Changing Norms Following the 2016 U.S. Presidential Election

Abstract

The 2016 presidential election was characterized by the remarkable expression of prejudice toward a range of groups. In two closely related studies (N = 388; 196 supporting Trump, 192 Clinton), we measured (1) perceptions of social norms toward prejudice or (2) people’s own levels of prejudice toward 19 social groups, shortly before and after the election. Some groups were targeted by the Trump campaign (e.g., Muslims, immigrants) and some were not (e.g., atheists, alcoholics). Participants saw an increase in the acceptability of prejudice toward groups Trump targeted but little shift in untargeted groups. By contrast, participants reported a personal drop in Trump-targeted prejudice, probably due changing comparison standards, with no change in prejudice toward untargeted groups. The 2016 election seems to have ushered in a normative climate that favored expression of several prejudices; this shift may have played a role in the substantial increase in bias-related incidents that follow closely upon the election.

Keywords

prejudice social norms Donald Trump election

Bigotry seems emboldened.

—President George W. Bush (2017, October 19) People conform to social norms; following group rules signals both identity and membership. Prejudice norms can be powerful—self-reported prejudices conform to norms quite closely (Crandall, Eshleman, & O’Brien, 2002). Because norms—and concerns about criticism, punishment, or ostracism that come from violating them—are one of the most important suppressors of prejudice, changes in social norms can lead to changes in beliefs, attitudes, and behaviors. When social norms shift to the approval of prejudice, groups can engage in discrimination, hate speech, and violence (Alvarez, 1999).

People often have conflicting motives for expressing prejudices. The right to free speech is deeply important to U.S. citizens, and expressions of even loathsome ideas often must be legally tolerated (Post, 1990; White & Crandall, 2017). On most prejudices that social psychologists study, there is cultural ambivalence—the acceptability of the prejudice is contested. Some feel that expressions of these prejudices are warranted, while others find them abhorrent (Crandall, Ferguson, & Bahns, 2013). This is often matched by an internal, individual ambivalence, where people recognize a prejudice within that is inconsistent with their own values (Gaertner & Dovidio, 1986; Katz & Hass, 1988).

This ambivalence, and its lack of normative clarity, makes people open to social influence (Sherif & Cantril, 1945; Zitek & Hebl, 2007). Blanchard, Crandall, Brigham, and Vaughan (2004) asked college students how to respond to racist occurrences on campus. Students were almost equally in the middle between tolerating speech and aggressively responding to racist incidents, but when a confederate joined the “survey” and gave an opinion first, students were strongly swayed toward her position. A single person can set a normative expectation of tolerance toward—or vigorous prosecution of—racist behavior. In situations of normative conflict, presenting models or standards of behavior can have a strong effect on both discrimination toward and tolerance of others (see also Paluck, 2009). Most of the negative affect that we call “prejudice” is toward groups for which the appropriate norms are in flux or dispute—we call this domain the “normative window” (see Crandall et al., 2013).

Social norms will not only influence how likely one is to express prejudice, but it also influences how much prejudice people think they have. Social comparison processes occur in the domain of prejudice, as people who feel high in prejudice are more likely to expose themselves to highly prejudiced groups such as the Ku Klux Klan (KKK) or Nazis in order to make them feel less prejudiced (O’Brien et al., 2010). An event that increases the normative acceptability of prejudice should—across the population—cause an increase in expressions of prejudice. At the same time, individuals may in the short run feel less prejudiced by comparison to a shifted norm (Biernat, 2012; O’Brien et al., 2010). This would cause them to report lower levels of prejudice, even if their feelings toward a group have not changed.

The 2016 campaign of U.S. presidential candidate Donald Trump was remarkable for its expressions of prejudice toward groups. At the initial campaign event, the candidate said, “When Mexico sends its people, they’re not sending their best…. They’re bringing drugs. They’re bringing crime. They’re rapists. And some, I assume, are good people” (Trump, 2015). The candidate ridiculed a reporter with a physical disability, reiterated his decades-old shaming of a beauty contestant for gaining weight, and said for American Muslims that a “database is okay, and watch list is okay, and surveillance is okay,” and later suggested a complete Muslim ban on immigration and tourism (Diamond, 2015; Saletan, 2016). At the time of the research, the acceptability of these prejudices was contested in the United States—with many people accepting such prejudices and many others condemning them.

The election of Donald Trump on November 8, 2016, was followed by a wave of racist incidents; the Southern Poverty Law Center reported more than 400 verified bias-related incidents in the week following election day and over 1,000 incidents in the month following, a substantial increase over the normal rate (Southern Poverty Law Center, 2016a, 2016b). Because the campaign and the candidate expressed high levels of various prejudices, we considered whether the election—by elevating candidate Trump to President-Elect—changed American’s perception of the social norms of prejudice. After the unexpected Trump victory, we hypothesized that the expression of prejudice would have become as more socially acceptable, particularly toward the groups that Trump targeted in the campaign.

Before the election, we recruited a sample of Donald Trump supporters and a sample of Hillary Clinton supporters for two-related studies. We asked them both before and after the election about either (1) their perception of social norms of prejudice or (2) their own levels of prejudice. They evaluated groups targeted by Trump, to see whether the election would change perceived norms about prejudice, and included a number of groups not targeted by Trump, to see whether this effect was specific to the campaign-relevant groups or affected all groups.

Method

Participants

We set out to recruit 400 people from Amazon’s Mechanical Turk (MTurk, using TurkPrime.com Litman, Robinson, & Abberbock, 2017) to participate in a “survey about social issues” for US$0.50.¹ Half of the participants responded to a call for Donald Trump supporters; the other half responded to call for Hillary Clinton supporters. One case was removed for large amounts of incomplete data, and 11 cases were removed due to prior participation, leaving 388 cases. Participants’ ages ranged from 18 to 66, with the modal age range of 26–35 years. Slightly more than half (55%) identified as male.

Parallel studies

Participants signed up for one of the two parallel but independent (mutually exclusive) studies. For the social norms study, participants were asked about their perceptions of social norms affecting the expression of prejudice. For the self-prejudice study, participants were asked about their own attitudes toward social groups. In both studies, participants rated all 19 groups (presented randomly) on a 0–100 sliding scale.

In the social norms study, we told participants we were not interested in their feelings. Instead, we wished to know how not ok (0) or perfectly ok (100) is to “express negative feelings toward the group.” Higher scores indicated social acceptability of prejudice.

In the self-prejudice study, participants reported their own prejudices—how negatively (0) or positively (100) they feel toward certain groups. Scores were reversed, so that higher scores represent more prejudice.

Participants then indicated their age, gender, support for presidential candidates from 0 (Clinton) to 100 (Trump), a handful of items about media use (discussed only in Online Supplemental Materials), and two political identification items—conservative-to-liberal (reverse scored) and Democrat-to-Republican (r = .82).

Time 1

Data were collected from October 28 to October 31, just before the November 8 election. Respondents agreed to participate and answered questions about 19 social groups. Nine of these were selected to reflect Trump’s campaign: Asian Americans, disabled people, fat people, immigrants, Mexicans, Muslims, socialists, and woman considering an abortion (a = .88 and .89 for the social norms study across Time 1 and Time 2; a = .86 and .85 for the self-prejudice study across Time 1 and Time 2). Ten groups were selected as not representative of targets of the campaign: alcoholics, atheists, Canadians, car salesman, drug dealers, lazy people, members of the National Rifle Association, people who cheat their taxes, politicians, porn stars, and rich people (a = .82 and .84 for social norms study across Time 1 and Time 2; a = .60 and .66 for the self-prejudice study across Time 1 and Time 2).² Across times and studies, average Cronbach’s α = .87.

Time 2

On November 11, Time 1 participants were invited again on MTurk for US$0.50. Over 5 days, 334 participants completed the follow-up study (86% retention, with N = 165 for social norms study and N = 169 for self-prejudice study³). Participants again rated the 19 groups on the same scales, and they again reported political identification. We also asked racial identity at Time 2; the majority of participants identified as White (82%).

We compared returning versus dropout participants on every variable measured at Time 1 including the 10 media usage items not used in this study. Only 2 of the 33 t tests and none of the four categorical tests were significant, showing little evidence of differential dropout rates.

Results

Social Norms Study

Trump versus Clinton supporters

How did supporters from the two campaigns differ before the election? To test this, we calculated a 2 (Clinton vs. Trump supporter) × 2 (targeted vs. not targeted)⁴ mixed analysis of variance (ANOVA) using only the data from Time 1 (Table 1). There was no difference between Clinton and Trump supporters of the perceived acceptability of prejudice, F(1, 195) = 0.09, p = .768, $η_{p}^{2}$ < .01. There was much more acceptability of prejudice toward the not targeted groups, F(1, 195) = 143.37, p < .001, $η_{p}^{2}$ = .42, but the interaction was not significant, F(1, 195) = 2.26, p = .135, $η_{p}^{2}$ = .01.

Table 1.

Mean Social Norms and Self-Reported Prejudice by Trump Campaign-Targeting and Candidate Supported.

	Social Norms Study		Self-Prejudice Study
Supported	Targeted	Not Targeted	Targeted	Not Targeted
Trump	39.77	57.21	52.42	59.55
(SD)	(23.87)	(18.69)	(17.79)	(10.50)
95% CI	[35.0, 44.5]	[53.5, 60.9]	[48.9, 56.0]	[57.5, 61.6]
Clinton	38.10	60.55	35.37	57.00
(SD)	(27.35)	(21.15)	(15.95)	(11.45)
95% CI	[32.7, 43.5]	[56.4, 64.7]	[32.1, 38.6]	[54.7, 59.3]
N	197		191

Effect of election on prejudice

Did the election unleash prejudice by changing social norms? To test this, we calculated a 2 (targeted vs. not targeted) × 2 (before vs. after) within-subjects ANOVA.

Participants perceived more tolerance for prejudice after the election than before, F(1, 164) = 6.47, p = .012, $η_{p}^{2}$ = .04, and perceived greater normative tolerance of prejudice toward the not targeted groups than the targeted ones, F(1, 164) = 126.45, p < .001, $η_{p}^{2}$ = .44. These main effects were qualified by a significant interaction, F(1, 164) = 6.24, p = .014, $η_{p}^{2}$ = .04 (Figure 1). For targeted groups, participants perceived higher normative acceptability after the election (M = 43.83, SD = 25.02) than before (M = 37.80, SD = 24.94), F(1, 164) = 9.35, p = .003, $η_{p}^{2}$ = .05; for not targeted groups, the perceived norm after the election (M = 59.06, SD = 20.57) did not differ than the norm before the election (M = 58.33, SD = 19.97), F(1, 164) = 0.28, p = .600, $η_{p}^{2}$ < .01. This corresponds to a d_z = .24 change for targeted groups and d_z = .04 for not targeted (see Morris & DeShon, 2002).

Figure 1.

The normative acceptability of prejudice toward groups targeted and not targeted by the Trump campaign, before and after the November 2016 election.

The election significantly increased the social acceptability of prejudice toward the groups Trump targeted, but it had little effect on perceived norms of the campaign-irrelevant groups. Note 4 provides analyses based on slightly different groups of the target groups. See Table 2 for social norm means across time for all 19 groups.

Table 2.

Difference Before and After the Election for Each Group in the Social Norms Study.

Group	Time 1 M (SD)	Time 2 M (SD)	t	p
Muslims^a	41.43 (35.76)	44.58 (33.63)	1.12	.265
Fat people^a	38.90 (34.50)	42.14 (32.61)	1.20	.231
Immigrants^a	41.04 (34.19)	46.31 (32.04)	1.78	.077
Mexicans^a	34.22 (33.17)	41.27 (33.43)	2.49	.014
Woman considering abortion^a	35.85 (34.82)	43.16 (33.00)	2.51	.013
Asian Americans^a	32.81 (33.53)	40.98 (34.84)	2.75	.007
Disabled people^a	24.40 (33.64)	34.32 (37.42)	3.47	.001
Socialists^a	53.73 (34.15)	57.90 (31.64)	1.41	.160
Drug dealers	69.40 (37.17)	63.18 (37.17)	2.05	.042
Atheists	44.25 (36.04)	51.06 (33.49)	2.56	.011
Rich people	56.98 (32.59)	58.84 (30.54)	0.680	.497
People who cheat on taxes	67.23 (34.68)	62.50 (34.55)	1.47	.144
Porn stars	61.27 (33.19)	61.47 (33.07)	0.068	.946
Canadians	43.50 (35.60)	53.69 (34.89)	3.54	.001
Alcoholics	49.96 (32.27)	51.10 (31.62)	0.460	.646
Members of the National Rifle Association	49.49 (32.69)	53.50 (30.49)	1.42	.158
Car salesman	65.32 (31.01)	65.16 (28.60)	0.063	.950
Lazy people	61.61 (34.69)	59.40 (34.42)	0.714	.476
Politicians	72.67 (30.77)	69.72 (30.48)	1.09	.276

Note. df for all tests is 164.

^aIndicates which groups were targeted by Trump.

Self-Prejudice Study

Trump versus Clinton supporters

How did supporters from the two campaigns differ in their personal prejudices before the election? Individual prejudice was higher for the not targeted groups than the targeted groups, F(1, 189) = 158.74, p < .001, $η_{p}^{2}$ = .46. The greater level of prejudice from the Trump supporters, F(1, 189) = 32.65, p < .001, $η_{p}^{2}$ = .15, is almost completely due to the greater prejudice toward the targeted groups, interaction F(1, 189) = 40.34, p < .001, $η_{p}^{2}$ = .18. Trump supporters expressed more prejudice toward targeted groups than Clinton supporters, F(1, 189) = 48.72, p < .001, $η_{p}^{2}$ = .21, while Trump and Clinton supporters did not differ in reporting prejudices toward nontargeted groups, F(1, 189) = 2.58, p = .110, $η_{p}^{2}$ = .01. Supporters of both candidates see prejudice norms in similar terms, but that Trump supporters report significantly higher levels of prejudice toward the targeted groups than Clinton supporters.

Effect of election on prejudice

How did the election affect people’s self-reported prejudice? To test this, we calculated a 2 (targeted vs. not targeted) × 2 (before vs. after) within-subjects ANOVA.

Participants expressed more prejudice toward the not targeted groups than targeted groups, F(1, 168) = 179.45, p < .001, $η_{p}^{2}$ = .52, and bit less prejudice was expressed after the election than beforehand, F(1, 168) = 6.00, p = .015, $η_{p}^{2}$ = .03. These main effects were qualified by a significant interaction, F(1, 168) = 5.99, p = .015, $η_{p}^{2}$ = .03, see Figure 2. People reported less prejudice toward targeted groups after (M = 40.56, SD = 17.78) than before (M = 43.28, SD = 18.50) the election, F(1, 168) = 8.06, p = .005, $η_{p}^{2}$ = .05, while there was no change in not targeted groups (pre M = 57.78, SD = 11.73; post M = 58.08, SD = 11.17), F(1, 168) = 0.27, p = .601, $η_{p}^{2}$ < .01. This corresponds to a d_z = −.22 for Trump-targeted prejudice and d_z = −.04 for the untargeted groups. Table 3 demonstrates mean differences for each group across the two time points, and again Note 4 provides analyses based on a slightly different grouping of the target groups.

Figure 2.

Self-rated prejudice toward groups targeted and not targeted by the Trump campaign, before and after the November election.

Table 3.

Difference Before and After the Election for Each Group in the Self-Prejudice Study.

Group	Time 1 M (SD)	Time 2 M (SD)	t	p
Muslims^a	50.88 (28.96)	48.29 (28.28)	1.64	.102
Fat people^a	48.54 (23.75)	46.43 (23.24)	1.38	.167
Immigrants^a	45.40 (27.88)	41.93 (26.53)	2.23	.027
Mexicans^a	41.47 (28.38)	38.12 (25.78)	1.98	.049
Woman considering abortion^a	48.23 (28.33)	47.51 (27.82)	0.487	.627
Asian Americans^a	28.63 (22.12)	26.16 (21.36)	1.62	.107
Disabled people^a	31.19 (22.26)	28.66 (21.27)	1.734	.085
Socialists^a	51.91 (27.10)	47.38 (27.89)	2.87	.005
Drug dealers	80.34 (21.79)	80.29 (21.31)	0.039	.969
Atheists	42.31 (29.92)	38.99 (30.23)	2.00	.048
Rich people	47.54 (23.99)	49.61 (24.42)	1.23	.219
People who cheat on taxes	75.92 (21.02)	73.36 (22.66)	1.89	.060
Porn stars	51.86 (27.00)	50.62 (26.85)	0.903	.368
Canadians	26.84 (22.72)	27.01 (21.20)	0.101	.920
Alcoholics	65.45 (23.40)	66.31 (22.23)	0.599	.550
NRA members	47.50 (30.51)	50.91 (32.15)	1.91	.057
Car salesman	60.55 (22.34)	62.17 (22.00)	1.09	.278
Lazy people	72.20 (21.66)	67.76 (21.08)	2.91	.004
Politicians	68.34 (24.38)	68.56 (22.11)	0.145	.885

Note. df for all tests is 168.

^aIndicates which groups were targeted by Trump.

Discussion

The Trump campaign toned down the prejudice-laced rhetoric in the final weeks of the campaign (Khalid & Detrow, 2016); it seems unlikely that the change in perceived norms was a result of persuasive communications. It was most likely the election itself—the public endorsement of Trump by the American people—that changed perceptions. Supporters of Trump and Clinton alike saw increased approval for expression the prejudices that characterized the Trump campaign.

Conversely, as the participants saw prejudices becoming more acceptable, they rated themselves as slightly less prejudiced. The rising public tide of prejudiced rhetoric created a compellingly low comparison standard—people evaluate themselves and their prejudices in direct comparison to others (Smith & Ho, 2002). In experiments when people discover others with high levels of prejudice, rather than concluding the world has people with much prejudice, they instead use these this as an opportunity to find themselves quite low in prejudice (“The world isn’t high in prejudice—I am particularly low in it!,” see O’Brien et al., 2010). The political campaign was a substantially larger manipulation than most laboratory experimental manipulations—our participants showed movement in both perceived norms and self-evaluation.

We assume that it is more likely that our participants changed their self-evaluation as a result of the Trump campaign and its sequelae, rather than changing notions of their selves affecting how they view the nation’s normative climate. Further, we assume that reduction in reports of self-prejudice is a change in self-evaluation rather than a change in actual dislike for the targeted groups.

People navigate their personal and the cultural ambivalences about prejudice; when the acceptability of a prejudice is contested, they are particularly reliant on social norms about when to express or when to suppress their feelings (Crandall & Eshleman, 2003). Because these norms are a primary source of suppression, changing in social norms of prejudice should have a large effect on how people behave. People saw these norms as changing toward greater tolerance for discriminatory speech and actions, and this should partly account for the substantial increase in bias-related incidents following the election.

The Normative Window

The kinds of prejudices that most people talk about—and most social scientists study—are normatively contested (Crandall & Warner, 2005). There is very little study of groups where there is agreement about a group’s social value, but the usual target of “prejudice” is a group in a “window of time in which social norms are shifting toward equal treatment…but for which the entire process has not yet been completed, and for which complete social agreement about the status of the group has not yet been achieved” (Crandall et al., 2013, p. 56). All of the groups that Trump targeted fit this description (Asian Americans, disabled people, fat people, immigrants, Mexicans, Muslims, socialists, woman considering an abortion); this lack of consensus—perhaps combined with their relatively low social status—makes them vulnerable to changing norms. The groups Trump did not target are less controversial, being either mostly considered “good” (e.g., Canadians, rich people) or widely considered “bad” (e.g., lazy people, drug dealers, people who cheat their taxes).

Constraints on generality

Our participants are not a representative sample of Americans and so one must be careful in generalizing the processes to an entire nation. Nevertheless, we found no differences in these effects by gender, and the shift in perceived norms was equivalent among both Trump and Clinton supporters. The limited size of the non-White population does not allow us to consider differences due to race or ethnicity. The age range is substantial, but the distribution oversampled the young- to middle-aged adult population.

Paul Krugman has claimed that Trump “gives outright, unapologetic voice to racism, sexism, contempt for ‘losers,’ and so on—feelings that…have long been things you weren’t supposed to talk about openly” (Krugman, 2017, p. A31). Our respondents provide the same impression—the election gave voice and license to express the previously suppressed.

Supplemental Material

Supplemental Material, SPPS750735_suppl_mat - Changing Norms Following the 2016 U.S. Presidential Election: The Trump Effect on Prejudice

Supplemental Material, SPPS750735_suppl_mat for Changing Norms Following the 2016 U.S. Presidential Election: The Trump Effect on Prejudice by Christian S. Crandall, Jason M. Miller and Mark H. White II in Social Psychological and Personality Science

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Notes

Supplemental Material

The supplemental material is available in the online version of the article.

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