we measure
15
people’s self-reported inequality salience in their everyday environment and perceived
16
fairness of resource allocation in society. It may be the case that country-level indicators of
17
inequality are an indirect proxy of people's own inequality perceptions. However, like all
18
indirect measures, the extent the country-level indicators map onto people’s own impressions
19
is likely imperfect. Thus, in this study we apply a more direct measure of subjective
20
perceptions of inequality which can potentially shed new insights on the link between
21
inequality and system justification. We test the prediction that perceptions of inequality will
22
moderate the association between social status and system justification. When inequality
23
perceptions are high, people with lower social status will be more likely to justify the system,
24
whereas the link between status and system justification will be weaker or reversed when
25
inequality perceptions are low.
26

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Overview
1
Our review shows that existing work both supports and contradicts SJT’s key claims.
2
This is a relatively typical pattern in much of social psychology. Some scholars posit an
3
effect; others find contradicting evidence. The situation is resolved when one side collects
4
enough evidence to show that their side is typically correct (e.g., a meta-analytic estimate
5
significant and in the predicted direction) or an overlooked moderator is identified that
6
explains the different results between studies (e.g., cultural context). The problem with this
7
approach, however, is that it is often not clear in advance what moderator variables might be
8
relevant. Thus, it is never clear whether moderation would have been found in previous
9
studies, or whether there are additional relevant moderators.
10
We take a different approach. Rather than considering which perspective receives the
11
most support, we instead aim to identify the subpopulations for whom the SJT assumptions
12
hold and the subpopulations for whom the SJT assumptions do not hold. That is, rather than
13
identifying which perspective is right and which perspective is wrong, we aim to identify the
14
people for whom each perspective best applies. Therefore, the overarching goal of our article
15
is to explore whether the two key claims of SJT that we reviewed hold for the whole sample
16
or only for subpopulations. The claims we test are:
17
Claim 1: Social status negatively predicts system-justifying attitudes.
18
Claim 2: The association between social status and system-justification is stronger
19
when inequality is salient.
20
In order to achieve this aim, we take two approaches. First, we take a traditional
21
approach that tests the claims in the whole sample using multiple regression analysis. Second,
22
we take a novel, bottom-up approach. Our analysis progresses in a stepwise fashion. First, we
23
inductively identify subpopulations using correlational class analysis (Boutyline, 2017). This
24
technique identifies subgroups who share a similar correlational structure in their responses.
25
The aim of this analysis is to test claim 1, that is to identify subpopulations who differ in how
26

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well SJT claim 1 applies. To do this, we include all the available items that measure system
1
justification or social status in the CCA. This identifies groups of people who think about the
2
economic system and its relation to their social status in a similar way. In this case, the CCA
3
could identify subpopulations with positive or negative associations between social status
4
indicators and system justification items. It is therefore a way of identifying the people in our
5
sample whose pattern of correlations between survey responses are consistent with the first
6
claim of SJT and those that are not.
7
Next, we test claim 2 by predicting subpopulation by inequality perceptions. That is,
8
are subpopulations which support SJT claim 1 more likely to emerge when inequality is
9
salient. We further explore the composition of the subpopulations (e.g., demographics). These
10
subsequent analyses help us to gain a deeper understanding of why SJT is supported among
11
some people, but not among others.
12
Finally, we are interested whether the subpopulations differ in how system
13
justification is associated with system legitimising attitudes like satisfaction with democracy,
14
trust in institutions and support for violence against the government. For political outcomes
15
we deliberately focused on attitudes that directly refer to important societal institutions. It is
16
the legitimacy of these institutions which will ultimately determine the level of societal unrest
17
(Farrell & Knight, 2003; Putnam, 1993). The analysis serves to explore if how people think
18
(i.e., subpopulation) is meaningful beyond what people think (i.e., mean system-justifying
19
attitude) for the legitimising of these institutions.
20
Method
21
Sample & Procedure
22
The sample consists of 5,157 respondents living in France (n = 1,201), Poland (n =
23
1,529), Spain (n = 1,215), and the UK (n = 1,212). The Polish sample was collected by the
24
Pollster Research Institute and the France, Spain and UK sample was collected by IPSOS.
25
Quotas were applied based on age, gender, education, and region. Quotas for age, gender, and
26

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education were crossed with each other. Region was not crossed with other quotas. The
1
distribution of these quota variables is based on Eurostat 2020 figures. The sample excludes
2
respondents who failed more than one of the three attention checks. Data collection was part
3
of a larger project which collected data in 9 countries. The combination of variables used in
4
this research, however, were only available in four countries. Therefore, we only included
5
these respective countries. Data and materials necessary to replicate our findings are available
6
on OSF (https://osf.io/gvcfx/?view_only=62031f9f7b6147af8c3c615d11340c1c).
7
Instruments
8
Instruments to detect subpopulations
9
Economic System Justification. Economic System Justification was measured using
10
three items (i.e., item 1, 7 and 12 of the original scale)
1
developed by Jost and Thompson
11
(2000). An example item reads “Economic positions are legitimate reflections of people’s
12
achievements.” All items were measured on a scale from 1 (Strongly disagree) to 5 (Strongly
13
agree). Internal consistency was satisfactory, Cronbach’s α = .76 (France = .77; Poland = .64;
14
Spain = .81; UK = .79)
15
Social status variables. Education was used as an indicator of objective social status.
16
Education was coded into two categories: individuals without university degrees (coded -0.5)
17
and individuals with a university degree (coded 0.5). This decision was made because
18
education effects are mainly driven by differences between individuals with university
19
degrees and all others (Easterbrook et al., 2016).
20
Two indicators of subjective social status were used: subjective income and relative
21
deprivation. For subjective income, respondents indicated on a 5-point scale to what extent
22
they felt that they were able to live a comfortable life with their current household income (1:
23
1
Due to limited study capacity, only these three items were measured in the study.

(Dis-)Advantaged System Justifiers
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very easy – 5: very difficult). We reverse-coded this item so that higher scores reflect living
1
more comfortably.
2
Relative deprivation was measured with three items from Elchardus and Spruyt (2012
3
(2012). An example item reads “Whichever way you look at it, people like me always get
4
short-changed.” All items were measured on a scale from 1 (Strongly disagree) to 5 (Strongly
5
agree). Internal consistency was satisfactory, Cronbach’s α = .78 (France = .80; Poland = .74;
6
Spain = .74; UK = .84).
7
Instruments to describe subpopulations
8
Subjective Inequality in Everyday Life. Subjective Inequality in Everyday Life
9
(SIEL) was measured using four items (i.e., item 4, 7, 8 and 9 of the original scale) developed
10
by García-Castro et al. (2019). An example item reads “Among the people I surround myself
11
with, some can afford to buy a lot more and better things than others.” All items were
12
measured on a scale from 1 (Strongly disagree) to 5 (Strongly agree). Internal consistency
13
was satisfactory, Cronbach’s α = .84 (France = .87; Poland = .83; Spain = .83; UK = .80).
14
Perceived Inequality of Resources. Perceived inequality of resources (PIR) was
15
measured using two items adapted from Sánchez-Rodríguez et al. (2019). An example item
16
reads “The resources in [Country] are distributed unequally.” All items were measured on a
17
scale from 1 (Strongly disagree) to 5 (Strongly agree). The two items correlated with r = .73
18
(France = .82; Poland = .70; Spain = .66; UK = .73).
19
Identification. Identification with education and income was measured using two
20
items: “I identify with people with a similar level of education to my own” and “I identify
21
with people with a similar level of income to my own”. Items were measured on a scale from
22
1 (Not at all) to 6 (Extremely). The two items correlated with r = .73 (France = .68; Poland
23
= .77; Spain = .73; UK = .71). We included these items to explore if levels of identification
24
differ across possible subgroups of participants.
25

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Status Anxiety. Status anxiety was measured using five items (i.e., item 1 to 5 of the
1
original scale) from Melita et al. (2020). An example item reads “I feel anxious that I will be
2
stuck in my position for life.” All items were measured on a scale from 1 (Strongly disagree)
3
to 5 (Strongly agree). Internal consistency was satisfactory, i.e., Cronbach’s α = .91 (France
4
= .91; Poland = .88; Spain = .90; UK = .93). We included this measure to explore if levels of
5
status anxiety differ across possible subgroups of participants.
6
Political outcomes
7
Trust in institutions. Trust in institutions was measured using three items adapted
8
from European Social Survey Round 9. Participants indicated the extent to which they trust
9
(1) [Country]’s parliament, (2) [Country]’s politicians and (3) the legal system on a scale
10
from 0 (No trust at all) to 10 (Complete trust). Internal consistency was satisfactory,
11
Cronbach’s α = .86 (France = .86; Poland = .86; Spain = .83; UK = .87).
12
Satisfaction with democracy. Satisfaction with democracy was measured with one
13
item adapted from European Social Survey Round 9. Participants indicated the extent to
14
which they are satisfied with the way democracy is working in [Country] on a scale from 0
15
(Very dissatisfied) to 10 (Very satisfied).
16
Support of violence against the government. Support of violence against the
17
government was measured using three items that were developed within the broader research
18
project. An example item reads “Violent action against the government is needed to bring
19
about real change.” All items were measured on a scale from 1 (Strongly disagree) to 5
20
(Strongly agree). Internal consistency was satisfactory, Cronbach’s α = .85 (France = .85;
21
Poland = .91; Spain = .79; UK = .78).
22
Control variables
23
As control variables in the regression models, we included participants’ age (grand-mean
24
centred) and gender (coded male = 0.5, female = -0.5). For complete information about all
25
items included in the original survey see codebook on OSF.
26

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Analytical Strategy
1
We conduct our analyses in two steps. First, we use the traditional approach to test
2
claim 1 that disadvantaged groups (i.e., low education, low income, and high deprivation)
3
tend to justify the existing system more than advantaged groups in the full sample. We
4
regressed education, income, and relative deprivation on system justification, including fixed
5
effects for countries.
6
In the second step, we use the bottom-up approach by conducting a CCA using the full
7
sample with the corclass R package (Boutyline et al., 2016). We included the economic
8
system justification items and social status items (8 items in total, see section ‘instruments to
9
detect subpopulations’). Using CCA allows us to test our assumptions inductively by sorting
10
individuals into subpopulations based on similarities in their correlation pattern, instead of
11
their absolute scores. This means individuals within one subpopulation can differ in their
12
absolute score of the included variables (e.g., individuals with high and low perceived relative
13
deprivation could be sorted into the same subpopulation) but will be similar regarding the
14
interrelations among system-justifying attitudes and social status (e.g., all individuals in the
15
same subpopulation will have a stronger negative association between system justification
16
and social status). This approach differs from other frequently used clustering methods like
17
hierarchical cluster analysis in which clusters are determined based on similarity of scores on
18
a set of items. That is, within a cluster, individuals are similar in terms of what they think
19
(e.g., individuals with similar system justifying attitudes cluster together), while CCA
20
determines clusters based on similarity in interrelationship between constructs, which is
21
similarity in how people think. CCA builds on relation class analysis (RCA, Goldberg, 2011).
22
RCA works well to cluster together individuals with linear transformation, but it is less
23
sensitive for clustering individuals who diverge from that kind of transformation. Simulations
24
indicate that CCA outperforms Relational Class Analysis in accuracy to detect shared patterns
25
in interrelations (Boutyline, 2017).
26

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12
To test claim 2, we conducted multinomial logistic regression analysis predicting
1
subpopulation by inequality perceptions and sociodemographic characteristics. This approach
2
allows us to test if interrelations supporting SJT claim 1 are more likely to occur when
3
inequality is salient. Finally, to explore whether how people think (i.e., CCA class
4
membership) predicts political outcomes above and beyond what people think (i.e., their
5
absolute scores on the measured attitudes), we predict violence against the government, trust
6
in institutions and satisfaction with democracy by system-justification and subpopulation.
7
Results
8
Claim 1: Social status negatively predicts system-justifying attitudes
9
Traditional Approach
10
We conducted multiple regression analysis, predicting system-justifying attitudes by
11
social status indicators (i.e., income, education, relative deprivation). Income and inequality
12
perception were mean centred in each country and education was coded as -0.5 (lower
13
educated, that is without university degree) and 0.5 (higher educated, that is bachelor’s degree
14
and higher). We included fixed effects for country and controlled for gender and age. Results
15
are displayed in Table 1 (separate country analyses are reported in SOM Table S1 to S4).
16
The results show that individuals with higher income hold more system-justifying
17
attitudes in the full sample and in all four countries separately. Further, there was no
18
significant relationship between relative deprivation and system justification. This is
19
inconsistent with the claim that disadvantaged groups justify the system (more). However, in
20
the full sample individuals with higher education had less system-justifying attitudes. This
21
finding held in the Spanish and British sample, but not in the French and Polish sample (see
22
SOM). This is (partly) consistent with the SJT claim. In combination, the findings show that
23
the relationship between social status and system justification might differ for subjective and
24
objective measures and between countries. All findings hold after controlling for gender and
25
age (see supplementary online material). The findings show that in the full sample, people
26

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13
with more conservative attitudes, who are older, or who are male hold more system-justifying
1
attitudes. Additionally, gender was only a significant predictor in Spain and age was not
2
significant in the UK.
3
In sum, when following a traditional approach, our initial findings do not fully support
4
the claim that disadvantaged groups hold more system-justifying attitudes when considering
5
income or relative deprivation, but our findings do support the claim when status is measured
6
using level of education (these associations were not significant in all countries, but were in
7
the predicted direction). These mixed results are emblematic of the status-system justification
8
literature. One way to advance this discussion is to follow a more bottom-up approach and try
9
to identify subpopulations for which the key predictions of SJT (may or may not) hold.
10
Bottom-up Approach: Correlational Class Analysis
11
In the following, we used CCA to first find subpopulations who share interrelations
12
between social status indicators and system-justifying attitudes. The CCA identified six
13
subpopulations in the full sample (for country description see SOM Table S5 to S18). Below,
14
we will describe each subpopulation in turn.
2
15
Subpopulation 1: Justifiers. In the first subpopulation, the system justification items
16
were negatively associated with income (~r = -.18, p < .001) and education (~r = -.49, p
17
< .001), and positively with relative deprivation (~r = .62, p < .001) (see Figure 1 for a
18
network plot; see SOM Table S19). That is, people who are disadvantaged in one of the three
19
domains (i.e., lower income, lower education and feeling deprived) were more likely to justify
20
the status quo, and vice versa. That is, this subpopulation shows a correlational pattern which
21
fits with the claims of SJT. In total, 24% of the full sample belonged to the Justifiers
22
population (French sample: 21%; Polish sample: 29%; Spanish sample: 24%; UK sample:
23
22%).
24
2
In the full sample, we found 1 degenerated class, which was excluded from further analyses. Degenerated
classes are classes which only consist of a few individuals, here n = 2.

(Dis-)Advantaged System Justifiers
14
Subpopulation 2: Rejectors. In the second subpopulation, the system justification
1
items were positively associated with income (r = .33, p < .001) and education (r = .48, p
2
< .001), and negatively with relative deprivation (~r = -.27, p < .001) (see Figure 1 for a
3
network plot; see SOM Table S20 for correlation matrices). That is, people who were
4
advantaged in three domains (i.e., higher education, higher income, and affluent), were more
5
likely to justify the status quo, and vice versa. That is, this subpopulation shows a correlation
6
pattern which contrasts with the claims of SJT. In total, 33% of the full sample belonged to
7
the rejector subpopulation (French sample: 35%; Polish sample: 34%; Spanish sample: 31%;
8
UK sample: 31%).
9
Subpopulation 3: Alternative. In the third subpopulation, all items were only weakly
10
correlated. That is, even the items that belonged to established scales only correlated weakly
11
(i.e., economic system justification: ~r = 0.08, only item 1 and item 2 are significantly related;
12
relative deprivation ~r = 0.15, item 2 and item 3 are not significantly related). System
13
justification was positively associated with income (~r = .10, pitem 1 & item 3 ≥ .100; pitem 2
14
< .001), education (~r = .11, pitem 1 & item 3 ≤ .003; pitem 2 = .248), and relative deprivation (~r
15
= .21, p ≤ .003
3
) (see Figure 1 for a network plot; see SOM Table S21 for correlation
16
matrices). In total, 12% of the full sample belonged to that subpopulation (French sample:
17
11%; Polish sample: 12%; Spanish sample: 10%; UK sample: 14%).
18
Subpopulation 4: Education-based Justifiers. In the fourth subpopulation, the
19
system justification items were strongly negatively associated with education (r = -.71, p
20
< .001), supporting SJT claims. They were positively associated with income (r = .09, p
21
≤ .006) and negatively with relative deprivation (~ r = .27, p < .001) rejecting SJT claims (see
22
Figure 1 for a network plot; see SOM Table S22 for correlation matrices). In total, 19% of the
23
full sample belonged to the Education-based Justifiers subpopulation (French sample: 20%;
24
3
The second relative deprivation item and third system justification item did not correlate significantly, r = .024,
p = .564.

(Dis-)Advantaged System Justifiers
15
Polish sample: 16%; Spanish sample: 22%; UK sample: 19%). We named this population
1
Education-based Justifiers because education had the strongest relation with system
2
justification. However, note that for income and relative deprivation, the results contradict
3
SJT.
4
Subpopulation 5: Education-based Rejectors. In the fifth subpopulation, the system
5
justification items were strongly positively associated with education (r = .66, p < .001),
6
rejecting SJT claims. It was negatively associated with income (r = -.14, p item 2 & item 3 ≤ .006, p
7
item 1 = .072) and positively with relative deprivation (~r = .20, p < .001),
4
supporting SJT
8
claims (see Figure 1 for a network plot; see SOM Table S23 for correlation matrices). That is,
9
people with lower income, higher education, and who felt more deprived, were more likely to
10
justify the status quo and vice versa. Especially, level of education revealed a strong
11
association with system-justifying attitudes. In this subpopulation, the relative deprivation
12
items did not correlate strongly with each other, and some even showed negative correlations.
13
In total, 7% of the full sample belonged to education-based rejector subpopulation (French
14
sample: 7%; Polish sample: 7%; Spanish sample: 8%; UK sample: 7%). We named this
15
population Education-based rejectors because education had the strongest relation with
16
system justification, however, note that for income and relative deprivation the results support
17
SJT.
18
Subpopulation 6: Income-based Rejectors. In the sixth subpopulation, the system
19
justification items were positively associated with income (r = .28, p < .001), rejecting SJT
20
claims. Economic system justification item 1 was unrelated to education (r = .08, p = .187),
21
but item 2 and item 3 were weakly negatively related to education (r = -.11, p ≤ .078),
22
supporting system justification claims. System justification was not significantly related to
23
relative deprivation (~r = -.07, p ≥ .121) (see Figure 1 for a network plot; see SOM Table S24
24
4
Relative deprivation item 3 only correlated significantly with economic system justification item 1 (r = .12, p
= .026), but not with economic system justification item 2 (r = .06, p = .261) and item 3 (r = -.01, p = .873).

(Dis-)Advantaged System Justifiers
16
for correlation matrices). That is, people with higher income were more likely to justify the
1
status quo, while no clear pattern for the other variables emerged. In total, 5% of the full
2
sample belonged to the income-based rejector subpopulation (French sample: 5%; Polish
3
sample: 3%; Spanish sample: 5%; UK sample: 7%). We named this population Income-based
4
Justifiers because income had the strongest relation with system justification, however, note
5
that for education and relative deprivation the results contradict SJT.
6
In sum, the CCA revealed that individuals differ in how social status is associated with
7
system-justification. About half of our sample was characterised by a pattern which either
8
strongly supported (i.e., Justifiers) or strongly rejected SJT assumptions (i.e., Rejectors). The
9
Justifier Subpopulation supports SJT’s claim that system-justifying attitudes are stronger/also
10
prevalent in disadvantaged subpopulations, whereas the Rejector Subpopulation 2 contradicts
11
SJT’s claim and finds that higher status individuals were more likely to endorse system-
12
justifying attitudes. Across all subpopulations, we find that 55% of people respond in ways
13
that are (partly) consistent with SJT’s claims (subpopulation 1, 4, 5, & 6), whereas the
14
remainder of the sample is inconsistent with the theory (subpopulation 2 and subpopulation
15
3).
16
Claim 2: The association between social status and system justification is stronger when
17
inequality is salient
18
To test claim 2, we conducted multinomial logistic regression analysis. We predicted
19
subpopulation membership (a categorical variable) using subjective inequality in everyday
20
life (SIEL) and perceived inequality in resources (PIR). A description of class composition is
21
displayed in Table 2 and all results are displayed in Table 3. We chose the Justifiers
22
subpopulation as the reference group because this tells us which characteristics are associated
23
with a higher likelihood to deviate from the group that best matched SJT Claim 1. The results
24
show when SIEL and PIR are higher, individuals were more likely to belong to the Rejectors,
25
Education-based Justifiers, Education-based Rejectors or Income-based Rejectors
26

(Dis-)Advantaged System Justifiers
17
subpopulation compared to the Justifiers subpopulation. SIEL and PIR did not predict a
1
difference between the Justifiers subpopulation and the Alternative subpopulation. The results
2
contradict SJT’s prediction. When inequality was salient, people were less likely to belong to
3
the Justifiers subpopulation. In other words, the Justifiers perceived the least amount of
4
inequality.
5
Who supports SJT?
6
We extended the multinomial regression used to test Claim 2 by entering
7
sociodemographic characteristics (e.g., gender) as predictors of subpopulation membership
8
(see Table 2 & Table 3). Out of the sociodemographic characteristics, education turned out to
9
be the most important predictor of subpopulation membership as higher educated people were
10
more likely to belong to any other subpopulation than the Justifiers subpopulation.
11
Additionally, people who had lower income and were older were more likely to belong to the
12
Rejectors subpopulation compared to the Justifiers subpopulation. People with higher income
13
were more likely to belong to the Alternatives compared to the Justifiers. People with lower
14
income and less relative deprivation were more likely to belong to Income-based Rejectors
15
compared to the Justifiers. People with higher income, less deprivation, and who were male
16
were more likely to belong to Education-based Justifiers compared to the Justifiers, and
17
people who were male and less deprived were more likely to belong to Education-based
18
Rejectors compared to the Justifiers.
19
Additional analyses: Exploring the association of identification and status anxiety for
20
Justifiers and Rejectors
21
Two subpopulations – Justifiers and Rejectors – in combination comprised of more
22
than half the sample, emerged in each country, and while the associations between social
23
status variables were similar, the association between social status and system justification
24
was opposing. Therefore, we conducted additional analyses to explore in more detail who is
25
more likely to belong to the Justifiers or the Rejectors. We estimated logistic regressions
26

(Dis-)Advantaged System Justifiers
18
predicting subpopulation membership by identification with status dimensions (education,
1
income), status anxiety, and their interactions with social status (see supplementary materials ,
2
Table S41 & S42 and figure S1 to S4). The results indicate that for lower educated people the
3
probability of belonging to the Rejectors subpopulation decreased with higher identification
4
with education, whereas for higher educated people the probability of belonging to the
5
Rejectors subpopulation increased with identification. For income the results were in the
6
opposite direction. That is for people with lower income (-1 SD) the probability of belonging
7
in the Rejectors subpopulation increased with higher identification with income, whereas for
8
people with higher income (+1 SD) the probability of belonging to the Rejectors
9
subpopulation decreased with identification. For status anxiety the result for both education
10
and income were similar. That is for lower status people the probability of belonging to the
11
Rejectors increased with status anxiety, whereas for higher status people the probability
12
decreased with status anxiety. This suggests that psychological variables of status anxiety and
13
group identification are differently associated with SJT support and may be important
14
moderators of the extent SJT claims are upheld or not. We discuss these findings in the
15
general discussion.
16
The role of what and how people think for legitimizing the system
17
To test the consequences of system justification, we ran multiple regression analyses
18
predicting violence against the government, trust in institutions, and support of democracy by
19
subpopulation controlling for mean level of system justification, income, relative deprivation
20
and education with fixed effects for country (results are displayed in Table 4 – 6). The aim
21
was to see if how people think (i.e., subpopulation membership) explains variance
22
additionally to what people think (e.g., economic system justification). We found that
23
subpopulation did explain additional variance in support of violence against the government
24
and trust in institutions, but not in satisfaction with democracy. Most notable, there was a
25
consistent difference between Justifiers and the Rejectors. The rejectors had significantly
26

(Dis-)Advantaged System Justifiers
19
lower trust and lower satisfaction with democracy but were also less supportive of violence
1
against the government than the Justifiers. These findings are not fully as expected, and we
2
will discuss them in the general discussion section.
3
Discussion
4
We tested two claims which are key predictions of SJT (Jost & Banaji, 1994). The
5
first claim we tested was if disadvantaged groups expressed more system-justifying attitudes
6
than advantaged groups. Using typical aggregate approaches, we find inconsistent results, a
7
set of findings we share with past investigations of these questions. However, using a bottom-
8
up approach, we find that how we answer the question depends on the subpopulation focused
9
on. In the Justifier subpopulation, we identified a subpopulation in which disadvantaged
10
people expressed more system-justifying attitudes than advantaged people, consistent with
11
SJT. We also found a Rejector subpopulation in which disadvantaged people expressed less
12
system-justifying attitudes than advantaged people, contrary to SJT. Four subpopulations
13
were identified that provided a mix of evidence supportive or opposed to SJT predictions
14
depending on the precise measure of social status. In total, these findings show that SJT does
15
receive support, but that support is limited to a specific subpopulation. At the same time, these
16
findings show that SJT does not receive support, but that rejection is limited to a specific
17
subpopulation. These different subpopulations were not detected when considering the
18
complete sample using regression analysis.
19
The second claim we tested was whether the negative association between social
20
status and system-justifying attitudes was more likely in contexts with more perceived
21
inequality. Although we found differences between the subpopulations in terms of perceived
22
inequality, these differences were not as anticipated by the theory. Instead of finding that the
23
Justifier subpopulation perceived more inequality, we found that the Justifier subpopulation
24
perceived the least amount of inequality of all of the subpopulations we identified. That is,
25
although the Justifier subpopulation is consistent with SJT predictions, the perceived levels of
26

(Dis-)Advantaged System Justifiers
20
inequality of this subpopulation are contrary to SJT predictions. This may suggest that other
1
theoretical explanations are necessary to explain why the Justifiers have a negative
2
association between social status and system-justifying attitudes.
3
Justifiers and Rejectors
4
Our bottom-up approach revealed that in about one quarter of the sample the SJT
5
prediction that social status is negatively associated with system-justifying attitudes held (i.e.,
6
Justifiers) and that for about one third of the sample the SJT prediction was rejected (i.e., the
7
Rejectors). For the remainder of the sample, we found a mixed pattern. Given that the
8
majority of people belonged to the Rejectors or one of alternative subpopulations, this can
9
also explain why – when considering the whole sample – the effects of social status on system
10
justification are small and/ or non-significant. The presence of these different subpopulations
11
may also explain why the results of prior investigations have been so inconsistent.
12
These two main subpopulations – Justifiers and Rejectors – were also found in each
13
country. Justifiers consist of disadvantaged individuals who justify the status quo, and
14
advantaged people who do not. Rejectors consist of advantaged individuals who justify the
15
status quo, and disadvantaged people who do not. They differ in how social status indicators
16
are associated with system justification, however, the associations between the social status
17
indicators were similar. That is, higher educated individuals perceived that it is easier to live
18
with their income and felt less deprived in both subpopulations, yet, only in the Rejectors
19
subpopulation the advantaged individuals defended the status quo. The Rejectors were
20
slightly higher educated on average and more likely to perceive inequality. Potentially, the
21
positive association between social status and system justifying attitude results from the need
22
to justify the inequality and their own high position within the society. However, it remains
23
unclear what exactly determines whether a lower or higher educated individual becomes a
24
Justifier or Rejector.
25

(Dis-)Advantaged System Justifiers
21
Exploratory analyses showed that the association between people’s status and
1
probability of belonging to the Justifiers and Rejectors subpopulation depended on
2
identification with status dimensions and status anxiety. Consistent with the assumptions of
3
the social identity model of system attitudes (SIMSA, Owuamalam et al., 2018), we found
4
that individuals who strongly identified with education were more likely to belong to a
5
subpopulation in which their status group justified the system (i.e., higher educated in the
6
Rejecters subpopulation and lower educated in the Justifiers subpopulation). However, for
7
income the pattern was reversed. For status anxiety, the results showed that both higher and
8
lower status individuals were more likely to bolster the status quo when they felt secure in
9
their status. However, when individuals worried about their status, they were more likely to
10
reject the status quo (i.e., lower status individuals were more likely to be in the Rejectors
11
subpopulation and higher status individuals in the Justifiers subpopulation). This could
12
indicate that contextual factors which impact the stability of societal structure also influences
13
the distribution of higher and lower status people in each subpopulation. Differences in social
14
identity and status anxiety do impact the probability of belonging to a subpopulation,
15
however, in which way needs further more detailed exploration. Especially, as the findings for
16
identification with income and education were in opposing directions.
17
Types of Social Status
18
We found four other subpopulations. Three of them (education-based justifiers,
19
education-based rejectors, and income-based justifiers) showed a pattern that is partly
20
consistent with SJT claims depending on the measure of social status. It appears that the
21
precise operationalization of social status is crucial. SJT’s predictions related to social status
22
treat social status in a relatively unidimensional way. That is, it is implied that groups range
23
on a continuum from disadvantaged to advantaged. However, our findings suggest that
24
different measures of social status have different associations with system-justifying attitudes.
25

(Dis-)Advantaged System Justifiers
22
If SJT wishes to incorporate these heterogeneous effects, they will need to integrate a more
1
nuanced approach to social status.
2
One way these three subpopulations with mixed support differ from the Justifier and
3
Rejectors subpopulations is that the associations between the measures of social status were
4
inconsistent. For example, education and subjective income were unrelated or negatively
5
related. That is, higher educated individuals felt it was less easy to live comfortably with their
6
income. Feelings of deprivation were mostly unrelated to education and income in these
7
subpopulations with mixed support. It appears that when status indicators are inconsistently
8
related, whether there is clear support for SJT or a clear rejection of SJT is also inconsistent.
9
This suggests that in communities or countries where the status indicators are not consistently
10
associated with each other, we might expect more inconsistent relations between status and
11
system-justifying attitudes.
12
Some readers may doubt that education is still a valid indicator of SES. On the one
13
hand, the number of individuals with higher education has increased steadily in the last
14
decades with currently an average of 60% of young people in OECD countries entering higher
15
education over their lifetime (OECD, 2019). On the other hand, individuals are significantly
16
less likely to attend higher education if their parents do not hold a higher education degree or
17
if their parents are immigrants (OECD, 2019). Thus, education is still highly dependent on
18
family background and social class. At the same time, the increase of higher educated
19
individuals also increases competition on the job market. If more higher educated individuals
20
are on the job market, the less companies need to compete for their labour and offer attractive
21
conditions. Therefore, unemployment rates among higher educated young people have risen,
22
especially after the economic crises in 2008 (Bell & Blanchflower, 2011). Nonetheless, higher
23
educated individuals are on average less likely to be unemployed in general and to suffer from
24
long-term unemployment than lower educated individuals (Núñez & Livanos, 2010). These
25
findings and trends suggest that education is still one possible indicator of social status.
26

(Dis-)Advantaged System Justifiers
23
The potential changing meaning of education as a measure of status highlights the
1
importance of including multiple status indicators. This helps build a broader understanding
2
of how status is associated with system-justifying attitudes. One difference between our
3
measures of status is that education is a relatively objective measure, whereas the other two
4
measures were more subjective. This raises the question as to whether the status-justification
5
association is stronger for objective measures compared to subjective measures of social
6
status. Directionally, we see that education correlates more strongly with economic system
7
justification than does income; however, our analysis is not designed to answer this question.
8
Studies with additional measures of system justification attitudes would help to understand
9
what type of status indicators matter most.
10
Alternatives
11
The Alternatives subpopulation stood out as having relatively weak associations. In
12
particular, the system justification items, and the relative deprivation items were only weakly
13
correlated. One possible explanation that we considered was that people in this group were
14
inattentive and the subpopulation captures people with ‘random’ answers. We investigated
15
this by examining whether such random patterns emerged on other scales for this
16
subpopulation. However, for other scales we found high and reliable scores (e.g., the trust
17
scale has a reliability of Cronbach’s α = .87). Therefore, we do not believe that the weak
18
correlations are necessarily due to inattentive participants.
19
Stability Across Countries and Time
20
We tested the two claims of SJT in a combined sample from four European countries
21
and also in each country separately (see supplemental materials). The countries differ
22
regarding multiple aspects, including their economic power and political orientation of the
23
government in power. Yet, the subpopulations we identified – especially Justifiers and
24
Rejectors – are remarkably similar across countries. We found that an average of 80% of
25
individuals who were classified as Justifiers or Rejectors in the full sample were also in that
26

(Dis-)Advantaged System Justifiers
24
category in the separate country analyses. For the other subpopulations, this number was
1
lower. There are two potential reasons for that. First, a methodological explanation. The CCA
2
algorithm aims to detect a moderate number of classes and therefore when sample size
3
decreases (i.e., each country has only ~ ¼ of the full sample size) the number of potential
4
classes that are detected decreases as well. This feeds directly into the second explanation,
5
which is that the Justifiers and Rejectors are the two “core” subpopulations, while the others
6
are more flexible and dependent on context.
7
Although we do find stability across countries, our analyses do not allow any
8
conclusions on how stable the subpopulations are across time and how the interrelations
9
between SES and system-justifying attitudes are formed. Future research should explore these
10
questions further. For example, exploring if similar subpopulations can be found in other
11
European nations and across the world or using longitudinal designs to examine how the
12
interrelations between beliefs (i.e., the subpopulations) are formed. Further, such studies
13
could explore which country-level factors or context factors can explain the emergence of
14
alternative subpopulations.
15
Conclusion
16
We suspect that some people will read about our findings and think that SJT is
17
vindicated because we find support for the theory. We suspect that others will read about
18
these same findings and think that SJT is rebuked because we find that most people do not
19
support the theory. However, we want to push back against this dichotomous thinking.
20
Rather, our approach here suggests that SJT principles may be useful descriptions of people,
21
but they are not descriptions of a majority of people. This is both a good sign for the theory (it
22
works for some people), but also speaks against the theory as a broad description of how
23
people reason about their political systems. In this way, it is limited and circumscribed.
24
Considering a theory, such as SJT, in this way requires that scientists engage in dialectical
25
thinking and to consider the issue at hand from multiple, sometimes contradicting
26

(Dis-)Advantaged System Justifiers
25
perspectives. More practically, it means that a key theoretical task for people interested in
1
system justification processes is to a priori identify the subsamples in which different
2
processes occur. Our conclusions here show the theoretical importance of expanding our
3
methodological toolkits. By expanding our toolkits, we are able to better understand the
4
conditional and contextual nature of system justification processes.
5

(Dis-)Advantaged System Justifiers
1
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10
11

(Dis-)Advantaged System Justifiers
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Table 1. Regression results using economic system justification as the criterion.
Predictor
b
b
95% CI
[LL, UL]
sr2
sr2
95% CI
[LL, UL]
Fit
Difference
(Intercept)
3.00**
[2.94, 3.06]
Income
0.18**
[0.15, 0.20]
.04
[.03, .05]
Education
-0.10**
[-0.15, -0.05]
.00
[.00, .01]
Relative Deprivation
-0.01
[-0.04, 0.02]
.00
[.00, .00]
Spain
0.11**
[0.04, 0.19]
.00
[.00, .01]
UK
-0.12**
[-0.19, -0.05]
.00
[.00, .01]
Poland
0.20**
[0.13, 0.26]
.01
[.00, .01]
R2 = .056**
95% CI [.05,.07]
Including covariates
(Intercept)
2.94**
[2.88, 3.00]
Income
0.17**
[0.15, 0.20]
.04
[.03, .05]
Education
-0.08**
[-0.13, -0.04]
.00
[.00, .00]
Relative Deprivation
-0.00
[-0.04, 0.03]
.00
[.00, .00]
Spain
0.12**
[0.05, 0.21]
.00
[.00, .01]
UK
-0.12**
[-0.19, -0.05]
.00
[.00, .01]
Poland
0.22**
[0.15, 0.27]
.01
[.00, .01]
Age
0.00**
[0.00, 0.01]
.01
[.00, .01]
Gender
0.09**
[0.04, 0.13]
.00
[.00, .01]
R2 = .062**
ΔR2 = .009**
95% CI [.05,.08]
95% CI [.00, .01]
Note. A significant b-weight indicates the semi-partial correlation is also significant. b represents unstandardized regression weights. sr2 represents
the semi-partial correlation squared. LL and UL indicate the lower and upper limits of a confidence interval, respectively.
* indicates p < .05. ** indicates p < .01.

(Dis-)Advantaged System Justifiers
6
Table 2. Description Subpopulations.
Full Sample
Justifiers
Rejectors
Alternatives
Education-
Based Justifiers
Education-
based Rejectors
Income-based
Rejectors
% Female
51.72%
54.26%
52.40%
51.08%
48.98%
48.06%
51.90%
% Lower educated
58.13%
69.64%
63.22%
54.73%
46.53%
43.61%
41.60%
Oc
cup
atio
n
% Full time employed
54.77%
52.27%
55.84%
55.72%
56.72%
63.61%
59.54%
% In education
4.52%
5.01%
4.04%
4.31%
5.40%
5.00%
3.43%
% Unemployed
6.76%
6.69%
2.53%
6.47%
4.58%
5.00%
8.02%
% Permanently sick or
disabled
2.78%
3.27%
3.28%
1.66%
2.24%
3.06%
2.67%
% Retired
22.95%
22.63%
24.89%
24.54%
24.43%
16.94%
20.61%
% Carework
6.41%
7.89%
7.51%
5.97%
4.58%
5.56%
4.20%
% Other
1.81%
2.23%
1.90%
1.32%
2.03%
0.83%
1.53%
Ur
ban
izat
ion
% village/ small town
38.88%
41.59%
37.98%
41.45%
37.27%
34.44%
38.17%
% medium/ large town
31.42%
31.55%
30.78%
29.85%
33.10%
30.83%
32.82%
% Suburbs/ big city
29.71%
26.85%
31.25%
28.69%
29.63%
34.72%
29.00%
% Minority
7.86%
7.91%
7.31%
7.46%
6.93%
9.44%
12.46%
Age
49.5 (15.86)
48.57 (15.73)
50.41 (15.57)
49.77 (16.37)
49.98 (16.18)
47.36 (15.87)
48.80 (15.56)
Income
3.00 (1.05)
2.96 (0.90)
2.84 (1.21)
3.23 (1.09)
3.17 (0.82)
3.13 (0.92)
2.87 (1.22)
Political orientation
4.96 (2.47)
5.08 (2.31)
4.84 (2.45)
5.09 (2.39)
4.78 (2.56)
5.12 (2.74)
5.16 (2.66)
System Justification
3.01 (0.88)
3.23 (0.74)
2.85 (0.88)
3.13 (0.48)
2.92 (1.07)
3.10 (1.03)
2.93 (1.01)
SIEL
3.97 (0.76)
3.82 (0.71)
4.05 (0.75)
3.83 (0.72)
4.03 (0.75)
4.11 (0.73)
4.03 (0.98)
PIR
3.80 (0.87)
3.63 (0.78)
3.90 (0.87)
3.67 (0.82)
3.87 (0.89)
3.87 (0.91)
3.88 (1.06)
Status Anxiety
2.93 (1.00)
3.00 (0.83)
2.97 (1.07)
2.83 (0.90)
2.84 (1.00)
2.85 (1.07)
2.91 (1.33)
Trust in Institutions
3.41 (2.21)
3.60 (2.05)
3.12 (2.24)
3.58 (2.15)
3.60 (2.32)
3.49 (2.32)
3.21 (2.60)
Support for violence
against the
government
2.66 (1.20)
2.78 (1.07)
2.70 (1.29)
2.60 (1.13)
2.53 (1.16)
2.60 (1.29)
2.65 (1.39)
Satisfaction with
Democracy
4.12 (2.62)
4.29 (2.34)
3.81 (2.71)
4.31 (2.50)
4.31 (2.66)
4.30 (2.74)
3.97 (3.05)

(Dis-)Advantaged System Justifiers
7
Table 3. Multinominal regression predicting class membership.
Rejectors
Alternatives
Education-based
Justifiers
Education-based
Rejectors
Income-based Rejectors
Odds
Ratios
95% CI
p
Odds
Ratios
95%
CI
p
Odds
Ratios
95%
CI
p
Odds
Ratios
95%
CI
p
Odds
Ratios
95%
CI
p
SIEL
1.36
[1.23;
1.51]
< .001
1.01
[0.89;
1.15]
.844
1.38
[1.22;
1.55]
< .001
1.66
[1.40;
1.96]
< .001
1.35
[1.12;
1.63]
.002
PIR
1.29
[1.18;
1.42]
< .001
1.10
[0.98;
1.24]
.118
1.33
[1.20;
1.48]
< .001
1.33
[1.15;
1.54]
< .001
1.33
[1.12;
1.63]
.001
Education
[ -0.5 = low;
0.5 = high]
1.42
[1.21;
1.67]
< .001
1.72
[1.39;
2.12]
< .001
2.36
[1.97;
2.83]
< .001
2.64
[2.06;
3.40]
< .001
3.38
[2.54;
4.50]
< .001
Subjective
Income
0.92
[0.86;
1.00]
.042
1.19
[1.08;
1.32]
.001
1.11
[1.01;
1.21]
.023
1.06
[0.94;
1.20]
.355
0.84
[0.71;
0.94]
< .001
Relative
Deprivation
1.09
[0.99;
1.20]
.077
0.90
[0.80;
1.02]
.095
0.86
[0.77;
0.96]
.005
0.85
[0.74;
0.98]
.026
0.95
[0.73;
0.96]
.011
Gender [-
0.5 =
female, 0.5
= male]
1.15
[0.99;
1.33]
.069
1.12
[0.92;
1.37]
.248
1.28
[1.08;
1.52]
.004
1.29
[1.05;
1.69]
.019
1.17
[0.80;
1.12]
.529
Political
orientation
0.98
[0.95;
1.01]
.185
1.00
[0.96;
1.04]
.948
0.97
[0.31;
1.00]
.051
1.01
[0.98;
1.08]
.288
1.04
[0.98;
1.10]
.205
Age
1.01
[1.00;
1.01]
< .002
1.00
[1.00;
1.01]
.185
1.01
[1.00;
1.01]
.057
1.00
[0.99;
1.00]
.200
1.00
[1.00;
1.01]
.615
Constant
1.12
[0.95;
1.21]
.056
0.37
[0.31;
0.43]
< .001
0.49
[0.43;
0.57]
< .001
0.16
[0.13;
0.20]
< .001
0.11
[0.09;
0.15]
< .001
Note. Observation 5,145. Reference group = Justifiers.

(Dis-)Advantaged System Justifiers
8
Table 4.
Regression results using violence as the criterion
Predictor
b
b
95% CI
[LL, UL]
sr2
sr2
95% CI
[LL, UL]
Fit
Difference
(Intercept)
2.46**
[2.39, 2.53]
Economic System Justification
-0.02
[-0.06, 0.01]
.00
[.00, .00]
Relative Deprivation
0.47**
[0.44, 0.51]
.11
[.09, .12]
Subjective Income
-0.05**
[-0.08, -0.02]
.00
[.00, .00]
Education
-0.02
[-0.08, 0.04]
.00
[.00, .00]
Spain
-0.08
[-0.17, 0.00]
.00
[.00, .00]
UK
0.05
[-0.03, 0.13]
.00
[.00, .00]
Poland
0.73**
[0.65, 0.81]
.05
[.04, .06]
R2 = .240**
95% CI [.22,.26]
(Intercept)
2.53**
[2.45, 2.61]
Economic System Justification
-0.03
[-0.07, 0.00]
.00
[.00, .00]
Relative Deprivation
0.48**
[0.44, 0.51]
.11
[.09, .13]
Subjective Income
-0.05**
[-0.08, -0.02]
.00
[.00, .00]
Education
-0.02
[-0.08, 0.05]
.00
[.00, .00]
Rejectors
-0.13**
[-0.20, -0.06]
.00
[.00, .00]
Alternatives
-0.06
[-0.16, 0.03]
.00
[.00, .00]
Education-based Justifiers
-0.09
[-0.18, -0.00]
.00
[.00, .00]
Education-based Rejectors
-0.05
[-0.19, 0.08]
.00
[.00, .00]
Income-based Rejectors
-0.01
[-0.15, 0.12]
.00
[.00, .00]
Spain
-0.08
[-0.16, -0.00]
.00
[.00, .00]
UK
0.05
[-0.03, 0.13]
.00
[.00, .00]
Poland
0.73**
[0.65, 0.81]
.05
[.04, .06]
R2 = .241**
ΔR2 = .002*
95% CI [.22,.26]
95% CI [.00, .01]
Note. A significant b-weight indicates the semi-partial correlation is also significant. b represents unstandardized regression weights. sr2 represents the semi-
partial correlation squared. LL and UL indicate the lower and upper limits of a confidence interval, respectively. * indicates p < .05. ** indicates p < .01.

(Dis-)Advantaged System Justifiers
9
Table 5.
Regression results using trust in institutions as the criterion
Predictor
b
b
95% CI
[LL, UL]
sr2
sr2
95% CI
[LL, UL]
Fit
Difference
(Intercept)
4.05**
[3.94, 4.17]
Economic System Justification
0.48**
[0.42, 0.55]
.04
[.03, .05]
Relative Deprivation
-0.65**
[-0.72, -0.58]
.06
[.05, .07]
Subjective Income
0.13**
[0.07, 0.19]
.00
[.00, .01]
Education
-0.05
[-0.18, 0.06]
.00
[.00, .00]
Spain
-0.70**
[-0.86, -0.54]
.01
[.01, .02]
UK
-0.28**
[-0.44, -0.12]
.00
[.00, .00]
Poland
-1.30**
[-1.44, -1.14]
.04
[.03, .05]
R2 = .191**
95% CI [.17,.21]
(Intercept)
4.21**
[4.05, 4.35]
Economic System Justification
0.47**
[0.40, 0.54]
.03
[.02, .04]
Relative Deprivation
-0.65**
[-0.72, -0.58]
.06
[.05, .07]
Subjective Income
0.12**
[0.06, 0.18]
.00
[.00, .01]
Education
-0.04
[-0.15, 0.08]
.00
[.00, .00]
Rejectors
-0.27**
[-0.40, -0.13]
.00
[.00, .00]
Alternatives
-0.17
[-0.37, 0.02]
.00
[.00, .00]
Education-based Justifiers
-0.09
[-0.25, 0.08]
.00
[.00, .00]
Education-based Rejectors
-0.22
[-0.47, 0.03]
.00
[.00, .00]
Income-based Rejectors
-0.43**
[-0.68, -0.16]
.00
[.00, .00]
Spain
-0.71**
[-0.87, -0.54]
.01
[.01, .02]
UK
-0.28**
[-0.43, -0.12]
.00
[.00, .00]
Poland
-1.31**
[-1.45, -1.17]
.04
[.03, .05]
R2 = .194**
ΔR2 = .003**
95% CI [.18,.22]
95% CI [.00, .01]
Note. A significant b-weight indicates the semi-partial correlation is also significant. b represents unstandardized regression weights. sr2 represents the semi-
partial correlation squared. LL and UL indicate the lower and upper limits of a confidence interval, respectively. * indicates p < .05. ** indicates p < .01.

(Dis-)Advantaged System Justifiers
10
Table 6.
Regression results using satisfaction with democracy as the criterion
Predictor
b
b
95% CI
[LL, UL]
sr2
sr2
95% CI
[LL, UL]
Fit
Difference
(Intercept)
4.77**
[4.63, 4.92]
Economic System Justification
0.59**
[0.51, 0.67]
.04
[.03, .05]
Relative Deprivation
-0.69**
[-0.77, -0.61]
.05
[.04, .06]
Subjective Income
0.20**
[0.12, 0.28]
.01
[.00, .01]
Education
-0.17*
[-0.30, -0.03]
.00
[.00, .00]
Spain
-0.36**
[-0.55, -0.18]
.00
[.00, .00]
UK
-0.46**
[-0.63, -0.29]
.00
[.00, .01]
Poland
-1.29**
[-1.49, -1.09]
.03
[.02, .04]
R2 = .161**
95% CI [.14,.18]
(Intercept)
4.87**
[4.67, 5.04]
Economic System Justification
0.58**
[0.50, 0.66]
.04
[.03, .05]
Relative Deprivation
-0.68**
[-0.76, -0.60]
.05
[.04, .06]
Subjective Income
0.20**
[0.12, 0.28]
.01
[.00, .01]
Education
-0.17*
[-0.31, -0.01]
.00
[.00, .00]
Rejectors
-0.19*
[-0.36, -0.01]
.00
[.00, .00]
Alternatives
-0.11
[-0.34, 0.13]
.00
[.00, .00]
Education-based Justifiers
-0.02
[-0.22, 0.19]
.00
[.00, .00]
Education-based Rejectors
-0.07
[-0.37, 0.23]
.00
[.00, .00]
Income-based Rejectors
-0.25
[-0.57, 0.08]
.00
[.00, .00]
Spain
-0.37**
[-0.54, -0.17]
.00
[.00, .00]
UK
-0.46**
[-0.64, -0.28]
.00
[.00, .01]
Poland
-1.30**
[-1.48, -1.11]
.03
[.02, .04]
R2 = .162**
ΔR2 = .001
95% CI [.15,.18]
95% CI [.00, .00]
Note. A significant b-weight indicates the semi-partial correlation is also significant. b represents unstandardized regression weights. sr2 represents the semi-
partial correlation squared. LL and UL indicate the lower and upper limits of a confidence interval, respectively. * indicates p < .05. ** indicates p < .01.