College Students’ Political Attitudes Affect Negative Stereotypes about Social Groups

Abstract

This study examined the relations between political attitudes and negative stereotypes in undergraduates by employing 4 measures of stereotypes: modern sexism, modern racism, feelings about 20 social groups, and ratings of the intelligence of these social groups. It was hypothesized that conservatives and Republicans alike would show more evidence of negative stereotypes than liberals and Democrats, especially for disadvantaged social groups. The study revealed that, indeed, Republicans showed stronger evidence of negative stereotypes but that Democrats also harbor some biases. Importantly, the social groups for whom Democrats and Republicans show negative stereotypes differed greatly. Republicans had considerably more negative stereotypes against racial and religious minorities, and particularly against individuals who do not identify with the cis-gender, heterosexual norm. Thus, the targets of Republicans’ stereotypes were groups that have traditionally been subjected to discrimination. Democrats, on the other hand, held stronger negative stereotypes against groups that are more politically powerful, such as Caucasians and Christians.

1. Introduction

In this time of political polarization in the US, tensions among social groups from different racial or ethnic backgrounds, political affiliations, religions, sexual orientations, and sexual identities run high. Against this backdrop, the present study examines the relationship between political attitudes and negative stereotypes in college students.

Stereotypes are generally defined as beliefs about social groups (Ashmore and DelBoca 1981). Stereotypes are not by definition negative, nor are they necessarily inaccurate (Jussim et al. 2015). However, negative stereotypes or prejudice are typically overgeneralizations of social groups and are associated with negative affect. Because prejudice has become a loaded term, this paper will use the more neutral term negative stereotype.

1.1. Aims of the Study

The aim of this study is to examine the relationship between political attitudes and negative stereotypes about social groups. This topic has received a lot of research attention. However, findings have been far from conclusive. During the past few years, two research strands on the relation between political attitudes and stereotypes have evolved, with one strand finding that conservatives show more negative stereotypes than liberals do and a second strand finding that political attitudes are not related to negative stereotypes but simply reveal in-group favoritism. The two research strands will be described below. An important goal of the present study is to elucidate which of the two research strands receives more empirical support. This is accomplished by (a) using four separate operational definitions of negative stereotypes and (b) by assessing attitudes towards a large number of social groups. This approach should provide greater convergent validity than previous studies.

1.2. Review of Research on the Relation between Political Attitudes and Negative Stereotypes

One research strand on the relation between political attitudes and negative stereotypes examines what has been described as a “prejudice gap” (Chambers et al. 2013). It finds that conservatives exhibit more stereotypical information processing than liberals (e.g., Jost et al. 2018), which is associated with greater prejudice. For example, social conservatism regarding issues such as abortion or LGBTQ rights is correlated with racial and homophobic prejudice (Hodson and Dhont 2015). Conservatism also correlates with Global Belief in a Just World (GBJW; Beyer 2020; Dittmar and Dickinson 1993), the belief that good things happen to good people and bad things to bad people. GBJW is often used to justify the status quo; e.g., if poor people are viewed as lazy, one does not feel morally obligated to help them as they are assumed to be responsible for their problems. GBJW is also strongly correlated with certain measures of stereotyping, such as modern sexism (Beyer 2020). Previous research on the relationship between conservatism and negative stereotypes also found that Trump supporters compared to supporters of Democratic candidates are more sexist (Bock et al. 2017; Monteith and Hildebrand 2020; Rothwell et al. 2019; Setzler and Yanus 2018) and racist (Bracic et al. 2019; Setzler and Yanus 2018; Shook et al. 2020). Thus, some researchers have found that politically conservative individuals and those high in GBJW are less empathetic and harbor more negative stereotypes towards racial and sexual minorities than liberals and individuals low in GBJW.

However, some researchers have challenged the conclusion that political conservatives, more so than liberals, display information processing biases and negative stereotypes against social groups. A recent meta-analysis found that liberals and conservatives show similar information processing biases (Ditto et al. 2018, but see the critique by Baron and Jost 2019). In a similar vein, both conservatives and liberals have been found to be equally biased against those with opposing viewpoints (Brandt et al. 2014; Chambers et al. 2013). Specifically, liberals are biased against conservatives and conservatives against liberals (Beyer 2020; Crawford and Brandt 2019). In addition, conservatives and liberals alike favored discrimination against those who violated their values (Wetherell et al. 2013). This suggests that regardless of one’s specific political leanings, those with strong political convictions are biased against people with opposing viewpoints. Brandt et al. (2014) referred to this as the “ideological-conflict hypothesis.” Social Identity Theory (e.g., Tajfel 1982) would predict a similar in-group bias. In the same vein, the similarity-liking principle (Byrne 1971) also claims that we favor individuals with similar values and dislike those whose values conflict with our own. Indeed, similarity in political attitudes even affects romantic interest (Mallinas et al. 2018).

Thus, while some research suggests that political conservatism is more likely to cause negative stereotypes of outgroups than liberalism does, other research finds that negative stereotypes are the inevitable result of in-group biases held by conservatives and liberals alike. These two conflicting sets of results have not been reconciled yet. There are methodological problems that have hampered progress in resolving the disparate findings. For example, much prior research has only examined stereotypes against a few social groups (for an exception, see Chambers et al. 2013), confounding dislike of a social group (e.g., a racial minority) with dislike of that group’s political ideology (e.g., African Americans’ perceived liberalism; see Brandt et al. 2014).

A prior study (Beyer 2020) examined stereotypes against 15 social groups with the goal of including a variety of social groups that align with either conservative or liberal ideologies. In Beyer’s 2020 study, college students strongly disliked people from the opposite side of the political spectrum, which supports the second strand of research suggesting that both conservatives and liberals exhibit biases. On the other hand, conservative participants felt more negative about racial, religious, and sexual minorities than liberals did. Specifically, participants high in conservatism showed more negative feelings towards individuals who are often on the receiving end of discrimination, such as African Americans, Hispanics, female and male homosexuals, and Muslims. This suggests a stronger bias among conservatives, providing support for the first strand of research.

However, matters are even more complex. Beyer (2020) argued that it is not enough to assess who holds more negative stereotypes but that we also need to consider the targets of negative stereotypes and their potential vulnerability to negative stereotypes and discrimination. In terms of real-world implications, it is important to consider the potential impact of negative stereotypes on social groups. The negative stereotypes held by conservatives were aimed at social groups that have historically been the targets of discrimination, including racial, ethnic, religious, and sexual orientation minorities (Beyer 2020). In contrast, the negative stereotypes held by liberals were often aimed at those in power, such as Caucasians or Christians, who are much less vulnerable to the effects of negative stereotypes.

1.3. Operationalizing Negative Stereotypes

In this paper, the term negative stereotype refers to a negative attitude toward a social group. Because the results regarding the relationship between political attitudes and negative stereotypes may be affected by the particular measurement used, the present research employed four different operationalizations of negative stereotypes: modern sexism, modern racism, feelings about 20 social groups, and intelligence ratings of the 20 social groups. If the results are consistent across these four operationalizations, this will increase confidence that the results are not spurious but demonstrate a consistent pattern. The literature for each of these operational definitions of negative stereotypes will be reviewed in the appropriate sections in the Discussion.

The present study also assesses reported exposure to social groups and personal experience with discrimination and collects data on voting intentions for the 2020 US presidential election.

1.4. Hypotheses

It was hypothesized that individuals from either political party show strong negative stereotypes about members of the other political party, providing some evidence for in-group bias. It was not expected that liberals were without bias. However, based on Beyer’s (2020) results, conservatives or those identifying as Republican were hypothesized to exhibit more negative stereotypes of several disadvantaged racial, ethnic, religious, and sexual minority groups than liberals or Democrats would. It was also hypothesized that liberal individuals or those identifying as Democrats, compared to conservatives or Republicans, hold more negative views of powerful social groups, such as Caucasians.

2. Method

The data were collected in the Spring and Fall of 2019 when it was fairly certain that Trump would receive the Republican nomination for president, but the field of contenders for the Democratic nomination was still wide open.

2.1. Participants

This study examined interrelations among conservatism, GBJW, and 4 different operationalizations of negative stereotypes: modern sexism, modern racism, feelings about 20 social groups, and intelligence ratings of the 20 social groups in 116 (79 females, 37 males) introductory psychology students at a small, public university in the midwestern US. The students indicated their age in ranges: 111 were between 18 and 24 years old, 4 between 25 and 30, and 1 between 31 and 40. Participants indicated their race (75 Caucasian, 17 African American, 10 Multi-racial, 6 Hispanic, 6 Asian, and 2 Native American) and religious affiliations (70 Christian, 19 non-religious, 18 Atheist or Agnostic, 5 Muslim, and 4 other).

2.2. Materials

Measures of negative stereotypes. A total of four different operationalizations of negative stereotypes were used: scores on the Modern Sexism Scale (Swim et al. 1995), the Modern Racism Scale (McConahay 1986), feelings about 20 social groups, and assessment of the intelligence of these social groups (African Americans, Asians, atheists, bisexuals, Catholics, Caucasians, Christians, Democrats, female homosexuals, homeless, immigrants, intellectually disabled, Jews, male homosexuals, men, Muslims, physically disabled, Republicans, transgender individuals, and women).

The Modern Sexism Scale consists of 8 statements such as “discrimination against women is no longer a problem in the US” and “women often miss out on good jobs due to sex discrimination” (reverse scored), with responses on a scale of 1 (strongly disagree) to 5 (strongly agree; Swim et al. 1995). Reliability ranges from 0.75 to 0.84 (Swim et al. 1995). The Modern Racism Scale (McConahay 1986) consists of 7 items on a 1 (strongly disagree) to 5 (strongly agree) Likert scale. A sample item is, “discrimination against Blacks is no longer a problem in America”. Cronbach’s alpha is 0.82 (McConahay 1986). Participants indicated their feelings about each social group on a 1 (extremely negative) to 7 (extremely positive) scale and indicated how intelligent they believed members of each of the 20 social groups to be on a 1 (very unintelligent) to 5 (very intelligent) scale.

Additional measures. Participants reported their experiences with racial, gender, and religious discrimination on a 1 (never) to 5 (very often) scale. The survey also assessed how often participants interact with members of the 20 social groups on a 1 (never) to 5 (very frequent) scale. In addition, participants completed the GBJW Scale (Lipkus 1991), a 7-item inventory where participants rank their feelings about statements on a scale from 1 (strongly disagree) to 6 (strongly agree). Sample statements include, “I feel that people get what they are entitled to have” and “I feel that the world is a fair place” (Lipkus 1991). Reliability for GBJW ranges from 0.79 to 0.82 (Lipkus 1991).

Participants indicated their voting intentions for the 2020 US presidential election, their political and religious affiliations, and answered demographic questions. Note that this study was conducted in Spring and Fall 2019, a year prior to the 2020 US presidential election and before candidates had been chosen; thus, the survey asked about voting for the candidate chosen by a particular party.

2.3. Procedure

Participants completed the measures in a Qualtrics survey administered in a computer lab. They first filled out the Modern Sexism Scale, then answered how positively they felt about the 20 social groups, followed by the Modern Racism Scale. Participants then rated the intelligence of members of the 20 social groups, filled out the GBJW scale, and rated how often they had experienced discrimination based on race, religion, and gender. They were then asked about the frequency of contact with members of the 20 social groups. The survey also inquired whom they intended to vote for and ended with demographic questions. The survey took about 35 min to complete. Students received class credit as an incentive for participation. Participation was voluntary.

3. Results

3.1. Political Affiliation and Voting Intentions

Participants were most likely to identify as having no political affiliation (44%), followed by Democrat (37.9%), Republican (15.5%), and member of a third party (2.6%). To determine if there was a gender gap in political affiliation, I conducted a chi-square analysis by gender and the three most prevalent choices of political affiliation (Democrat, no party affiliation, Republican). This analysis was significant, χ²(2, 113) = 8.59, p = 0.02. Women were about twice as likely to identify as Democrat compared to men (46.2% versus 22.9%) but almost three times less likely to identify as Republican (10.3% versus 28.6%). Similar percentages of women and men did not identify with a political party (43.6% versus 48.6%).

Participants who indicated for whom they would vote in the 2020 US presidential election (see

Table 1. Gender Differences in Voting Intentions for the 2020 US Presidential Election.

Voting Intention	Entire Sample	Women	Men
Undecided	43.1	45.6	37.8
Democratic candidate	32.8	39.2	18.9
Republican candidate	12.9	7.6	24.3
Do not intend to vote	7.8	5.1	13.5
No answer	3.4	2.5	5.4

Note. Numbers refer to percentages within a column.

) were most likely to say that they were undecided (43.1%), followed by intending to vote for a Democratic presidential candidate (32.8%), a Republican candidate (12.9%), not intending to vote (7.8%), and declining to answer (3.4%). To determine if there was a gender gap in voting intentions, a chi-square analysis by gender and the four most prevalent choices (Democrat, Republican, undecided, will not vote) was conducted. A substantial gender gap in voting intentions for the 2020 US presidential election emerged, χ²(3, 112) = 11.40, p = 0.02 (see Table 1). While many women and men were undecided, women were twice as likely to indicate they would vote for a Democratic candidate and about three times less likely than men to indicate they would vote for a Republican candidate. Only 5.2% of women but 14.3% of men indicated that they did not intend to vote.

3.2. Interrelations among Four Measures of Negative Stereotypes: Modern Sexism, Modern Racism, Feelings about Social Groups, Assessments of Perceived Intelligence

Note that all correlation coefficients below are r(116).

Modern sexism. As

Table 2. Correlations among Liking for Social Groups, Modern Racism, Modern Sexism, Conservatism, and GBJW.

	Modern Sexism	Modern Racism	Conservatism	GBJW
African Americans	−0.22 *	−0.37 ***	−0.19 *	−0.08
Asians	−0.14	−0.16	0.02	−0.03
Atheists	−0.10	−0.20 *	−0.31 **	0.04
Bisexuals	−0.28 **	−0.35 ***	−0.16	0.05
Catholics	0.02	0.06	0.19 *	0.15
Caucasians	0.18	0.11	0.19 *	0.23 *
Christians	0.04	0.01	0.28 **	0.12
Democrats	−0.27 **	−0.31 **	−0.31 **	−0.11
Female Homosexuals	−00.31 **	−0.19 *	−0.06	−0.02
Homeless	−0.23 **	−0.18	0.04	−0.05
Immigrants	−0.22 *	−0.27 **	−0.11	−0.06
Intellectually Disabled	−0.18 *	−0.18	0.02	−0.01
Jews	−0.21 *	−0.19 *	0.03	−0.11
Male Homosexuals	−0.37 ***	−0.42 ***	−0.18	−0.11
Men	0.10	0.03	0.04	0.25 *
Muslims	−0.23 *	−0.18	−0.09	−0.08
Physically Disabled	−0.22 *	−0.26 **	−0.04	0.00
Republicans	0.20 *	0.20 *	0.18 *	0.21 *
Transgender	−0.39 ***	−0.41 ***	−0.14	−0.11
Women	−0.03	−0.21 *	0.01	0.02
Modern Sexism		0.64 ***	0.30 **	0.45 ***
Modern Racism			0.32 **	0.43 ***
Conservatism				0.27 **

Notes. * p < 0.05; ** p < 0.01; *** p < 0.0001.

shows, modern sexism was very highly correlated with modern racism, 0.64, p = 0.0001. Participants high in modern sexism felt more negatively about African Americans, −0.22, p = 0.02, bisexuals, −0.28, p = 0.003, Democrats, −0.27, p = 0.004, female homosexuals, −0.31, p = 0.001, the homeless, −0.23, p = 0.01, immigrants, −0.22, p = 0.02, intellectually disabled people, −0.18, p = 0.05, Jews, −0.21, p = 0.03, male homosexuals, −0.37, p = 0.0001, Muslims, −0.23, p = 0.02, physically disabled people, p = 0.02, and transgender individuals, −0.39, p = 0.0001, while feeling more positively about Republicans, 0.20, p = 0.03.

Modern racism. Table 2 indicates that participants high in modern racism felt more negatively about African Americans, −0.37, p = 0.0001, atheists, −0.20, p = 0.03, bisexuals, −0.35, p = 0.0001, Democrats, −0.31, p = 0.001, female homosexuals, −0.19, p = 0.04, immigrants, −0.27, p = 0.004, Jews, −0.19, p = 0.04, male homosexuals, −0.42, p = 0.0001, physically disabled individuals, −0.26, p = 0.005, transgender individuals, −0.41, p = 0.0001, and women, −0.21, p = 0.03, while feeling more positively about Republicans, 0.20, p = 0.03. Individuals high in modern racism also held marginally more negative views of Asians, −0.16, p = 0.08, the homeless, −0.18, p = 0.06, intellectually disabled individuals, −0.18, p = 0.06, and Muslims, −0.18, p = 0.06.

Feelings about social groups. Feelings about the 20 social groups were significantly intercorrelated, all rs > 0.22, ps < 0.02, with but a few exceptions. Liking for Republicans was uncorrelated with liking for Democrats, 0.02, p = 0.82, female homosexuals, 0.16, p = 0.09, immigrants, 0.09, p = 0.33, male homosexuals, 0.18, p = 0.06, and women, = 0.15, p = 0.12. Feelings for atheists and Christians were uncorrelated, −0.02, p = 0.87, as were the feelings for Caucasians and Democrats, 0.17, p = 0.08, and Caucasians and transgender individuals, 0.18, p = 0.06.

Perceived intelligence ratings of social groups. The perceived intelligence ratings of the 20 social groups were highly intercorrelated, rs > 22, ps > 0.01.

Table 3. Correlations among Ratings of Intelligence, Modern Sexism, Modern Racism, Conservatism, and GBJW.

	Modern Sexism	Modern Racism	Conservatism	GBJW
African Americans	−0.26 **	−0.35 ***	−0.13	−0.05
Asians	−0.14	−0.08	0.02	−0.05
Atheists	−0.14	−0.26 **	−0.18 *	−0.08
Bisexuals	−0.30 **	−0.29 **	−0.06	0.03
Catholics	−0.25 **	−0.17	−0.06	0.03
Caucasians	−0.06	−0.05	−0.06	0.05
Christians	−0.08	−0.08	0.06	0.05
Democrats	−0.13	−0.19 *	−0.16	−0.02
Female Homosexuals	−0.19 *	−0.14	0.02	0.11
Homeless	−0.27 **	−0.29 **	−0.10	−0.15
Immigrants	−0.22 *	−0.20 *	−0.13	−0.00
Intellectually Disabled	−0.31 **	−0.24 **	−0.07	−0.07
Jews	−0.22 *	−0.25 **	−0.03	−0.06
Male Homosexuals	−0.30 **	−0.37 ***	−0.05	−0.03
Men	−0.01	0.01	0.01	0.18
Muslims	−0.18 *	−0.11	−0.08	−0.00
Physically Disabled	−0.26 **	−0.23 **	−0.01	−0.03
Republicans	0.03	−0.03	−0.02	0.07
Transgender	−0.35 ***	−0.42 ***	−0.08	−0.05
Women	−0.12	−0.20 *	0.01	0.09
Modern Sexism		0.64 ***	0.30 **	0.45 ***
Modern Racism			0.32 **	0.43 ***
Conservatism				0.27 **

Note. * p < 0.05; ** p < 0.01; *** p < 0.0001.

reveals that modern sexism correlated negatively with intelligence ratings of African Americans, −0.26, p = 0.005, bisexuals, −0.30, p = 0.001, Catholics, −0.25, p = 0.008, female homosexuals, −0.19, p = 0.04, the homeless, −0.27, p = 0.004, immigrants, −0.22, p = 0.02, intellectually disabled individuals, −0.31, p = 0.001, Jews, −0.22, p = 0.02, male homosexuals, −0.30, p = 0.001, Muslims, −0.18, p = 0.05, physically disabled individuals, −0.26, p = 0.006, and transgender individuals, −0.35, p = 0.0001. Modern racism correlated negatively with intelligence ratings of African Americans, −0.35, p = 0.0001, atheists, −0.26, p = 0.004, bisexuals, −0.29, p = 0.002, Democrats, −0.19, p = 0.04, the homeless, −0.29, p = 0.002, immigrants, −0.20, p = 0.03, intellectually disabled individuals, −0.24, p = 0.008, Jews, −0.25, p = 0.007, male homosexuals, −0.37, p = 0.0001, physically disabled individuals, −0.23, p = 0.01, transgender individuals, −0.42, p = 0.0001, and women, −0.20, p = 0.03.

3.3. Interrelations among Conservatism, GBJW, and Measures of Negative Stereotypes

Conservatism. As can be seen in Table 2, conservatism was correlated with modern sexism, 0.30, p = 0.001, and modern racism, 0.32, p = 0.0001. Participants high in conservatism felt less positively about minorities such as African Americans, −0.19, p = 0.04, and those with opposing viewpoints such as atheists, −0.31, p = 0.001, and Democrats, −0.31, p = 0.001, but felt more positively about Catholics, 0.19, p = 0.04, Caucasians, 0.19, p = 0.05, Christians, 0.28, p = 0.003, and Republicans, 0.18, p = 0.05. Conservatism was negatively correlated with intelligence ratings of atheists, 0.18, p = 0.05, but no other social groups.

GBJW. GBJW was highly correlated with both modern sexism, 0.45, p = 0.0001, and modern racism, 0.43, p = 0.0001. Participants who rated Caucasians, 0.23, p = 0.02, men, 0.25, p = 0.007, and Republicans favorably, 0.21, p = 0.02, tended to score higher on GBJW.

3.4. Political Affiliation and Negative Stereotypes

Democrats (44) and Republicans (18) were compared in their stereotypes about the 20 social groups. There were significant differences in the positivity ratings of the 20 social groups (see

Table 4. Mean Ratings of Liking for 20 Social Groups.

	Entire Sample	Democrats	Republicans
Women	6.1	6.2	5.8
Asians	5.6	5.7	5.3
Physically Disabled	5.5	5.7	5.4
Bisexuals	5.5	5.9 **	4.4
Intellectually Disabled	5.4	5.5	5.5
Female Homosexuals	5.4	5.9 **	4.4
African Americans	5.3	5.7 *	4.7
Immigrants	5.3	5.8 **	4.2
Caucasians	5.2	4.8 **	5.9
Men	5.2	5.2	5.5
Christians	5.2	5.0	5.6
Jews	5.2	5.1	5.3
Muslims	5.2	5.4 *	4.4
Male Homosexuals	5.2	5.5 **	4.1
Catholics	5.1	5	5.4
Democrats	5.0	6.1 ***	3
Transgender	4.9	5.4 **	3.8
Homeless	4.8	4.9	4.7
Atheists	4.6	4.7 *	3.6
Republicans	3.9	3.1 ***	5.1

Notes. Ratings can range from 1 to 7, with 7 being the most favorable. * p < 0.05; ** p < 0.01; *** p < 0.0001 denote significant differences between Democrats and Republicans.

). Democrats rated nine groups significantly more positively than Republicans did: African Americans, F(1, 60) = 5.00, p = 0.03, partial η² = 0.076, atheists, F(1, 60) = 5.12, p = 0.03, partial η² = 0.079, bisexuals, F(1, 60) = 10.20, p = 0.002, partial η² = 0.145, Democrats, F(1, 60) = 88.96, p = 0.0001, partial η² = 0.597, female homosexuals, F(1, 60) = 12.88, p = 0.001, partial η² = 0.177, immigrants, F(1, 60) = 11.93, p = 0.001, partial η² = 0.166, male homosexuals, F(1, 60) = 8.01, p = 0.006, partial η² = 0.118, Muslims, F(1, 60) = 4.63, p = 0.04, partial η² = 0.072, and transgender individuals, F(1, 60) = 9.01, p = 0.004, partial η² = 0.131. The two social groups Republicans rated significantly more positively than Democrats did were Caucasians, F(1, 60) = 7.90, p = 0.007, partial η² = 0.116, and Republicans, F(1, 60) = 17.80, p = 0.0001, partial η² = 0.229.

Table 5. Mean Ratings of Intelligence of 20 Social Groups by Political Affiliation.

	Entire Sample	Democrats	Republicans
Asians	4.4	4.6	4.2
Women	4.3	4.6 *	4.1
Bisexuals	4.0	4.2 *	3.7
African Americans	4.0	4.2	3.8
Female Homosexuals	4.0	4.2	3.8
Jews	4.0	4.0	3.9
Physically Disabled	4.0	4.1	3.9
Democrats	3.9	4.3 ***	3.4
Male Homosexuals	3.9	4.1	3.7
Muslims	3.9	4.1	3.8
Transgender	3.9	4.0	3.7
Christians	3.9	4.0	3.9
Caucasians	3.9	3.8	3.9
Men	3.9	3.9	4.1
Immigrants	3.8	3.9	3.6
Catholics	3.8	3.8	3.8
Atheists	3.7	3.9	3.6
Intellectually Disabled	3.5	3.6	3.4
Homeless	3.3	3.4	3.3
Republicans	3.3	2.9 **	3.9

Notes. 1 = very unintelligent to 5 = very intelligent. * p < 0.05; ** p < 0.01; *** p < 0.0001 denote significant differences between Democrats and Republicans.

displays significant differences in the intelligence ratings of the 20 social groups. Democrats rated bisexuals, F(1, 60) = 4.31, p = 0.04, partial η² = 0.067, Democrats, F(1, 60) = 15.59, p = 0.0001, partial η² = 0.206, and women, F(1, 60) = 4.71, p = 0.03, partial η² = 0.073, as significantly more intelligent than Republicans did. Republicans only rated Republicans as significantly more intelligent than Democrats did, F(1, 60) = 13.54, p = 0.001, partial η² = 0.184.

Table 6. Mean Scores on Modern Sexism, Modern Racism, GBJW, and Conservatism by Political Affiliation.

	Entire Sample	Democrats	Republicans
Modern Sexism	2.4	2.2 **	2.9
Modern Racism	1.9	1.7 **	2.4
GBJW	3.0	2.7 **	3.5
Conservatism	2.6	2.2 ***	3.7

Note. * p < 0.05; ** p < 0.01; *** p < 0.0001 denote significant differences between Democrats and Republicans.

shows that Republicans scored significantly higher than Democrats on modern sexism, F(1, 60) = 13.41, p = 0.001, partial η² = 0.183, modern racism, F(1, 60) = 11.68, p = 0.001, partial η² = 0.163, conservatism, F(1, 60) = 37.78, p = 0.0001, partial η² = 0.386, and GBJW, F(1, 60) = 7.52, p = 0.008, partial η² = 0.111.

Democrats indicated that they had interacted with bisexuals, F(1, 60) = 3.86, p = 0.05, partial η² = 0.060, and Democrats, F(1, 60) = 7.57, p = 0.008, partial η² = 0.112, significantly more often than Republicans did. Republicans indicated that they had interacted with Republicans more, F(1, 60) = 11.00, p = 0.002, partial η² = 0.155.

3.5. Interrelations among Conservatism, GBJW, Modern Sexism, Modern Racism, and Exposure to Social Groups

Individuals high in conservatism were less likely to have interacted with atheists, 0.19, p = 0.04, but more likely to have interacted with Christians, 0.19, p = 0.05. Individuals high in modern sexism were less likely to have interacted with bisexuals, −0.29, p = 0.001, Democrats, −0.25, p = 0.008, female homosexuals, −0.27, p = 0.003, male homosexuals, −0.31, p = 0.001, and transgender individuals, 0.23, p = 0.01. Individuals high in modern racism were less likely to have interacted with bisexuals, −0.34, p = 0.0001, Democrats, −0.26, p = 0.005, male homosexuals, −0.33, p = 0.0001, and transgender individuals, −0.28, p = 0.003. Those high in GBJW were less likely to have interacted with Democrats, −0.22, p = 0.02.

3.6. Experience with Discrimination

Participants indicated their experience with discrimination on a 1 (never) to 5 (very often) scale. There was a highly significant race difference in experience with racial discrimination, F(5, 110) = 8.09, p = 0.0001, partial η² = 0.269. African Americans reported the highest level of discrimination (3.9), followed closely by Asians (3.7), Native Americans (3.5), Other (3.3), and Multi-racial individuals (3.2), with Caucasians scoring by far the lowest (2.2). There was a significant difference in the experience with religious discrimination, F(5, 110) = 4.00, p = 0.002, partial η² = 0.153. Muslims reported very high absolute levels of discrimination (4.4), followed by Other (3.5), with much lower scores for Christians (2.1), Agnostics and Atheists (both 2.0), and those without any religious identification (1.9). There was a significant gender difference in the experience of gender discrimination, F(1, 114) = 24.03, p = 0.0001, partial η² = 0.174. Females reported much higher levels of discrimination (3.1) compared to males (2.0).

4. Discussion

4.1. Political Affiliation and Voting Intentions

One year prior to the 2020 US presidential election, the student participants were most likely to identify as having no political affiliation, followed by identifying as Democrat, Republican, and finally, member of third parties. Women were more than twice as likely to identify as Democrat and almost three times less likely to identify as Republican. Similar percentages of women and men did not identify with a specific political party. Similarly, a substantial gender gap in voting intentions for the 2020 US presidential election emerged (see Table 1). While the majority of both women and men were undecided, women were twice as likely to indicate they would vote for a Democratic candidate and about three times less likely to intend to vote for a Republican candidate. Other researchers have also found a greater likelihood of men intending to vote for Trump (Shook et al. 2020). This gender voting gap was confirmed in the actual 2020 US presidential election (Schmidt 2020).

4.2. Interrelations among Four Measures of Negative Stereotypes: Modern Sexism, Modern Racism, Feelings about Social Groups, Assessments of Intelligence

Modern sexism. As can be seen in Table 2, modern sexism was strongly correlated with modern racism, which has been reported before (e.g., Schaffner et al. 2018; Shook et al. 2020). Participants high in modern sexism felt more negatively about African Americans, bisexuals, Democrats, female and male homosexuals, the homeless, immigrants, intellectually and physically disabled people, Jews, Muslims, and transgender individuals, while feeling more positively about Republicans. Thus, modern sexism related to more negative feelings for 12 and more positive feelings for one of the 20 social groups. Particularly noteworthy for a measure of sexism is that it did not relate to negative feelings for women, but more negative feelings for sexual and religious minorities, individuals with disabilities, and politically powerless individuals (the homeless, immigrants), combined with more positivity for Republicans. Beyer (2020) also found that modern sexism related to negative feelings for several social groups other than women and positive feelings for Republicans.

The practical relevance of this finding is that individuals high in sexism often deny or lack awareness that women are victims of discrimination, which can contribute to actual gender discrimination (Begeny et al. 2020). Thus, if individuals high in modern sexism generalize negative stereotypes against social groups besides women, this may result in discriminatory actions against those social groups as well.

Modern racism. Participants high in modern racism felt significantly more negatively about many of the same groups as those who had scored high in modern sexism: African Americans, bisexuals, Democrats, female and male homosexuals, immigrants, Jews, physically disabled individuals, and transgender individuals. In addition, they felt more negatively about atheists and women. Furthermore, they were marginally more negative towards four additional groups: Asians, the homeless, intellectually disabled individuals, and Muslims. Like those high in modern sexism, individuals high in modern racism felt more positively about Republicans. Thus, modern racism related to significantly more negativity for 11 social groups and marginally more negativity towards an additional four groups that are frequent targets of discrimination while correlating with positivity towards Republicans. As with modern sexism, individuals high in modern racism showed particular disdain for individuals outside the heterosexual norm. Interestingly, modern racism correlated with negativity towards women, whereas modern sexism did not. Thus, both modern sexism and modern racism appear to measure more than just the sexist or racist stereotypes, respectively, they were designed to assess. They seem to tap into a more general tendency to hold negative stereotypes of members of disadvantaged or less powerful groups. In fact, prejudice towards different social groups is highly intercorrelated, at least for explicit measures (Bergh et al. 2012).

Feelings about social groups. Individuals’ feelings about the 20 social groups were the third way that negative stereotypes were operationally defined. These feelings about social groups were highly significantly intercorrelated. Participants who rated one social group negatively tended to rate other social groups negatively as well, replicating similar findings by Beyer (2020) and Chambers et al. (2013). This phenomenon has been described as “generalized prejudice” (for a summary, see Bergh and Akrami 2016). This further corroborates the above statement that inventories designed to measure sexism or racism actually reveal a more global tendency toward negative stereotypes of social groups. In other words, individuals who hold negative views of one disadvantaged group may be predisposed to holding negative views of other disadvantaged groups as well.

Perceived intelligence ratings of social groups. Participants’ perceptions of the intelligence of members of the 20 social groups were examined. Since intelligence is a valued trait, this is yet another operationalization of negative stereotypes about social groups. Modern sexism and modern racism both correlated with more negative intelligence ratings of the same nine disadvantaged and minority groups: African Americans, bisexuals, the homeless, immigrants, intellectually and physically disabled individuals, Jews, male homosexuals, and transgender individuals. In addition, modern sexism correlated negatively with intelligence ratings of Catholics, female homosexuals, and Muslims, while modern racism correlated negatively with intelligence ratings of atheists, Democrats, and women. Thus, this fourth measure of negative stereotypes again reveals the interconnectedness of attitudes towards social groups. Apparently, we do not typically hold negative stereotypes toward just one group. Rather, negative stereotypes tend to come in clusters: If you negatively stereotype one disadvantaged group, you are likely to stereotype other disadvantaged groups as well.

These findings reveal that the four measures of negative stereotypes show convergent validity. However, the main hypothesis was that conservatism relates to negative stereotypes, which is examined next.

4.3. Interrelations among Conservatism, GBJW, and Measures of Negative Stereotypes

Conservatism. Conservatism was correlated with modern sexism and modern racism. Other researchers have also found a connection between conservatism on the one hand and both sexism (Beyer 2020; Bock et al. 2017; Bracic et al. 2019; Rothwell et al. 2019; Schaffner et al. 2018; Shook et al. 2020) and racism, on the other hand (Bracic et al. 2019; Schaffner et al. 2018; Shook et al. 2020). The present research found that conservative participants felt less favorably about minorities such as African Americans and those with opposing viewpoints, such as atheists and Democrats, but felt more positively about Catholics, Caucasians, Christians, and Republicans than liberal participants did. Thus, as hypothesized, conservatives showed greater negative stereotypes than liberals when using modern sexism, modern racism, and feelings towards social groups as operational definitions of negative stereotypes. However, one of the measures of negative stereotypes, viz., ratings of intelligence of social groups (see Table 3), showed less evidence of negative stereotypes. In summary, the relationship between conservatism and negative stereotypes was assessed using four separate measures of stereotypes, with three measures (modern sexism, modern racism, and feelings toward social groups) finding that conservatives show more negative stereotypes than liberals do, supporting the strand of research identified in the introduction as the “prejudice gap” view. Overall, the results for the relationship between conservatism and negative stereotypes were less strong than the findings for the relationship between political affiliation and stereotypes, which is detailed in Section 4.4.

GBJW. Participants who scored high on GBJW rated Caucasians, men, and Republicans more favorably and were also much higher in both modern sexism and modern racism, demonstrating the relation between GBJW and negative stereotypes. Other researchers have found that GBJW correlates with the perception that wealth inequality is due to personal traits, such as laziness (Kraus et al. 2019). Future research should further examine the role of GBJW in stereotypes of disadvantaged social groups.

4.4. Political Affiliation and Negative Stereotypes

In another set of analyses, only participants who identified as either Democrat or Republican were used to determine the effect of party affiliation on negative stereotypes. This results in a smaller sample size, as it excludes individuals who do not strongly identify politically. However, excluding those without strong political affiliations actually represents a more direct test of the relationship between political attitudes and negative stereotypes. Despite lower statistical power, the analyses comparing Republicans to Democrats showed stronger relations between party affiliation and negative stereotypes than the analyses of the relation between conservatism and negative stereotypes did. For comparison purposes, the left side of Table 4 includes the means for the full sample of participants.

There were several similarities in how Democrats and Republicans rated the 20 social groups. They rated women most positively, and Asians and physically disabled individuals quite positively, while rating the homeless and atheists negatively. Another consistency was that they rated members of the other political party most negatively of all the groups, further demonstrating the chasm between the two political groups. Republicans rated nine groups, viz., African Americans, atheists, bisexuals, Democrats, female and male homosexuals, immigrants, Muslims, and transgender individuals, significantly more negatively than Democrats did. This supports Blair’s (2017) finding that Trump voters held much more anti-Muslim, anti-gay, and anti-trans stereotypes than Democratic voters. The two social groups Democrats rated significantly more negatively than Republicans were Caucasians and Republicans. It is interesting to note that when examining the results for all participants (i.e., including those without party affiliation), Republicans were rated most negatively, substantially lower than the second least liked group, atheists.

As can be seen in Table 5, both Democrats and Republicans viewed Asians as the most intelligent of the 20 social groups, followed by women. At or near the bottom of the list were Catholics, atheists, homeless, and intellectually disabled individuals. Both Democrats and Republicans rated the other political party’s members among the least intelligent. When looking at data from the entire sample, even individuals with intellectual disabilities were rated as more intelligent than Republicans, a quite unexpected finding. Republicans rated bisexuals, Democrats, and women as significantly less intelligent than Democrats did. The only social group Democrats rated significantly less intelligent than Republicans did was Republicans. Republicans scored significantly higher than Democrats on modern sexism, modern racism, conservatism, and GBJW. In summary, as hypothesized, Republicans displayed more negative stereotypes than Democrats regardless of the specific operational definition (modern sexism, modern racism, liking of social groups, ratings of intelligence of social groups) of negative stereotypes. This provides strong support for the “prejudice gap” view. Overall, despite the smaller sample size and, therefore, lower statistical power, the results for individuals who identified with a political party were stronger than the results for the continuous measure of conservatism. This may be due to the continuous measure including many individuals without strong political leanings. It is when we examine individuals with a definite political party preference that the strong relationship between political leanings and negative stereotypes emerges.

4.5. Implications of Negative Stereotypes for Society

When considering the implications of negative stereotypes for society, the number of social groups for whom one holds negative stereotypes is less consequential than the type of social groups against which stereotypes are held. As predicted, Republicans felt more negatively about social groups that have been targets of racial, religious, or sexual discrimination and disenfranchisement than Democrats did. At the same time, Republicans favored more powerful social groups.

Overall, the social groups against whom Republicans held the strongest negative stereotypes were individuals outside of the cisgender norm and immigrants. Prusaczyk and Hodson (2020) found that conservative individuals showed more prejudice toward gender non-conformists, a pattern we replicated for Republicans in this study. In the US, gender non-conformists are still perceived as threatening the status quo of traditional marriage and parenthood (Hodson and Dhont 2015). For example, while support for same-sex marriage had risen to 70% in 2020, many Republicans still hold very negative attitudes, with only about half supporting same-sex marriage (PRRI Staff 2020). Indeed, in the present study, Republicans disliked individuals outside the heterosexual, cisgender norm more than most other social groups (see Table 4). This was especially the case for feelings about transgender individuals, which were only eclipsed by Republicans’ disdain for atheists and Democrats.

Negative feelings about disadvantaged social groups may emerge because conservatives are more likely to accept inequality, as it serves to protect their beliefs from the threat of change (Hirsh et al. 2010). Indeed, in this study, Republicans felt less positively than Democrats did about members of groups that hold less power. Hodson and Dhont (2015) found that liberals tend to dislike those who hold power over others or try to impose their beliefs, a finding this research replicated, as Democrats felt less positively than Republicans about Catholics, Caucasians, Christians, and Republicans. Chambers et al. (2013) also found that liberals held less positive views of majority groups. Thus, both Republicans and Democrats held negative stereotypes, but the social groups associated with those stereotypes differed. Not surprisingly, those who have opposing viewpoints are strongly disliked; both Republicans and Democrats reserved their most negative feelings for their political opponents. However, Republicans also felt more negatively about racial, religious, and sexual minorities and more positively about “White majority” groups such as Caucasians and Christians than Democrats did. It should be noted that these differences in negative stereotypes by political party were not small. Indeed, the effect sizes were quite substantial.

Thus, Democrats clearly are not immune to negative stereotypes. However, negative stereotypes of those in power, such as Caucasians and Christians (groups to which many Democrats actually belong), do not have analogous deleterious effects on those advantaged groups as Republicans’ negative stereotypes of disadvantaged groups, such as racial and religious minorities and members of the LGBTQ community, do. The groups that are more negatively stereotyped by Republicans are still frequent victims of employment, housing, and other forms of discrimination and targets of hate crimes (e.g., see the Federal Bureau of Investigation’s [FBI] Uniform Crime Reports’ most recent data).

Other researchers have also observed different motivations and value systems in conservatives and liberals. For example, Jost et al. (2018, p. 58) note that “liberals […] are motivated by (humanistic) concerns for equality (and social justice), and this leads them to embrace social change, whereas conservatives […] are motivated by the (normative) desire to preserve tradition (and social order), and this is what leads them to defend and justify inequalities in the social system”. Similarly, Graham et al. (2009) found a difference in the value systems of conservatives and liberals, with liberals valuing Harm/care and Fairness/reciprocity more than conservatives did.

4.6. Interrelations among Political Affiliation, Modern Sexism, Modern Racism, and Exposure to Social Groups

Unsurprisingly, Democrats indicated that they had interacted more with Democrats, while Republicans indicated that they had interacted more with Republicans. The only other significant difference was that Democrats said that they had interacted more with bisexuals than Republicans did. Individuals high in modern sexism or modern racism were less likely to have interacted with bisexuals, Democrats, male homosexuals, and transgender individuals. Those high in modern sexism were also less likely to have interacted with female homosexuals. This indicates that individuals high in modern sexism or modern racism interact less with individuals outside the cisgender, heterosexual norm. Of course, cause and effect cannot be inferred from this. Do individuals high in modern sexism or modern racism actively avoid interactions with sexual minorities due to their negative stereotypes, or does the lack of interaction lead to negative stereotypes? In any case, a lack of interaction with certain social groups is unlikely to lead to revisions to one’s negative stereotypes.

4.7. Experience with Discrimination

There was a highly significant race difference in the experience of racial discrimination, with African American participants reporting the highest level of discrimination and Caucasians the lowest. Given the current state of racial strife in the US (as exemplified by police shootings and the rise of the Black Lives Matter movement), this is not too surprising. In terms of experience with religious discrimination, Muslims reported very high levels of discrimination compared to Christians and atheists. Again, this may not be surprising given the US government policies and rhetoric at the time of the survey (e.g., blocking entry into the US from certain majority-Muslim countries). There was also a significant gender difference in the experience of gender discrimination, with females reporting higher levels of discrimination compared to males.

On an absolute level, Muslims indicated experiencing the highest level of discrimination, followed by African Americans, Asians, and Native Americans. What is striking is that this is somewhat at odds with participants’ descriptions of their feelings about members of some of these social groups. For example, Asians reported experiencing a fairly substantial amount of discrimination, yet of the 20 social groups, they were second highest in favorability for Republicans and fourth for Democrats and were rated as the most intelligent group. This study predates the emergence of COVID-19 and ensuing racial epithets accompanied by increased discriminatory actions directed at Asians (e.g., Kambhampaty 2020). On the other hand, atheists reported little discrimination, but they were the least liked group by Republicans, and even among Democrats were 13th of 20. They were also rated among the least intelligent groups. Atheism is a fairly invisible social category, which could explain why atheists, despite their low favorability ratings, might escape discrimination. Overall, negative stereotypes and discrimination are still quite prevalent, and a better understanding of their relation to political attitudes is imperative.

4.8. Limitations of This Research

One limitation of this research is its small sample size, although the results are consistent with a previous study by Beyer (2020). It should also be noted that the study was conducted on undergraduates. College students in the US are generally less conservative than non-college-educated individuals (College Free Speech Rankings 2021). However, the aim of this study was not to assess the absolute level of conservatism but instead to focus on the relationship between conservatism and negative stereotypes. This relation is likely to be similar in college and non-college samples, despite differences in absolute levels of conservatism. Another limitation is that the study used college students at one small, public university in the Midwest of the US, limiting generalizability.

The selection of the social groups serving as targets may also be questioned. Several groups were specifically chosen as targets because they represent minority or traditionally disenfranchised groups. Understanding who may hold negative stereotypes against such groups is important. Other social groups were chosen as counterweights, representing more powerful groups (e.g., men, Caucasians). Furthermore, the finding that conservatism correlates with modern sexism and modern racism and that Republicans score significantly higher than Democrats in modern sexism and modern racism indicates their greater susceptibility to negative stereotypes towards disadvantaged groups.

4.9. Directions for the Future

This research supported the hypothesis that conservatives hold more negative stereotypes than liberals. It is important to point out that Democrats and liberals also hold negative stereotypes, e.g., against Republicans and Caucasians. However, in terms of societal implications during times of social unrest, such as what was experienced following the George Floyd killing, and increasing religious, racial, and sexual minority intolerance (exemplified by the rise of White supremacy and other hate groups; see Federal Bureau of Investigation 2020), it is imperative that we identify who is most likely to hold negative stereotypes against disadvantaged, rather than against advantaged, social groups. Thus, we need a better understanding of why certain political groups show negative stereotypes against certain types of social groups.

Furthermore, it is important to point out that the relationship between political attitudes and negative stereotypes is clearest when examining individuals who have strong political attitudes, e.g., those identifying with a political party. The results were less clear-cut when using a continuous measure of political attitude: Conservatism. This measure, by virtue of including those in the middle of the scale who do not have strong political leanings, showed less consistent connections between political attitudes and negative stereotypes. Future research should take the strength of political leanings into account.

It would be helpful to identify other individual difference variables which affect negative stereotypes. Examples include hegemonic masculinity (Vescio and Schermerhorn 2021) and hostile sexism (Glick 2019; Ratliff et al. 2019), which predicted support for Trump in the 2016 election. Hegemonic masculinity was also related to sexism, racism, homophobia, xenophobia, and Islamophobia (Vescio and Schermerhorn 2021). In order to fight negative stereotypes of social groups, we need to understand better the characteristics associated with stereotyping.

5. Conclusions

Individuals with strong political convictions are biased against those with different viewpoints, with the most negative stereotypes held by members of the two major US political parties about members of the other political party. In addition to disliking those whose views conflict with our own, this study found that, as hypothesized, Republicans held more negative stereotypical views of many stigmatized groups. This finding held across four different operationalizations of negative stereotypes: modern sexism, modern racism, negative feelings, and intelligence ratings of social groups. This reveals that negative stereotypes of one disadvantaged social group often generalize to other disadvantaged social groups. For example, an individual with a negative stereotype of African Americans is also likely to hold a negative stereotype of individuals outside of the heterosexual norm. The reason we need to be concerned about the presence of negative stereotypes is that they can lead to discrimination. More research is needed to elucidate factors associated with negative stereotypes against disadvantaged social groups and what we can do to counteract them.