Sage Journals: Discover world-class research

Abstract

The limited research on support for state repression of protests points to protest violence, ideological opposition, and racial/ethnic resentment, but few have examined how moral intuitions influence support for repression and racialized opposition to protest claims. The authors use a national survey of 1,030 respondents, fielded in June 2020 at the height of the post-Floyd Black Lives Matter protests, to investigate the moral motivations for supporting Trump’s “law and order” response. Drawing on moral foundations theory, the authors hypothesize that individualizing moral intuitions that prioritize care and protection of the vulnerable (a social justice orientation) influences opposition to Trump, whereas binding moral intuitions that prioritize social stability (a social order orientation) influence support for “law and order.” The authors find strong support for these hypotheses, and skepticism toward racial injustice claims mediates much of these effects. This research thus expands the limited literature on public support for protest repression by illuminating the moral dimension.

Keywords

Black Lives Matter protest repression Trump moral foundations public opinion

Throughout the summer of 2020, millions of Americans left their homes during a global pandemic to protest the deaths of Black men and women at the hands of police (Buchanan, Bul, and Patel 2020). Although overwhelmingly peaceful (Chenoweth and Pressman 2020), even compared with the civil rights era (Goff and McCarthy 2021), President Trump criticized protesters for causing disorder and committing violence. In defense of “law and order” and those tasked with keeping it, Trump went on the offense, casting the Black Lives Matter (BLM) movement and protesters as criminal aggressors, threatening military action against this “domestic terror” and calling on the National Guard to “dominate the streets” (Burns 2020a).

Presidential opposition to protests is nothing new (Davenport 2007; Earl 2003), and research has repeatedly shown that violent protests often provoke backlash and loss of public support (Muñoz and Anduiza 2019; Stephan and Chenoweth 2008; Wasow 2020). Although most protests were nonviolent, many Americans agreed with Trump’s assessment and advocated for repression. What led to such polarized responses? And despite the overwhelmingly peaceful nature of the protest wave, why did so many Americans support Trump’s “law and order” response?

Numerous studies have examined the correlates of repression and aggressive policing of protests (Earl 2003; Earl, Soule, and McCarthy 2003; McCarthy, Martin, and McPhail 2007), but few have examined the sources of public support for such responses to protests (Metcalfe and Pickett 2022). Results from these few studies suggest that violent protest increases public support for repression (Edwards and Arnon 2021). Other studies show that opposition to protest goals increases support for repression but that this effect is moderated by ideological beliefs, especially racial resentment (Metcalfe and Pickett 2022; Muñoz and Anduiza 2019). Despite the morally charged nature of people’s responses to violent protest, research in this area has yet to examine how peoples’ moral orientations toward social justice and social order influence their support for protest repression or whether moral orientations contribute to racialized beliefs about protest participants and goals.

To fill this gap, we draw on a national survey of 1,030 U.S. respondents, fielded at the height of the June 2020 protests, to investigate the moral and ideological factors that underlay Americans’ divergent reactions to President Trump’s “law and order” response. To conceptualize and measure individuals’ orientation toward social justice or social order, we draw on moral foundations theory (MFT; Graham et al. 2011; Haidt 2012). MFT is grounded in the assumption that “fast thinking” cognition precedes “slow” moral reasoning, guides a person’s judgements (whether consciously or not) about political and moral issues, and manifests in two distinct moral foci: a concern for the well-being and fair treatment of individuals (individualizing moral intuitions) leading to a social justice orientation and a concern for maintaining lines of authority and group boundaries (binding moral intuitions) leading to a social order orientation (Silver, Goff, and Iceland 2022). We test whether individuals’ moral orientations explain differential support for Trump’s “law and order” response to the 2020 BLM protests, net of proximity to protests, conservatism, racial resentment, and other important controls. We also test whether the effect of moral intuitions is mediated by respondents’ skepticism toward the claim of racial injustice by police.

Our study contributes to the literature on public attitudes toward protest repression in several ways. First, we introduce a well-established moral framework, MFT, to explain differential support for protest repression and, by extension, the moral motivations behind support for or opposition to protest movements. Second, we expand prior research on the link between racial ideology and support for repression, highlighting the moral motivations behind both. Third, we expand the prior research on support for repression by including contextual factors such as proximity to protests.

Sources of Support for Repression

Social movement scholars define repression as “any action by another group which raises the contender’s cost of collective action” (Tilly 1978:100). This may include coercive measures such as “harassment, surveillance/spying, bans, arrests” (Davenport 2007:1) or preventive measures such as laws delimiting places to protest (Earl 2003). Most scholars have investigated the causes of protest repression¹ (Davenport, Soule, and Armstrong 2011; Earl et al. 2003; McCarthy et al. 2007), but few have examined the correlates of public support for repression.

Protest Violence

Studies generally show that the use of violent tactics leads to negative public opinion and state repression (Stephan and Chenoweth 2008; Wasow 2020). When protests turn violent or disruptive beyond what is acceptable, they provoke opposition from the state and the public (Muñoz and Anduiza 2019) and spur support for groups opposing the violent group (Simpson, Willer, and Feinberg 2018). There is also evidence that protest violence increases support for repression by heightening individuals’ fear of harm. Using survey experiments in both the United States and Israel, Edwards and Arnon (2021) found that in both contexts, the threat of harm had a larger effect on support for protest repression than protesters’ either being armed or being from an outgroup. Using a nationally representative survey experiment in the United States, Metcalfe and Pickett (2022) found that respondents exposed to a protest vignette that depicted both property damage and violence were more likely to express fear of protesters and to support police control. Finally, in a different experimental study, Hsiao and Radnitz (2021) found that perceptions of violence increased participants’ support for arresting protesters and passing laws to punish them.

Proximity to Protest Violence

Studies suggest that opposition to protests may be contingent upon people’s proximity to protest violence. Proximity to protester violence was found to provoke opposition during the civil rights era (Wasow 2020), whereas nearness to nonviolent sit-in protests was associated with public support (Andrews, Beyerlein, and Tucker Farnum 2016). Proximity, however, does not always influence public reaction to protest. Research on the 2020 racial justice protests shows that proximity measures do not explain changes in attitudes about racial justice (Reny and Newman 2021). Although these studies do not directly measure support for repression, opposition to protest is considered an important factor (Metcalfe and Pickett 2022).

Political Affinity

Despite the association between protest violence and support for repression, studies have found that some people’s support for repression is more ideological. Hsiao and Radnitz (2021) found that after controlling for violent tactics, Republicans perceived protests by ideological opponents as more violent than did Democrats in a corresponding scenario. Similarly, though not focusing on repression per se, Muñoz and Anduiza (2019) found that supporters of a 2016 antiausterity movement in Barcelona remained supportive even after observing a violent outbreak. Along these lines, a large experimental study in the United States and Israel showed that people supported increased repressive measures if violence was mentioned in the protest vignette (Edwards and Arnon 2021). The study also found that in the United States, Democrats were more likely to favor repression if Sons of Confederate Veterans were protesting and that Republicans were more likely to favor repression of BLM protests. Israelis were more likely more likely to favor repression against Palestinian protesters. In short, research indicates that people are more likely to support repression of protests when the protesters represent an opposing political group or ideology.

Racial Animus

A large stream of research has shown that people tend to oppose protests and support repression when protesters are members of racial and ethnic outgroups. Research also shows that differences in repression by police is often racially stratified (Davenport et al. 2011). Such racially motivated support for repression extends to bystanders as well, as some have been found to view protesters as more violent if they are Black (Davenport et al. 2011; Nicholson and Valentino 2021). Violent attributions only account for some of the opposition. As with ideological alignment, when protests are racially focused, people tend to side with their racial or ethnic in-group, even when protests are nonviolent (Edwards and Arnon 2021).

Research on opposition to BLM has focused on the role of racial resentment and symbolic racism (Kinder and Sears 1981; Pettigrew 1989), concluding that it is “dislike of Black Americans, and a resentment of the very acts of pointing out injustice and asking for equal treatment” that drives White opposition to BLM (Drakulich et al. 2020:246). Focusing on support for repression, not just opposition to BLM, Metcalfe and Pickett (2022) found that racial resentment increased support of repression whether the protest group was proimmigrant or pro-BLM. Racial animus clearly plays a role in support for protest repression.

Although the research on racial resentment has produced significant results across numerous studies (Drakulich et al. 2020; Metcalfe and Pickett 2022; Riley and Peterson 2020), measuring racial resentment is complicated by some confounding factors. Racial resentment measures potentially confound negative attitudes about Black people with negative views of any group that does not appear to “pull itself up by its own bootstraps” (Riley and Peterson 2020). Recently, other research has incorporated a measure of belief in systemic racism in policing to more directly tap skepticism toward claims of racial injustice (Silver et al. 2022). This research shows that disbelief in systemic racism as a cause of police use of excessive force is strongly associated with opposition to BLM and support for police. There is likely a strong link between skepticism toward claims of racial injustice and supporting the repression of racial justice protests.

“Law and Order” as a Repression Frame

“Law and order” rhetoric has been a dominant justification for the policing of protests since the 1960s. In response to disruptive protests for racial justice, politicians and law enforcement have turned to the “law and order” counterframe to stir up opposition to racial justice protests and support for repressive tactics and policies. The appeal to “law and order” was used by Barry Goldwater in the 1964 presidential election to cast civil rights protests as acts of lawlessness (Beckett and Sasson 2004). This frame propelled Richard Nixon to victory in 1968 as it stoked concerns among White voters about rising urban crime, changing moral values, and the tumult of civil rights and antiwar protests (Flamm 2005). Continuing through subsequent administrations, and most recently with Donald Trump (Swaine 2017), the “law and order” frame has proven a popular tool for mobilizing opposition to challenges to the status quo.

The “law and order” frame provokes concerns for social order beyond U.S. politics and protests. Outside the United States, scholars have examined the use of “law and order” discourse as symbolic violence against protest movements (González-Sánchez 2019) and have demonstrated how political leaders use a “hero-protector” narrative to legitimize using force against perceived threats to the social order (Clément, Lindemann, and Sangar 2017). Drawing on a Durkheimian approach, criminologists in the United Kingdom found that support for police and punitiveness is linked to individuals’ concern for conserving the social and moral order of society, regardless of any personal threat from crime (Jackson and Bradford 2009). U.S. studies also demonstrate a link between concerns for social order and support for punitive criminal justice policies (J. R. Silver 2020; Silver and Silver 2017; Vaughan, Bell Holleran, and Silver 2019). Across national contexts and social issues, preferences for social order are linked to support for “law and order” rhetoric and policies and those who proffer them.

In the United States, concern for social order and support of “law and order” have long been tinged with racial bias. Rhetoric and policies aimed at promoting a “color-blind” social order have served as fronts for maintaining racial inequality (Bonilla-Silva 1997, 2015). Efforts to eradicate racial stratification through collective action, from abolition (Stamatov 2015) to civil rights (Andrews 2004), have often been cast as assaults on the social order by their opponents (Noll 2010; Tisby 2020). As scholars of social movements note, opposition to contentious protest can be viewed as a form of social control (Gamson 1990; McAdam, Tarrow, and Tilly 2001), and in the United States, opposition to racial justice movements has been closely linked with efforts to maintain the racial status quo (McVeigh, Myers, and Sikkink 2004).

The concern for social order, and its racial undertones, contrasts with the predominant concern of most social movements: social justice. “Injustice frames” are central to collective action and are often used to motivate participants to resist institutions and actors who are described as perpetuating unjust and oppressive conditions (Gamson 1992; McAdam et al. 2001; Tilly 1978). Thus, the conflict between protest movements and the political authorities they target can be seen, in part, as a conflict between concerns for social justice and concerns for social order. As Charles Tilly (1969) observed,

Collective violence has flowed regularly out of the central political processes of western countries. . . . The oppressed have struck in the name of justice, the privileged in the name of order, the in-between in the name of fear. (p. 5)

Although collective action on behalf of social justice or social order is often stratified by position in society, attitudes about such collective action are more variable. Public support for protest, violent or otherwise, and for aggressive policing of protests, violent or otherwise, is conditioned by several factors beyond social position, as discussed earlier. “Law and order” does not resonate with everyone, and the resonance of repression cuts across many different factors.

A Moral Intuitionist Approach

Research in moral psychology has sought to understand how and why individuals make moral judgments and how this influences support for or opposition to other attitudes and behaviors. MFT has proved useful for sociological research on the moral causes and consequences of Americans’ political and social views (Feinberg and Willer 2013; Goff, Silver, and Sigfusdottir 2022; Miles and Upenieks 2018; Robbins and Kiser 2020; Silver and Silver 2021; Vaisey and Miles 2014). Recent sociological research has extended these insights to explain divergent attitudes toward protests and policing (Silver et al. 2022; J. R. Silver 2020).

Moral intuitions, according to MFT, are cognitive modules that evolved within societies to regulate interpersonal behavior and social cohesion (Haidt 2012). MFT organizes people’s moral intuitions into two conceptually distinct domains: “individualizing” intuitions that sensitize people to the harm or mistreatment of others and “binding” intuitions that sensitize people to violations of the social order. Individualizing intuitions, according to MFT, evolved to enhance interpersonal relationships through the promotion of rights, autonomy, and reciprocity, and binding moral intuitions evolved to enhance group cohesion through the promotion of loyalty, hierarchy, and protection of the sacred (Graham et al. 2011).

In MFT, these two domains are derived from five constituent moral intuitions referred to as “moral foundations” (Graham et al. 2011). Two moral foundations contribute to an individual’s individualizing moral intuitions: the care/harm foundation, which is rooted in the evolutionary challenge of child rearing, “makes us sensitive to signs of suffering and need” and “makes us despise cruelty and want to care for those who are suffering” (Haidt 2012:153). The fairness/cheating foundation, which is rooted in the evolutionary challenge of forming cooperative non-kin relationships, “makes us sensitive to indications that another person is likely to be a good (or bad) partner for collaboration and reciprocal altruism,” and “makes us want to shun or punish cheaters” (Haidt 2012:153). Three additional moral foundations contribute to an individual’s binding moral intuitions: the loyalty/betrayal foundation, which is rooted in the evolutionary challenge of forming cohesive groups, emphasizes loyalty to nations, families, interest groups, and teams and “makes us sensitive to signs that another person is (or is not) a team player” (Haidt 2012:154). The authority/subversion foundation, which is rooted in the evolutionary challenge of maintaining functioning hierarchies, “makes us sensitive to signs of rank or status, and to signs that other people are (or are not) behaving properly, given their position” (Haidt 2012:154). Finally, the sanctity/degradation foundation, which is rooted in the evolutionary challenge of strengthening groups by encouraging reverence toward sacred totems, makes “people feel that some things, actions, and people are noble, pure, and elevated; [while] others are base, polluted, and degraded” (Haidt 2012:174). The individualizing moral foundations of care/harm and fairness/cheating are highly correlated with each other, as are the binding moral foundations of loyalty/betrayal, authority/subversion, and sanctity/degradation, supporting their grouping in these two domains (Graham et al. 2011).

It is important to note that binding and individualizing moral intuitions are conceptually distinct within MFT (Graham et al. 2011; Haidt, Graham, and Joseph 2009), with studies showing that they tend to be modestly and positively correlated with each other (Goff et al. 2022; Niemi and Young 2016; Silver and Silver 2017, 2021). Following from this, the two domains of moral intuitions also overlap empirically, and individuals may exhibit strong individualizing moral intuitions and weak binding moral intuitions, a pattern typically observed among political liberals in the United States, or their moral intuitions may be more equally distributed across the two domains, a pattern typically observed among U.S. conservatives (Graham, Haidt, and Nosek 2009).

MFT claims that moral intuitions are developed through social learning (Haidt et al. 2009), and a good amount of research demonstrates that factors such as gender (Graham et al. 2011), education (Feldman 2021; Napier and Luguri 2013), social class (Vaisey and Miles 2014), religion (Graham et al. 2009; Miles 2014), cohort (Miles 2014; Vaisey and Miles 2014), and nationality (Graham et al. 2011; Shweder et al. 1993) play a role in shaping individual- and group-oriented moral values. This line of research thus extends research on moral intuitions beyond individual psychology. In short, MFT argues that evolutionarily prepared moral foundations develop in individuals through socialization within families, communities, interest groups, and nations, differentially sensitizing individuals to react to moral violations (Haidt 2012). This variation makes MFT useful for examining Americans’ divergent responses to such morally laden issues as Trump’s “law and order” response to the 2020 racial justice protests.

Moral Intuitions and Support for Trump’s Law and Order Response

Understanding the resonance of social movement frames and counterframes has been an important task within social movement research (Benford and Snow 2000; Hewitt and McCammon 2004). The categorization of moral intuitions as individualizing and binding suggests that certain frames may resonate with one set of intuitions more than the other, and strong moral intuitions in either the individualizing or binding domain may influence individuals to support actors and institutions which promote the moral principles of that domain (Broćić and Miles 2021; Goff et al. 2022; Silver et al. 2022).

Several studies have documented a link between individualizing and binding moral intuitions and American’s attitudes toward justice-related issues. These studies find that binding moral intuitions are associated with a preference for more punitive criminal justice policies, whereas individualizing moral intuitions show the opposite association (Silver and Silver 2017; Vaughan et al. 2019). Another study revealed a similar pattern with acceptance of police use of force: binding moral intuitions were positively associated and individualizing moral intuitions were negatively associated (J. R. Silver 2020). Replicating these studies and extending them to social movements, Silver et al. (2022) found that individualizing moral intuitions were positively associated with support for BLM and negatively associated with support for police; the opposite associations were found for binding moral intuitions. No studies, to our knowledge, have examined the link between moral intuitions and attitudes toward repression of protest movements by the state.

Building on prior research, we argue that the “law and order” frame will resonate with binding moral intuitions—that is, intuitions emphasizing societal stability, hierarchy, and cohesion—thereby eliciting a social order response in support for protest repression. Individualizing moral intuitions, which emphasize care and protection of the vulnerable, in contrast, will elicit a social justice response characterized by opposition to the repression of protest. Our first two hypotheses are, therefore, as follows:

Hypothesis 1: Binding moral intuitions will be associated with support for Trump’s “law and order” response to the 2020 racial justice protests.

Hypothesis 2: Individualizing moral intuitions will be associated with opposition to Trump’s “law and order” response to the 2020 racial justice protests.

The Mediating Role of Skepticism toward Racial Injustice

The “law and order” frame not only taps into concerns for social order but, as many have noted, can also function as a “dog whistle” for unacceptable racial animus (Drakulich et al. 2020; Thompson and Busby forthcoming). Although systemic racism (i.e., laws, policies, norms, and institutions that disadvantage Black people) has long been part of scholarly discussions (Bonilla-Silva 1997), the BLM movement, particularly the protests following the murder of George Floyd, have decidedly shifted public discourse toward discussion of systemic racism (Dunivin et al. 2022; Riley and Peterson 2020). Just as “law and order” has been used to justify police use of force, it has also been used stoke skepticism toward claims of systemic racism in policing, blaming Black citizens for instances of police brutality (Burns 2020b; Falconer 2020).

However, researchers have yet to fully examine the influence of systemic racism beliefs per se on Americans’ attitudes toward protest movements. Only one study, to our knowledge, has attempted this. Silver et al. (2022) found that individualizing moral intuitions influence people to support BLM and oppose police through increasing belief in systemic racism in policing, whereas binding moral intuitions increase skepticism, opposition to BLM, and support for police. This research suggests that the claims of BLM protesters concerning racial injustice by police likely resonate differently with people’s different moral intuitions. Considering this, we examine skepticism toward racial injustice by police as a potential mediating factor in the relationship between moral intuitions on support for repression.

Specifically, we conceptualize skepticism toward racial injustice by police as rooted in a person’s moral intuitions. To be skeptical of racial injustice by police is to be skeptical of the claim that racial injustice is a fundamental feature of society (Delgado and Stefancic 2017), and this skeptical view is at odds with people’s individualizing moral intuitions, which put care and protection of the vulnerable at the center of moral concern. Likewise, to believe that society is rightly ordered and the authorities (police) act legitimately is to reject the notion that racial bias is a dominant cause of police misbehavior. This perspective is skeptical toward critiques of, or threats to, the social order (e.g., police) and is more likely to resonate with people’s binding moral intuitions, which put preservation of the social order at the center of moral concern. We therefore expect that skepticism toward racial injustice by police will track with peoples’ moral intuitions and mediate their association with support Trump’s “law and order” response. Our third and final hypothesis is thus:

Hypothesis 3: Skepticism toward racial injustice by police will mediate the association between moral intuitions and support for Trump’s “law and order” response.

Data and Methods

To test these hypotheses, we use a national survey fielded with Amazon’s Mechanical Turk (MTurk) on June 22, 2020, during the peak in public support for BLM that followed the killing of George Floyd.² Online opt-in surveys such as MTurk are advantageous for capturing public sentiment in a timely manner, and they eliminate interviewer effects, reduce social desirability bias, increase attention, and reduce speeding, compared with other survey methods (Anson 2018; Chang and Krosnick 2009; Hauser and Schwarz 2016; Weinberg, Freese, and McElhattan 2014). Moreover, MTurk samples have yielded comparable results with the General Social Survey (GSS) regarding the direction of statistically significant effects (Thompson and Pickett 2020). The MTurk platform was particularly useful to gather timely data on support of Trump’s “law and order” response during the height of national interest in the post-Floyd protests and when the option of using repressive force was especially salient.

Beginning with 1,058 respondents, we generated an analytic sample of 1,030 using listwise deletion for missing items. Compared with the GSS, our sample is more White (68 percent vs. 64 percent), less Black (10 percent vs. 14 percent), somewhat less Hispanic (15 percent vs. 17 percent), less female (42 percent vs. 54 percent), and more educated (72 percent vs. 33 percent with at least a bachelor’s degree), like many MTurk samples. Online Appendix A provides a comparison between our survey and the 2018 GSS on these measures.

Following Thompson and Pickett (2020), we verify the generalizability of our data using several key measures relevant to our study. Online Appendices B through D show coefficient plots for demographic factors and political ideology in regressions of voting for Trump in 2016, approval of police use of force, and fear of crime. Similarly to Thompson and Pickett (2020), we find that our MTurk sample is comparable with the GSS on these key measures, with most coefficients sharing the same directionality in the models. The MTurk sample, however, is more positive toward Trump for White, Black, Hispanic, and conservative respondents, which we address through several robustness checks. Given our sample’s youth, higher education level, and greater political polarization than the population, our results are perhaps particularly useful for understanding the attitudes of those more likely to engage in protest (Schussman and Soule 2005) or oppose such political action.³

Support for Trump’s “Law and Order” Response

Our dependent variable is a scale of agreement with three statements concerning President Trump’s response to the George Floyd demonstrations that swept the United States in the summer of 2020: (1) President Trump was right for wanting to use the military to keep the George Floyd demonstrations under control, (2) President Trump was right when he described the George Floyd demonstrations as “domestic terror,” and (3) President Trump was right to ask state governors to deploy the National Guard in sufficient numbers to “dominate the streets.” Responses ranged from 1 = strongly disagree to 5 = strongly agree. Cronbach’s α for this scale is .94.

Moral Intuitions

We measure moral intuitions using the 30-item Moral Foundations Questionnaire, shown in online Appendix E (Graham et al. 2011; Haidt 2012). A measure of individualizing moral intuitions was calculated on the basis of the mean of the 12 items in MFT’s care/harm and fairness/cheating foundations (α = .85). A measure of binding moral intuitions was calculated on the basis of the mean of the 18 items included in MFT’s loyalty/betrayal, authority/subversion, and sanctity/degradation foundations (α = .85). The correlation between the individualizing and binding moral intuitions scales is r = .113 (p < .001), consistent with prior research (Goff et al. 2022; Niemi and Young 2016; Silver et al. 2022).

Skepticism toward Racial Injustice by Police

We construct a scale of skepticism toward racial injustice by police using five agree/disagree statements: (1) Black citizens usually exaggerate when they complain about mistreatment by police; (2) in many instances, police brutality is reported when the police have in fact acted appropriately; (3) Black citizens often falsely accuse police of brutality in order to draw attention away from their own wrongdoing; (4) if Black citizens were more respectful to police, police would treat them better; and (5) Black citizens need to take more responsibility for how they end up being treated by police. Responses ranged from 1 = strongly agree to 5 = strongly disagree, so that higher values indicate greater skepticism toward racial injustice by police. Cronbach’s α for this scale is .94.

Controls

Protest Exposure

To control for exposure to protest, we use three measures. First, we use distance to the nearest violent protest, calculated using information from the Crowd Counting Consortium on the geolocation of racial justice protests from May 25 (George Floyd’s death) to June 22 (the date of the survey). We calculated the respondents’ distance to the nearest protest by using the respondents’ latitude and longitude at the time of the survey.⁴ Because some respondents were out of their home states at the time of the survey, we include a control for out of state.⁵ Second, we include a measure of the number of violent protests in the respondent’s state, and third, we include the average size of these protests.⁶ The average size of protests in the state was constructed from a categorical measure of the size of each protest: 0 = unknown⁷; 1 = 1 to 99; 2 = 100 to 999; 3 = 1,000 to 9,999; and 4 = 10,000 or more. Table 1 shows descriptive statistics for all variables.

Table 1.

Descriptive Statistics.

Variable	n	Mean/Proportion	SD	Minimum	Maximum
Support for Trump repression	1,041	2.72	1.46	1	5
Individualizing MF	1,040	4.02	.75	1	5
Binding MF	1,040	3.18	.89	1	5
Logged distance to protest	1,041	2.40	1.42	−5.58	7.78
Number of violent protests, state	1,041	21.08	20.64	0	81
Average size of protests, state	1,041	1.18	.14	.65	1.79
Out of state	1,041	.23		0	1
Cold to BLM	1,041	.25		0	1
Skepticism toward racial justice	1,041	2.85	1.28	1	5
White, NH	1,041	67.50		0	1
Black, NH	1,041	9.81		0	1
Hispanic	1,041	15.10		0	1
Other	1,041	7.60		0	1
Urbanicity	1,041	2.58	1.03	1	4
Religious importance	1,039	3.04	1.58	1	5
Female	1,041	.42		0	1
Age	1,038	40.61	11.64	19	83
Education	1,040	2.78	.95	1	4
Income	1,040	3.89	1.45	1	6
Southern	1,041	.41		0	1
Conservatism	1,040	2.75	1.26	1	5
News interest	1,039	3.35	.70	1	4
Law enforcement	1,037	.10		0	1

Note: BLM = Black Lives Matter; MF = moral foundation; NH = non-Hispanic.

Negativity toward BLM

To distinguish both support for Trump’s “law and order” response and skepticism toward the racial injustice in policing frame from general opposition to BLM, we control for respondents’ attitude toward BLM using a thermometer measure that ranges from 0 (cold) to 100 (warm). We reverse-coded the measure such that higher values indicate less favorable feelings toward BLM.

We measure conservatism with a scale from 1 = very liberal to 5 = very conservative, on the basis of self-report. Importance of religion is measured on a scale from 1 = very unimportant to 5 = very important.

Race is measured by dummy variables for non-Hispanic White, non-Hispanic Black, Hispanic, and other, with non-Hispanic White as the reference category. Respondent sex is measured using a dummy variable called female. Age is measured in years. Education is measured on the basis of the respondent’s highest level of schooling, coded from 1 = high school graduate or less to 4 = graduate or professional degree. Income is the annual total for the household and is coded from 1 = less than $20,000 to 6 = $100,000 or more.

We control for residential urbanicity, measured by the “type of area” in which respondents reported living, coded from 1 = rural area or small town to 4 = major city. We also include an indicator of whether the respondent is from a southern state. Interest in the news is measured on the basis of self-reported “interest in keeping up with current events by listening to, watching, or reading about the news” and is coded 1 = not at all interested to 4 = very interested. We also include a measure indicating if the respondent has ever worked in law enforcement.

In our analysis, we use ordinary least squares regression to estimate a base model with all the controls only. Then we include the moral intuitions measures, followed by the skepticism toward systemic racism measure. We then provide the results of a mediation analysis for the skepticism toward racial injustice by police measure. We center and standardize all continuous variables to aid in comparing the coefficients. The variance inflation factor (VIF) never exceeds 1.37 for any model or 2.18 for any variable, well below the recommended threshold of 4. Online Appendix F provides the pairwise correlation matrix for the study variables.

Results

The first model in Table 2 shows the moral intuitions measures with all controls. Consistent with hypotheses 1 and 2, binding moral intuitions are positively associated with support for Trump’s “law and order” response (b = .361, p < .001), and individualizing moral intuitions are negatively associated (b = –.120, p < .001). Compared with a control-only model (not shown), the inclusion of the moral intuitions measures increased the adjusted R² value by 16 percent (from .483 to .560), as confirmed by a log-likelihood ratio test (χ² = 166.38, df = 2, p < .001), thus verifying that moral intuitions contribute significantly to explaining support for Trump’s “law and order” response (results available upon request). Importantly, moral intuitions influence their support for “law and order” net of their actual experience of protest violence; the coefficient for the number of violent protests in the state is significant at the p < .05 level (b = .049). We thus find support for the first two hypotheses that moral intuitions explain peoples support for Trump’s “law and order” response, net of exposure to violent protest and important demographic and ideological factors.

Table 2.

Support for Trump’s ‘Law and Order’ Response to 2020 Protests.

	Model 1		Model 2
	b	SE	b	SE
Individualizing MF	−.120***	.03	−.049*	.02
Binding MF	.361***	.03	.150***	.03
Skepticism toward racial injustice			.528***	.03
Log distance to violent protest	.026	.02	.016	.01
Number of violent protests, state	.049*	.02	.040*	.02
Average size of protests, state	.026	.02	.032	.02
Cold to BLM	.271***	.03	.107***	.02
Black, NH	−.280**	.09	−.143*	.07
Hispanic	.242**	.07	.096	.05
Other race	−.315***	.08	−.220**	.07
Urbanicity	.007	.02	.002	.02
Religious importance	.066*	.03	.057*	.02
Female	.006	.04	.052	.04
Age	−.037	.02	−.033	.02
Education	.029	.02	−.003	.02
Income	−.008	.02	.0004	.02
Southern	.02	.05	.030	.04
Conservatism	.270***	.03	.167***	.03
News interest	.029	.02	.029	.02
Law enforcement	.182*	.08	.112*	.05
Out of state	.09	.05	.074	.04
Constant	−.099	.06	−.087	.05
n	1,030		1,030
R ²	.568		.695
Adjusted R²	.560		.689
BIC	2,204.62		1,851.97

Note: Ordinary least squares regression of support for Trump’s “law and order” response on independent variables is presented, with heteroskedastic robust standard errors. BLM = Black Lives Matter; MF = moral foundation; NH = non-Hispanic.

p < .05. **p < .01. ***p < .001.

Next, we include our measure of skepticism toward racial injustice by police. As shown in model 2, skepticism is strongly and positively associated with support for Trump’s “law and order” response (b = .528, p < .001). The model also shows that the coefficient for individualizing moral intuitions is reduced by 59 percent, resulting in a direct effect of b = –.048 (p < .05). We calculated an indirect effect of individualizing moral intuitions predicting support for Trump’s “law and order” response through skepticism toward racial injustice by police of b = –.072, and Karlson-Holm-Breen analysis indicates that this indirect effect is significant at the p < .01 level (SE = .022). We also find that when accounting for skepticism toward racial injustice by police, the coefficient for binding moral intuitions is reduced by 58 percent, resulting in a direct effect of b = .150 (p < .001) and an indirect effect of b = .211 (p < .001, SE = .025). This means that for both individualizing and binding moral intuitions, more than half of the association with support for Trump’s “law and order” response is mediated through skepticism toward racial injustice by police.⁸

In sum, we find support for hypothesis 3, that skepticism toward racial injustice by police mediates much of the association between the moral intuitions measures and support for Trump’s “law and order” response. Our results suggest that concerns about care, fairness, and the protection of the vulnerable—individualizing moral intuitions associated with a social justice orientation—and concerns about stability, hierarchy, and social cohesion—binding moral intuitions associated with a social order orientation—are important independent sources of support or opposition to “law and order” responses to protests. Our results also suggest that moral intuitions influence peoples’ support for Trump’s “law and order” response in part because they influence their beliefs about racial injustice by police that lie at the heart of protest movements such as BLM. The path coefficients for the above analysis are shown in Figure 1, and regression coefficients predicting our measure of skepticism toward racial injustice by police are presented in online Appendix E.

Figure 1.

Path analysis results predicting support for Trump’s “law and order” response to the 2020 racial justice protests (n = 1,030).

Robustness

Several robustness checks are in order. First, we test that support for Trump’s “law and order” response is not a proxy for support for Trump himself. We included measures in the full model of whether respondents voted for Trump in the 2016 election or planned to in the 2020 election. In both models, individualizing moral intuitions lost statistical significance, but not binding moral intuitions (b = .144, p < .001). This suggests that the effect of moral intuitions, especially the binding moral intuitions, on support for Trump’s “law and order” response is not explained merely by support for Trump.

Second, skepticism toward racial injustice by police may proxy for racial resentment. We estimated the full model with a measure of racial resentment (Kinder and Sears 1981). Again, individualizing moral intuitions lost statistical significance, but binding did not (b = .123, p < .001). Skepticism toward racial injustice remained significant (b = .422, p < .001), and racial resentment was significant (b = .200, p < .001). The mean VIF for this model was 1.50, and no coefficient had a VIF above 3.1, well below the rule of thumb of 4.0 for multicollinearity.

Third, our model may not account for perception of racial threat. We constructed a measure of perceived threat from Black people using two questions: one that asks how much of the racial tension in the United States is attributable to Black people and a second that asks whether Black people have too much influence in public affairs (Cronbach’s α = .77). Again, with this measure of perceived Black threat included in the full model, individualizing moral intuitions lost statistical significance but binding did not (b = .136, p < .001). Skepticism toward racial injustice remains statistically significant (b = .437, p < .001), and perception of Black threat is also significant (b = .176, p < .001). The mean VIF for this model was 1.47, and no coefficient had a VIF above 2.88, well below the rule of thumb of 4.0 for multicollinearity.⁹

In support of our argument, these robustness checks suggest that effects of binding moral intuitions and skepticism toward racial injustice are distinct from racial resentment, perceptions of Black threat, and voting for Trump.¹⁰ These robustness checks also suggest that the link between individualizing moral intuitions and support for Trump’s “law and order” response is more closely tied to attitudes about race, racism, and support for Trump himself, whereas the link between binding moral intuitions is largely independent of these attitudes. Given our nonprobability sample and the similarity of some of these robustness variables, conclusions about how they interact with moral intuitions and skepticism toward racial injustice measures should be interpreted with caution. However, that our key independent variables are robust to multiple specifications provides additional support for our hypotheses.

Discussion

In this study we used MFT (Graham et al. 2011; Haidt 2012) to examine the influence of individualizing and binding moral intuitions on Americans’ support for President Trump’s “law and order” response to the 2020 racial justice protests. We found that binding moral intuitions that put social order at the center of moral concern increased support for Trump’s response, and individualizing moral intuitions that put caring for the vulnerable at the center of moral concern decreased support for Trump’s “law and order” response.

The limited research on public support for the repression of protest movements has shown that fear of violence, opposition to the ideology of the movement, and racially motivated opposition to the claims of protesters can strongly influence support for repression. Ours is the first study to show that moral intuitions also matter. Explaining variation in support for Trump’s “law and order” response net of many other important factors was a high bar for the moral intuitions measures to clear. These results demonstrate the need to investigate the moral-intuitive underpinnings of support for and opposition to social movements, especially as it relates to the moral dimensions of resonance with movement frames and counterframes.

We also find that skepticism toward the claims of BLM and other racial justice protesters—that the police are racially unjust—mediated more than half of the effect of both the individualizing and binding moral intuitions. Our findings thus suggest that individualizing moral intuitions led people to take a social justice perspective by decreasing their skepticism toward (or increasing their belief in) racial injustice by police, which in turn decreased support for (or increased opposition to) Trump’s “law and order” response. Our findings also suggest that binding moral intuitions led people to take a social order perspective by increasing their skepticism regarding racial injustice by police, which, in turn, led them to support Trump’s “law and order” response.

Our results suggest several new directions for research on public attitudes regarding repression and protest. First, protests carry symbolic meaning beyond the particular issues they address, and this meaning is tied to concerns about social order in general (McAdam et al. 2001; Tilly 1969). In the case of racial justice movements, some argue that this symbolic meaning is racially charged, and opposition to such protests is racially motivated (Cole 2020; Drakulich et al. 2020; Riley and Peterson 2020). Scholars have further argued that “law and order” counterframing serves as a “dog whistle”; that is, it stands in for an unexpressed (or inexpressible) racist motivations, presented in other terms, which some have termed symbolic racism (Kinder and Sears 1981; López 2014; Pettigrew 1989). We see merit in the dog whistle concept.

Our results suggest an additional perspective: racialized attitudes may operate alongside, or in conjunction with, individualizing and binding moral intuitions. Americans may express support for “law and order” responses as a means of expressing their more difficult-to-articulate moral intuitions related to social order and the fear that protests will produce chaos. This notion is supported by the robust influence of respondents’ binding moral intuitions on their support for Trump’s “law and order” response, net of skepticism, racial resentment, and other relevant factors.

This conclusion has important implications for social movement research and practice. First, because protest movements are often framed in terms of social justice and the response of the state is often framed in terms of social order (Gamson 1992; Tilly 1969), supporting one or the other is likely to reflect a person’s underlying moral intuitions regarding social justice or social order. Our results lead us to conclude that “law and order” as a justification for repression of protests may function as a “dog whistle” at two levels—at the level of skepticism about movement framing and at the level of individuals’ moral intuitions.

Second, social movement framing draws on moral values, morally laden narratives, and morally charged emotions to motivate potential participants (Benford and Snow 2000; Jasper 2008; Polletta et al. 2011). When social movements frame their efforts in terms of social justice, and when states frame their policing of protests in terms of social order, they limit their resonant capacity. The strategic advantage of balancing moral concerns for social justice and social order is evidenced in some studies of effective social movement framing. In Hewitt and McCammon’s (2004) study of the women’s suffrage movement, they found that suffrage advocates were most effective in securing state-level suffrage for women when their local messaging achieved a balance between supporting the dominant social order concerning women’s roles and challenging this order through advocating for women’s full political participation. Our study highlights the moral-intuitive underpinnings of such framing efforts, suggesting that concerns for social justice or social order need not be opposed to each other and that examining the moral intuitions underlying frame disputes may reveal how effective social movement frames, which draw on a diversity of moral intuitions, enable movements to succeed (McCammon et al. 2001).

Along these lines, the “fast thinking,” intuitive nature of moral intuitions (Haidt 2012; cf. Kahneman 2013) may also explain why a person who possesses strong moral intuitions in both the individualizing and binding domains may express support for racial justice and for “law and order” without seeing these two stances as contradictory. According to MFT, individualizing and binding moral intuitions are conceptually distinct and vary independently of one another. Therefore, it is critical that empirical research identify situational, positional (e.g., race and class), and emotional patterns in which different moral intuitions are likely to be activated (Luft 2020). MFT was developed to better understand political polarization (Haidt 2012; cf. Morson and Shapiro 2021), but polarization cuts across political, religious, and other ideological affiliations (DellaPosta 2020; Whitehead and Perry 2020). Therefore, future researchers should investigate how various combinations of moral intuitions motivate individuals’ responses in different contexts to a variety of types of protest movements.

This study is not without limitations. First, the data were drawn from a single survey administered using Amazon’s MTurk in June 2020, during the peak in public support for BLM that followed the killing of George Floyd. The degree to which our results generalize to other time periods is thus unknown, as is the degree to which they reflect what might be found using a national probability sample, given the positive educational skew of the sample. Online surveys such as MTurk have some advantages, as noted above. However, the results must be interpreted with an appropriate amount of caution.

Second, our measures of proximity to protest were not as precise as we would have liked. MTurk survey respondents are likely more technologically engaged, and it is unsurprising that many were traveling when completing the survey. Therefore, our measure of distance to a violent protest was not as accurate as it could have been and knowing only respondents’ state of residence did not provide sufficient resolution for estimating exposure to the number of violent or large protests. County-level estimates would have been preferable (Andrews et al. 2016).

Third, we did not have adequate measures of exposure to news media beyond our question about interest in the news. Recent studies have illustrated the importance of where individuals get their news for their political attitudes, including attitudes toward BLM and racial justice (Reny and Newman 2021; Wasow 2020). These and other studies (Goff and McCarthy 2021, 2022) note the apparent mismatch between perceptions of the 2020 protests and what actually happened, likely because of exposure to different media framings. Future research should therefore consider how media framing interacts with peoples’ moral intuitions and how moral intuitions may be influenced by or facilitate attachment to particular media outlets.

Conclusion

Americans generally support protest movements and oppose repression (Metcalfe and Pickett 2022). Nonetheless, many resonated with Trump’s “law and order” response to the 2020 racial justice protests. In this study, we found that a significant amount of divergence in support for Trump’s “law and order” response is explained by people’s moral intuitions. This finding is important, as messaging from and about protest movements is increasingly subject to filtering and framing via rapid and diffuse social media platforms and outlets, making it more likely that gut-level moral-intuitive responses may play a role in forming judgements about movements and their aims. Having a better understanding of the moral-intuitive underpinnings of Americans’ divergent reactions to such messaging may help movement organizers, law enforcement and policymakers better address polarized responses. Thus, in addition to informing future research, we hope the results of this study will help movement organizers and other interested stakeholders craft messages that reach the broadest possible audience so that issues of racial injustice can be redressed to establish a more just social order.

Supplemental Material

sj-docx-1-srd-10.1177_23780231221110277 – Supplemental material for The Resonance of Repression: Moral Intuitions, Skepticism toward Racial Injustice, and Public Support for Trump’s “Law and Order” Response to the 2020 Racial Justice Protests

Supplemental material, sj-docx-1-srd-10.1177_23780231221110277 for The Resonance of Repression: Moral Intuitions, Skepticism toward Racial Injustice, and Public Support for Trump’s “Law and Order” Response to the 2020 Racial Justice Protests by Kerby Goff, Eric Silver and John Iceland in Socius

Footnotes

ORCID iD

Kerby Goff

Supplemental Material

Supplemental material for this article is available online.

1

Repression is used in the literature as an analytic category, applicable to the suppression of protest regardless of movement ideology, tactics, or legality, though state repression of protests occurs more often with left-leaning movements (Wood 2020) and violent protests ().

2

The MTurk platform employs eligible “workers” to select and perform various online “human intelligence tasks” for a small financial incentive, in this case $2. Eligible respondents included MTurk workers 18 years or older who lived in the United States and who, for high-quality respondents, had completed more than 500 previous human intelligence tasks and who had 95 percent or higher approval ratings (Graham et al. 2020; Peer, Vosgerau, and Acquisti 2014).

3

Additional models with survey weights to match population demographic and education measures from the 2019 American Community Survey and a political ideology measure from the 2018 GSS produced very similar results. Results are available in the .

4

We calculate distances in Stata using the user-written command geonear ().

5

About one quarter of respondents were out of state when taking the survey. The out-of-state variable is never significant, indicating that respondents’ out-of-state location did not bias their attitudes toward Trump’s repression.

6

We also estimated models using the state- and county-level counts of violent protests and average size of protests for the respondents’ location at the time of the survey. Results were similar but with greater standard errors.

7

We also estimated models with all protests of unknown size removed. Results on key independent variables were unchanged. The coefficient for the number of violent protests in the state was lower and not statistically significant. We left these protests in the final model because protests of unknown size are likely very small. The mean size of protests in category 1 (1–99) is 36, and thus category 0 serves as a meaningful lowest level category in the measure.

8

Auxiliary analysis with the Stata command medeff provides similar results. We used medsens to examine the sensitivity of this model to unexamined confounders, which showed that any confounder must explain a high proportion of the unexplained variance for both the outcome and mediator (e.g., 50 percent and 55 percent, respectively) to reduce the indirect effect to zero. It is thus safe to conclude that our mediation results are robust. Results are available in .

9

Results were the same with voting for Trump, racial resentment, and Black threat all included in the same model, and multicollinearity was minimal, as both the mean and the maximum VIF score remained below 4.

10

It is possible that racial resentment, Black threat, skepticism toward racial injustice, and coldness toward BLM might derive from the same underlying construct. Principal-factor analysis suggests that there are four factors that generally follow the same divisions as our skepticism, racial resentment, and Black threat scales, along with the coldness to BLM measure. Our skepticism toward racial injustice by police scale explains most of the variation in these measures: 88.8 percent (eigenvalue = 6.61). This suggests that skepticism toward racial injustice by police accounts for much of the common variance with racial resentment, perceptions of Black threat, and coldness toward BLM, but not all. Given our nonprobability sample, these results should be interpreted with caution. Factor analysis results are available in .

Author Biographies

Kerby Goff is a PhD candidate in the Department of Sociology and Criminology at Penn State University. His research focuses on social movements at the intersection of gender, education, and religion.

Eric Silver is a professor in the Department of Sociology and Criminology at Penn State University. His research focuses on morality, deviance, punishment, and public opinion.

John Iceland is a distinguished professor in the Department of Sociology and Criminology at Penn State University. His research focuses on social inequality in the United States.

References

Andrews

Kenneth T.

2004. Freedom Is a Constant Struggle: The Mississippi Civil Rights Movement and Its Legacy. Chicago: University of Chicago Press.

Andrews

Kenneth T.

Beyerlein

Kraig

Tucker Farnum

Tuneka

. 2016. “The Legitimacy of Protest: Explaining White Southerners’ Attitudes toward the Civil Rights Movement.” Social Forces 94(3):1021–44.

Anson

Ian G.

2018. “Taking the Time? Explaining Effortful Participation among Low-Cost Online Survey Participants.” Research & Politics 5(3):1–18.

Beckett

Katherine

Sasson

Theodore

. 2004. The Politics of Injustice: Crime and Punishment in America. 2nd ed. Thousand Oaks, CA: Sage.

Benford

Robert D.

Snow

David A.

2000. “Framing Processes and Social Movements: An Overview and Assessment.” Annual Review of Sociology 26:611–39.

Bonilla-Silva

Eduardo

. 1997. “Rethinking Racism: Toward a Structural Interpretation.” American Sociological Review 62(3):465.

Bonilla-Silva

Eduardo

. 2015. “The Structure of Racism in Color-Blind, ‘Post-racial’ America.” American Behavioral Scientist 59(11):1358–76.

Broćić

Miloš

Miles

Andrew

. 2021. “College and the ‘Culture War’: Assessing Higher Education’s Influence on Moral Attitudes.” American Sociological Review 86(5):856–95.

Buchanan

Larry

Bul

Quoctrung

Patel

Jugal K.

2020. “Black Lives Matter May Be the Largest Movement in U.S. History.” The New York Times. Retrieved October 10, 2021. https://www.nytimes.com/interactive/2020/07/03/us/george-floyd-protests-crowd-size.html/.

10.

Burns

Katelyn

. 2020a. “Trump Responded to the Protests by Lashing out at Antifa, the Media, and Democrats.” Vox. Retrieved August 25, 2021. https://www.vox.com/policy-and-politics/2020/5/31/21276156/trump-antifa-media-local-democratic-leaders-protests.

11.

Burns

Katelyn

. 2020b. “Trump’s Latest Tweets Are from an Alternate Reality Where the Protests Are out of Control.” Vox. Retrieved August 5, 2021. https://www.vox.com/policy-and-politics/2020/6/3/21279088/trump-tweets-alternate-reality-george-floyd-protests/.

12.

Chang

Linchiat

Krosnick

Jon A.

2009. “National Surveys via RDD Telephone Interviewing versus the Internet: Comparing Sample Representativeness and Response Quality.” Public Opinion Quarterly 73(4):641–78.

13.

Chenoweth

Erica

Pressman

Jeremy

. 2020. “This Summer’s Black Lives Matter Protesters Were Overwhelmingly Peaceful, Our Research Finds.” The Washington Post. Retrieved September 4, 2021. https://www.washingtonpost.com/politics/2020/10/16/this-summers-black-lives-matter-protesters-were-overwhelming-peaceful-our-research-finds/.

14.

Clément

Maéva

Lindemann

Thomas

Sangar

Eric

. 2017. “The ‘Hero-Protector Narrative’: Manufacturing Emotional Consent for the Use of Force.” Political Psychology 38(6):991–1008.

15.

Cole

Geneva

. 2020. “Types of White Identification and Attitudes about Black Lives Matter.” Social Science Quarterly 101(4):1627–33.

16.

Davenport

Christian

. 2007. “State Repression and Political Order.” Annual Review of Political Science 10(1):1–23.

17.

Davenport

Christian

Soule

Sarah A.

Armstrong

David A.

2011. “Protesting while Black? The Differential Policing of American Activism, 1960 to 1990.” American Sociological Review 76(1):152–78.

18.

Delgado

Richard

Stefancic

Jean

. 2017. Critical Race Theory: An Introduction. 3rd ed. New York: New York University Press.

19.

DellaPosta

Daniel

. 2020. “Pluralistic Collapse: The ‘Oil Spill’ Model of Mass Opinion Polarization.” American Sociological Review 85(3):507–36.

20.

Drakulich

Kevin

Wozniak

Kevin H.

Hagan

John

Johnson

Devon

. 2020. “Race and Policing in the 2016 Presidential Election: Black Lives Matter, the Police, and Dog Whistle Politics.” Criminology 58(2):370–402.

21.

Dunivin

Zackary Okun

Yan

Harry Yaojun

Ince

Jelani

Rojas

Fabio

. 2022. “Black Lives Matter Protests Shift Public Discourse.” Proceedings of the National Academy of Sciences 119(10):e2117320119.

22.

Earl

Jennifer

. 2003. “Tanks, Tear Gas, and Taxes: Toward a Theory of Movement Repression.” Sociological Theory 21(1):44–68.

23.

Earl

Jennifer

Soule

Sarah A.

McCarthy

John D.

2003. “Protest under Fire? Explaining the Policing of Protest.” American Sociological Review 68(4):581–606.

24.

Edwards

Pearce

Arnon

Daniel

. 2021. “Violence on Many Sides: Framing Effects on Protest and Support for Repression.” British Journal of Political Science 51(2):488–506.

25.

Falconer

Rebecca

. 2020. “Trump Says Black Lives Matter Is ‘Discriminatory’ and ‘Bad for Black People.’” Axios. Retrieved August 25, 2021. https://www.axios.com/trump-black-lives-matter-bad-for-black-people-0094dbef-e0ea-40f3-b905-4a45189ccc4c.html.

26.

Feinberg

Matthew

Willer

Robb

. 2013. “The Moral Roots of Environmental Attitudes.” Psychological Science 24(1):56–62.

27.

Feldman

Gilad

. 2021. “Personal Values and Moral Foundations: Examining Relations and Joint Prediction of Moral Variables.” Social Psychological and Personality Science 12(5):676–86.

28.

Flamm

Michael W.

2005. Law and Order: Street Crime, Civil Unrest, and the Crisis of Liberalism in the 1960s. New York: Columbia University Press.

29.

Gamson

William A.

1990. The Strategy of Social Protest. 2nd ed. Belmont, CA: Wadsworth.

30.

Gamson

William A.

1992. Talking Politics. New York: Cambridge University Press.

31.

Goff

Kerby

McCarthy

John D.

2021. “Critics Claim BLM Protests Were More Violent Than 1960s Civil Rights Ones. That’s Just Not True.” The Washington Post. Retrieved October 12, 2021. https://www.washingtonpost.com/politics/2021/10/12/critics-claim-blm-was-more-violent-than-1960s-civil-rights-protests-thats-just-not-true/.

32.

Goff

Kerby

McCarthy

John D.

2022. “No, Antifa Didn’t ‘Infiltrate’ Black Lives Matter during the 2020 Protests. But Did It Increase Violence?” The Washington Post. Retrieved February 21, 2022. https://www.washingtonpost.com/politics/2022/02/08/antifa-blm-extremism-violence/.

33.

Goff

Kerby

Silver

Eric

Sigfusdottir

Inga Dora

. 2022. “Academic Orientation as a Function of Moral Fit: The Role of Individualizing Morality.” Sociology of Education 95(2):153–70.

34.

González-Sánchez

Ignacio

. 2019. “Symbolic Violence and the Penalization of the Protest.” Revista Internacional de Sociología 77(4):e138.

35.

Graham

Amanda

Cullen

Francis T.

Pickett

Justin T.

Jonson

Cheryl Lero

Haner

Murat

Sloan

Melissa M.

2020. “Faith in Trump, Moral Foundations, and Social Distancing Defiance during the Coronavirus Pandemic.” Socius 6. Retrieved June 19, 2022. https://journals.sagepub.com/doi/10.1177/2378023120956815.

36.

Graham

Jesse

Haidt

Jonathan

Nosek

Brian A.

2009. “Liberals and Conservatives Rely on Different Sets of Moral Foundations.” Journal of Personality and Social Psychology 96(5):1029–46.

37.

Graham

Jesse

Nosek

Brian A.

Haidt

Jonathan

Iyer

Ravi

Koleva

Spassena

Ditto

Peter H.

2011. “Mapping the Moral Domain.” Journal of Personality and Social Psychology 101(2):366–85.

38.

Haidt

Jonathan

. 2012. The Righteous Mind: Why Good People Are Divided by Politics and Religion. New York: Pantheon.

39.

Haidt

Jonathan

Graham

Jesse

Joseph

Craig

. 2009. “Above and below Left–Right: Ideological Narratives and Moral Foundations.” Psychological Inquiry 20(2–3):110–19.

40.

Hauser

David J.

Schwarz

Norbert

. 2016. “Attentive Turkers: MTurk Participants Perform Better on Online Attention Checks Than Do Subject Pool Participants.” Behavior Research Methods 48(1):400–407.

41.

Hewitt

Lyndi

McCammon

Holly

. 2004. “Explaining Suffrage Mobilization: Balance, Neutralization, and Range in Collective Action Frames, 1892–1919.” Mobilization: An International Quarterly 9(2):149–66.

42.

Hsiao

Yuan

Radnitz

Scott

. 2021. “Allies or Agitators? How Partisan Identity Shapes Public Opinion about Violent or Nonviolent Protests.” Political Communication 38(4):479–97.

43.

Jackson

Jonathan

Bradford

Ben

. 2009. “Crime, Policing and Social Order: On the Expressive Nature of Public Confidence in Policing: Crime, Policing and Social Order.” British Journal of Sociology 60(3):493–521.

44.

Jasper

James M.

2008. The Art of Moral Protest Culture, Biography, and Creativity in Social Movements. Chicago: University of Chicago Press.

45.

Kahneman

Daniel

. 2013. Thinking, Fast and Slow. New York: Farrar, Straus.

46.

Kinder

Donald

Sears

David

. 1981. “Prejudice and Politics: Symbolic Racism versus Racial Threats to the Good Life.” Journal of Personality and Social Psychology 40(3):414–31.

47.

López

Ian Haney

. 2014. Dog Whistle Politics: How Coded Racial Appeals Reinvented Racism and Wrecked the Middle Class. Oxford, UK: Oxford University Press.

48.

Luft

Aliza

. 2020. “Theorizing Moral Cognition: Culture in Action, Situations, and Relationships.” Socius 6. Retrieved June 19, 2022. https://journals.sagepub.com/doi/10.1177/2378023120916125.

49.

McAdam

Doug

Tarrow

Sidney G.

Tilly

Charles

. 2001. Dynamics of Contention. Cambridge, UK: Cambridge University Press.

50.

McCammon

Holly J.

Campbell

Karen E.

Granberg

Ellen M.

Mowery

Christine

. 2001. “How Movements Win: Gendered Opportunity Structures and U.S. Women’s Suffrage Movements, 1866 to 1919.” American Sociological Review 66:49–70.

51.

McCarthy

John D.

Martin

Andrew

McPhail

Clark

. 2007. “Policing Disorderly Campus Protests and Convivial Gatherings: The Interaction of Threat, Social Organization, and First Amendment Guarantees.” Social Problems 54(3):274–96.

52.

McVeigh

Rory

Myers

Daniel J.

Sikkink

David

. 2004. “Corn, Klansmen, and Coolidge: Structure and Framing in Social Movements.” Social Forces 83(2):653–90.

53.

Metcalfe

Christi

Pickett

Justin T.

2022. “Public Fear of Protesters and Support for Protest Policing: An Experimental Test of Two Theoretical Models.” Criminology 60(1):60–89.

54.

Miles

Andrew

. 2014. “Demographic Correlates of Moral Differences in the Contemporary.” Poetics 46(October):75–88.

55.

Miles

Andrew

Upenieks

Laura

. 2018. “An Expanded Model of the Moral Self: Beyond Care and Justice.” Social Science Research 72(1):1–19.

56.

Morson

Gary Saul

Shapiro

Morton

. 2021. Minds Wide Shut: How the New Fundamentalism Divides Us. Princeton, NJ: Princeton University Press.

57.

Muñoz

Jordi

Anduiza

Eva

. 2019. “‘If a Fight Starts, Watch the Crowd’: The Effect of Violence on Popular Support for Social Movements.” Journal of Peace Research 56(4):485–98.

58.

Napier

Jaime L.

Luguri

Jamie B.

2013. “Moral Mind-Sets: Abstract Thinking Increases a Preference for ‘Individualizing’ over ‘Binding’ Moral Foundations.” Social Psychological and Personality Science 4(6):754–59.

59.

Nicholson

D. Adam

Valentino

Lauren

. 2021. “Message Received? The Roles of Emotion, Race, and Politics in Social Movements Perceptions and Support.” Mobilization: An International Quarterly 26(1):41–64.

60.

Niemi

Laura

Young

Liane

. 2016. “When and Why We See Victims as Responsible: The Impact of Ideology on Attitudes toward Victims.” Personality and Social Psychology Bulletin 42(9):1227–42.

61.

Noll

Mark A.

2010. God and Race in American Politics: A Short History. Princeton, NJ: Princeton University Press.

62.

Peer

Eyal

Vosgerau

Joachim

Acquisti

Alessandro

. 2014. “National Surveys via RDD Telephone Interviewing versus the Internet: Comparing Sample Representativeness and Response Quality.” Behavior Research Methods 46(4):1023–31.

63.

Pettigrew

Thomas F.

1989. “The Nature of Modern Racism in the United States.” Revue Internationale de Psychologie Sociale 2(3):291–303.

64.

Polletta

Francesca

Bobby Chen

Pang Ching

Gardner

Beth Gharrity

Motes

Alice

. 2011. “The Sociology of Storytelling.” Annual Review of Sociology 37:109–30.

65.

Reny

Tyler T.

Newman

Benjamin J.

2021. “The Opinion-Mobilizing Effect of Social Protest against Police Violence: Evidence from the 2020 George Floyd Protests.” American Political Science Review 115(4):1499–1507.

66.

Riley

Emmitt Y.

Peterson

Clarissa

. 2020. “I Can’t Breathe: Assessing the Role of Racial Resentment and Racial Prejudice in Whites’ Feelings toward Black Lives Matter.” National Review of Black Politics 1(4):496–515.

67.

Robbins

Blaine

Kiser

Edgar

. 2020. “State Coercion, Moral Attitudes, and Tax Compliance: Evidence from a National Factorial Survey Experiment of Income Tax Evasion.” Social Science Research 91:102448.

68.

Schussman

Alan

Soule

Sarah A.

2005. “Process and Protest: Accounting for Individual Protest Participation.” Social Forces 84(2):1083–1108.

69.

Shweder

Richard A.

Haidt

Jonathan

Horton

Randall

Joseph

Craig

. 2008. “The Cultural Psychology of the Emotions.” Pp. 417–31 in Handbook of emotions, edited by Lewis

Haviland-Jones

J. M.

Barrett

L. F.

New York: Guilford Publications.

70.

Silver

Eric

Goff

Kerby

Iceland

John

. 2022. “Social Order and Social Justice: Moral Intuitions, Systemic Racism Beliefs, and Americans’ Divergent Attitudes toward Black Lives Matter and Police.” Criminology 60(20):342–69.

71.

Silver

Eric

Silver

Jasmine R.

2021. “Morality and Self-Control: The Role of Binding and Individualizing Moral Motives.” Deviant Behavior 42(3):366–85.

72.

Silver

Jasmine R.

2020. “Moral Motives, Police Legitimacy and Acceptance of Force.” Policing: An International Journal 43(5):799–815.

73.

Silver

Jasmine R.

Silver

Eric

. 2017. “Why Are Conservatives More Punitive Than Liberals? A Moral Foundations Approach.” Law and Human Behavior 41(3):258.

74.

Simpson

Brent

Willer

Robb

Feinberg

Matthew

. 2018. “Does Violent Protest Backfire? Testing a Theory of Public Reactions to Activist Violence.” Socius 4. Retrieved June 19, 2022. https://journals.sagepub.com/doi/full/10.1177/2378023118803189.

75.

Stamatov

Peter

. 2015. The Origins of Global Humanitarianism: Religion, Empires, and Advocacy. New York: Cambridge University Press.

76.

Stephan

Maria J.

Chenoweth

Erica

. 2008. “Why Civil Resistance Works: The Strategic Logic of Nonviolent Conflict.” International Security 33(1):7–44.

77.

Swaine

Jon

. 2017. “Trump Breaks from Obama with Crime Crackdown and ‘Blue Lives Matter’ Protections.” The Guardian. Retrieved June 19, 2022. https://www.theguardian.com/us-news/2017/feb/09/trump-criminal-justice-reform-police-protections-obama.

78.

Thompson

Andrew Ifedapo

Busby

Ethan C.

Forthcoming. “Defending the Dog Whistle: The Role of Justifications in Racial Messaging.” Political Behavior.

79.

Thompson

Andrew J.

Pickett

Justin T.

2020. “Are Relational Inferences from Crowdsourced and Opt-In Samples Generalizable? Comparing Criminal Justice Attitudes in the GSS and Five Online Samples.” Journal of Quantitative Criminology 36(4):907–32.

80.

Tilly

Charles

. 1969. “Collective Violence in European Perspective.” Pp. 5–34 in Violence in America: Historical and Comparative Perspectives, edited by Graham

H. D.

Gurr

T. R.

Washington, DC: U.S. Government Printing Office.

81.

Tilly

Charles

. 1978. From Mobilization to Revolution. New York: Random House.

82.

Tisby

Jemar

. 2020. The Color of Compromise: The Truth about the American Church’s Complicity in Racism. Grand Rapids, MI: Zondervan.

83.

Vaisey

Stephen

Miles

Andrew

. 2014. “Tools from Moral Psychology for Measuring Personal Moral Culture.” Theory and Society 43(3–4):311–32.

84.

Vaughan

Tyler J.

Holleran

Lisa Bell

Silver

Jasmine R.

2019. “Applying Moral Foundations Theory to the Explanation of Capital Jurors’ Sentencing Decisions.” Justice Quarterly 36(7):1176–1205.

85.

Wasow

Omar

. 2020. “Agenda Seeding: How 1960s Black Protests Moved Elites, Public Opinion and Voting.” American Political Science Review 114(3):638–59.

86.

Weinberg

Jill D.

Freese

Jeremy

McElhattan

David

. 2014. “National Surveys via RDD Telephone Interviewing versus the Internet: Comparing Sample Representativeness and Response Quality.” Sociological Science 1(19):292–310.

87.

Whitehead

Andrew L.

Perry

Samuel L.

2020. Taking America Back for God: Christian Nationalism in the United States. New York: Oxford University Press.

88.

Wood

Lesley

. 2020. “Policing Counter-Protest.” Sociology Compass 14(11):1–10.

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.25 MB

The Resonance of Repression: Moral Intuitions,Skepticism toward Racial Injustice,and Public Support for Trump’s “Law and Order” Response to the 2020 Racial Justice Protests

Abstract

Keywords

Sources of Support for Repression

Protest Violence

Proximity to Protest Violence

Political Affinity

Racial Animus

“Law and Order” as a Repression Frame

A Moral Intuitionist Approach

Moral Intuitions and Support for Trump’s Law and Order Response

The Mediating Role of Skepticism toward Racial Injustice

Data and Methods

Support for Trump’s “Law and Order” Response

Moral Intuitions

Skepticism toward Racial Injustice by Police

Controls

Protest Exposure

Negativity toward BLM

Results

Robustness

Discussion

Conclusion

Supplemental Material

sj-docx-1-srd-10.1177_23780231221110277 – Supplemental material for The Resonance of Repression: Moral Intuitions, Skepticism toward Racial Injustice, and Public Support for Trump’s “Law and Order” Response to the 2020 Racial Justice Protests

Footnotes

ORCID iD

Supplemental Material

1

2

3

4

5

6

7

8

9

10

Author Biographies

References

Supplementary Material