For the good of the party, for the good of the nation: ingroup projection can motivate support for political violence

Support for political violence in the United States appears to be growing. We outline a model that positions ingroup projection—seeing ingroup values as the shared values of a larger inclusive societal group—as a key psychological process through which identification with political ingroups (Democrats/Republicans) and with national superordinate categories (Americans) influence support for political violence. We tested this model in two studies. Study 1 (N = 297) included original survey data collected during the 2016 US Presidential election, and analyses revealed that identification with Democrats or Republicans and identification with Americans both had positive indirect effects on support for political violence that were mediated by ingroup projection. Study 2 (N = 642) provided a preregistered replication of these results using original data collected during the 2022 US Midterm Senate elections. These results provide insight into the psychological processes that underlie support for political violence in the United States and elucidate a generalizable model for understanding destructive intergroup behaviors in a variety of real-world intergroup contexts.

Introduction

On January 6^th, 2021, thousands of Americans gathered in Washington DC for the “Save America” rally. By and large, the attendees believed that the 2020 US Presidential election had been stolen from Donald Trump and were assembled to voice their dissent with Congress' certification of Joe Biden's victory. Following a speech from Donald Trump, roughly two thousand of these attendees moved to the United States' Capitol building, forced their way past police and Capitol security, and entered the building. As their actions were broadcasted nationwide, millions of Americans across the country watched protestors vandalizing the building, assaulting police officers and members of the media, and threatening US lawmakers with violence. The response, it seems, was widespread condemnation. Ultimately, the dignity of an important American democratic institution had been undermined, several people had lost their lives, and over $2.7 million in damages had been done to the Capitol building (District of Columbia | 18 months since the Jan. 6 attack on the Capitol, 2022). Yet, despite extensive media coverage and public scrutiny of the destructive actions taken on January 6^th, survey data indicated that 1 year later 4%−5% of Americans believed these actions had been justified (Hounshell and Askarinam, 2022).

Support for the Capitol attack provides a particularly noteworthy example of what appears to be a broader trend in American politics. Polling data indicates that levels of endorsement of political violence have been increasing across the political spectrum (Diamond et al., 2020; Kalmoe and Mason, 2022; Lerner, 2023). This growing endorsement of political violence enacted by other members of one's ingroup (political party, in this case) points to an important gap in the psychological literature. While research has identified many psychosocial factors that predict direct participation in political violence, radicalism, and extremism (e.g. della Porta, 1995; McCauley and Moskalenko, 2008; Hogg et al., 2013; Kruglanski et al., 2014), decidedly less attention has been paid to those who do not participate in political violence but nevertheless endorse it (Moskalenko and McCauley, 2009; Becker, 2021).

Yet, understanding the processes that lead people to endorse political violence even while they are unwilling or unlikely to participate in it themselves is equally important. Ingroup support for intergroup violence is likely to increase its occurrence (Jetten et al., 1996; de la Roche, 2001; Crandall et al., 2002; Hayes and McAllister, 2005; Waldmann, 2005; Ritchey and Ruback, 2018). Additionally, the psychological processes involved in endorsing vs. engaging in political violence may not always be the same. For instance, those who engage in violent extremism have been shown to be uniquely concerned with group acceptance (Goldman and Hogg, 2016) or to be on a “quest for personal significance” (Kruglanski et al., 2014). Whether concerns like these motivate the endorsement of political violence by others is not clear, and it may be that endorsing the actions of others involves its own unique set of psychological processes.

We propose that in many cases, political violence can be productively understood as an example of a particular type of collective action—what we term destructive intergroup behavior. While collective action involves any action taken by someone acting as a representative of their group with the intention of promoting the group's interests (Wright et al., 1990), we define destructive intergroup behavior as collective action taken with the specific proximal intent of harming an outgroup or its members (Wright et al., 2018). Thus, when someone endorses political violence by members of their political ingroup, they often do so with the clear recognition that the primary intention of this action is to harm the political outgroup or its members. In these cases, they are endorsing destructive intergroup behavior.

We elaborate on this concept of destructive intergroup behavior and its relationship to political violence, and propose three key psychological processes through which people come to endorse destructive intergroup behavior: strength of identification with the relevant ingroup (i.e., ingroup identification), strength of identification with a relevant larger more inclusive social category (i.e., superordinate category identification), and a process known as ingroup projection (i.e., seeing the characteristics and standards of the ingroup as shared by the larger more inclusive category). Using data collected during two important US elections, we demonstrate the utility of this model for explaining support for political violence in real-world political contexts.

Defining destructive intergroup behavior

Like other forms of collective action, destructive intergroup behavior (DIB) involves someone acting as a representative of their ingroup with the primary intent of promoting ingroup interests. However, what distinguishes DIB from other forms of collective action is that those engaged in DIB are aware that action will cause direct harm to a relevant outgroup and/or its members and choose the behavior for this proximal purpose. Thus, as a form of collective action DIB is distinguished from acts of interpersonal harm-doing or harm committed purely for personal gain because the actor is self-categorizing as a group member, the targets are chosen because they are outgroup members, and the harmdoing is believed to promote ingroup interests. DIB is also distinguished from collective actions that cause harm unintentionally or by accident.

While outgroup harm is always the proximal purpose of DIB, people can seek to harm outgroup members for a variety of additional more distal and strategic reasons. Even when DIB may be motivated primarily by a desire to see another group suffer, there may be associated symbolic and psychological benefits to the ingroup (e.g., retributive justice, vengeance), such as when anti-fascists used the @YesYoureRacist Twitter account to expose the identities of Americans who attended the 2017 “Unite the Right” rally in Charlottesville (Judkis, 2021). In these cases, DIB also serves the goal of rebalancing the scales of justice or reifying societally-shared norms (Wenzel and Thielmann, 2006). However, it is also likely that DIB is often used as a strategy for achieving other more concrete distal group goals. For instance, qualitative analyses of court documents reveals that many of the Trump supporters who engaged in violent and destructive actions on January 6^th were motivated by a desire to reinstate Donald Trump as President of the United States (Donovan et al., 2022). Likewise, many of the bombings committed by far-left activists in the US during the 1970s were intended not only to cause harm but ultimately to affect political decisions (Parker and Eisler, 2023). Irrespective of the long-term strategic goals, whether harm-doing on behalf of one's group should be understood as DIB depends on the role of harm as a motivator of the action.

Using this definition, a wide range of collective behaviors qualify as DIB. Yet, what they all share is that they are intended to cause harm to an outgroup. Whereas physical violence can easily be identified as DIB, there are other less obvious forms that seek to cause psychological harm, including provoking fear, tarnishing the outgroup's image, and destroying outgroup symbols, or that seek to cause significant financial harm, such as damaging property or interfering with a business' operations. It is also useful to distinguish DIB from the more commonly used concept of non-normative collective action (e.g., Wright et al., 1990; Becker and Tausch, 2016; Jost et al., 2017; Sweetman et al., 2019; Selvanathan and Leidner, 2020). While normative actions are those that conform to established societal norms, non-normative collective actions violate these norms (see Wright, 2009). In contrast, the distinction between DIB and non-DIB collective actions hinges not on societal norms, but on the actor's intention. An action is considered DIB when it is intended to cause harm, regardless of whether the action is consistent or inconsistent with the norms of the broader society. Thus, DIB provides a distinction that crosscuts the normative/non-normative distinction: some acts of DIB may be considered normative, such as launching political smear campaigns and political attack ads, and some non-normative actions would not be considered DIB, such as engaging in a hunger strike or protesting naked.

DIB and political violence

A widely used definition of political violence is provided by della Porta (1995), who defines political violence as “those repertoires of collective action that involve great physical force and cause damage to an adversary in order to impose political aims” (p. 2). More recent definitions have expanded this to include non-physical forms of harm committed by a broader range of collective movements. For instance, Bosi and Malthaner (2015) define political violence as a “heterogeneous repertoire of actions oriented at inflicting physical, psychological, and symbolic damage to individuals and/or property with the intention of influencing various audiences for affecting or resisting political, social, and/or cultural change” (p. 439). Thus, political violence can be broadly conceptualized as an act of harm—be it physical, psychological, or symbolic—that is used to forcibly produce (or prevent) social change.

Using this conceptualization, a wide range of behaviors that would be considered political violence are also acts of DIB; collective action that attempts to achieve political goals through the use physical, psychological, or symbolic harm to a political outgroup would also be DIB. However, there are important differences between political violence and DIB as well. For instance, while political violence can occur when the harm was accidental (see della Porta, 1995), DIB is defined by the actors' explicit intent to cause harm. Likewise, while violent attacks by single unaffiliated individuals can constitute political violence, DIB has a clearer intergroup focus; violent actions are considered DIB only if the actor is thinking of themselves and their targets in terms of their collective (group-based) identities. Furthermore, given that DIB can be motivated by a wide range of group-derived goals, some acts of DIB would not be considered political violence insofar as the goal of the harm is unrelated to social change motives (e.g., vengeance, punishment).

Thus, while there is certainly meaningful overlap between political violence and DIB, not all political violence is DIB, nor is all DIB political violence. The current research examines the psychological processes through which group members come to support DIB. Here we examine this question within the context of American politics, a context in which support for violence against political outgroups is growing among both Democrats and Republicans (Diamond et al., 2020; Kalmoe and Mason, 2022; Lerner, 2023) and in which political violence is indeed often understood and supported as DIB. However, our results are intended to provide insight into why group members support DIB specifically and thus may not generalize to all types of political violence.

Ingroup identification and DIB endorsement

Understanding political violence as DIB—and ultimately as collective action—requires an understanding of the relevant social identities at play. Insights from the Social Identity Approach (see Tajfel and Turner, 1979; Reicher et al., 2010) have inspired research showing that the degree to which an individual identifies with an ingroup is a strong predictor of their reactions to the ingroup's mistreatment (Smith et al., 1994; Simon and Klandermans, 2001; Stephan et al., 2002; Merrilees et al., 2013). Generally speaking, stronger ingroup identification is both a direct (Thomas et al., 2009) and indirect (Van Zomeren et al., 2008) precursor to collective action intentions (Wright and Tropp, 2002) and increases broadband support for actions intended to alleviate ingroup suffering. Thus, strong ingroup identification should act as an important psychological antecedent to support for DIB when harming an outgroup is seen to promote group interests, protects the ingroup from that outgroup, or rights a wrong against the ingroup. Indeed, research has revealed a connection between strong ingroup identification and engaging in intergroup harmdoing (Sidanius et al., 2004; Hogg and Adelman, 2013; Merrilees et al., 2013, 2014). Furthermore, compared to weak identifiers, strong identifiers are more likely to recognize and personally suffer from experiences of prejudice and discrimination (Operario and Fiske, 2001; Major et al., 2003; McCoy and Major, 2003; Sellers and Shelton, 2003; Eliezer et al., 2010), which may lead strong identifiers to be more inclined to endorse harmful action directed at the perpetrators.

Identification with the superordinate category and DIB endorsement

While strong identification with the ingroup seems critical for support for DIB, other social identities may also play a role (see Huynh et al., 2014), in particular the larger more inclusive superordinate category. A superordinate category encompasses both the ingroup and the relevant outgroup (Tajfel and Turner, 1979) and defines the values, standards, and normative characteristics for all subgroups contained within (Turner et al., 1987). The strength of one's identification with this larger group may also have implications for DIB endorsement. However, this relationship may be more complex than the more straightforward connection between ingroup identification and support for DIB. There are good reasons to predict that strong identification with a superordinate category should have a negative relationship with support for harming the outgroup—that is, strong identification with the larger social category that includes a relevant outgroup should reduce interest in harming that outgroup. However, there are also theoretical reasons to believe that superordinate category identification can produce the opposite effect, such that stronger superordinate group identification should result in stronger support for DIB.

On the one hand, focusing on a larger superordinate category can convert those who were previously outgroup members into ingroup members as part of a larger shared “common ingroup.” When this happens, benefits previously reserved for ingroup members are extended to those who were previously outgroup members (see Gaertner et al., 1993). For example, identification with the superordinate category has been shown to decrease ingroup biases and outgroup prejudice (Gaertner et al., 1989, 1993), and to increase empathy (Dovidio et al., 2004) and prosocial behavior (Dovidio et al., 1997; Nier et al., 2001) toward the outgroup. Stronger superordinate category identification can foster more positive attitudes toward the outgroup and, thus, should reduce support for DIB toward outgroup members (Simon and Ruhs, 2008; Dovidio et al., 2009; Tausch et al., 2009).

On the other hand, there are also reasons to predict that strong identification with a superordinate category can lead to harsher evaluation and treatment of members of other subgroups within the superordinate category. This prediction is based on Self-Categorization Theory (Turner et al., 1987) and Mummendey and Wenzel's (1999) Ingroup Projection Model. Because the superordinate category defines the standards for all subgroups, these standards serve as a comparative framework for determining the worth of each subgroup. Subgroups that embody these superordinate group standards are evaluated positively, while subgroups that deviate from them are evaluated negatively and ascribed lower status within the superordinate category. Stronger identification with the superordinate category can increase this tendency to stratify subgroups.

From this perspective, support for DIB might be motivated by processes similar to those that underpin what Marques and Paez (1994)'s have called the “black sheep effect,” which describes how, at times, ingroup members who commit an offense are punished more severely than outgroup members who commit the same offense (van Prooijen and Lam, 2007; Pinto et al., 2010). Importantly, Wenzel and Thielmann (2006) demonstrated that this is more pronounced for those who identify strongly with the relevant superordinate category: compared to low identified Australians, strong identifiers preferred stronger punishments for Australians who committed fraud. Self-categorization theory allows us to assume that a similar dynamic will apply at the intergroup level. Thus, insofar as stronger superordinate category identification leads members of one subgroup to hold other subgroups more accountable to a set of shared standards, this stronger identification should predict increased support for DIB against subgroups whose members are seen to have violated these standards.

Ingroup projection and DIB endorsement

If superordinate category standards are used to determine the evaluation and treatment of subgroups and therefore have the potential to promote cross-group harmdoing rather than cross-group cooperation and harmony, a key consideration is how members of a subgroup determine the superordinate category standards. According to Mummendey and Wenzel's (1999) Ingroup Projection Model, each subgroup seeks to project their own group-specific standards onto the superordinate category. Thus, each group is likely to see the superordinate category's standards as more similar to their own subgroup's standards (Wenzel et al., 2003; Waldzus et al., 2004) and one subgroup's understanding of superordinate category standards need not be the same as another's. As a result, an outgroup can be seen to be deviant or deficient in terms of the standards of the larger social category because those standards actually reflect ingroup standards that have been projected onto the superordinate category. Nonetheless, this outgroup will come to be seen as deserving of devaluation and discrimination for failing to meet what are understood to be shared standards (Waldzus and Mummendey, 2004; Wenzel et al., 2007).

Importantly, identification with one's local subgroup and identification with the larger superordinate category should each uniquely predict the extent of ingroup projection (Wenzel et al., 2007). Strong identification with the local subgroup motivates a desire to see the subgroups' standards reflected more broadly in the world and, thus, greater ingroup projection (Wenzel et al., 2003). Likewise, individuals who are highly identified with the superordinate category are particularly motivated to see this larger group reflect and adopt the standards of their valued subgroups.

Furthermore, when group members are engaged in ingroup projection, they are particularly attentive of superordinate category standards and more likely to negatively evaluate and punish those who they believe deviate from these standards (Wenzel et al., 2007). Hence, strong identification with the local subgroup and the superordinate category will each increase the strength of ingroup projection, which in turn increases the likelihood that other subgroups will be held to one's own ingroup standards. Therefore, under conditions of high ingroup projection, deviant outgroup characteristics and actions become doubly problematic: not only do they deviate from a standard important to one's local ingroup, they also violate a standard that is seen to apply to the entire superordinate category. Thus, members of this deviant outgroup should be seen as particularly deserving targets of DIB. Indeed, under conditions of high ingroup projection, punishing those who violate the ingroup's standards may even be perceived to be a righteous act taken to protect the “true” values of a given superordinate category. Thus, this is an important motivation for the legitimization and support of DIB. For instance, ingroup projection has been found to be linked not only to less positive attitudes toward outgroups, but also to greater perceived legitimacy of the outgroup's lower status (Weber et al., 2002) and to support for policies limiting outgroups' rights and opportunities (Huynh et al., 2015). Likewise, ingroup projection provides a psychological mechanism through which strong identification with one's local ingroup and with the superordinate category will combine to increase support for DIB.

Modeling DIB endorsement

This theorizing is summarized by the following three hypotheses:

1. Ingroup identification will have a positive total effect on DIB endorsement. Part of this effect will be a positive direct effect (Hypothesis 1a). Another part of this effect will be a positive indirect effect that is mediated by ingroup projection (Hypothesis 1b).

However, the impact of superordinate group identification on DIB endorsement will be more complex, creating what has been called a “suppression effect” (see Tzelgov and Henik, 1991).

2. Superordinate category identification will have a negative direct effect on DIB endorsement, due to the benefits of sharing a common ingroup identity with the outgroup.

3. However, superordinate category identification will also have a positive indirect effect on DIB endorsement that is mediated by ingroup projection.

Understanding American political violence as DIB

These hypotheses and the psychological processes described therein provide a theoretical account of DIB endorsement that can be applied across a wide range of intergroup contexts and forms of DIB, including many kinds of political violence. Indeed, there is good evidence that attempts to explain support for political violence in the United States benefit from considering the relevant social identities at play. For instance, Wagoner et al. (2021) recently found that stronger identification as a Trump supporter predicted beliefs that the 2020 US Presidential election was illegitimate and support for political violence. Similar results for other politically-relevant social identities have been reported (Wohl et al., 2014; Lobato et al., 2020; Armaly et al., 2022; Kacholia and Neuner, 2022; Kalmoe and Mason, 2022). Thus, as theorized in our model of DIB, strong identification with the relevant political ingroup seems a consistent prerequisite for supporting political violence.

Likewise, our prediction that strong identification with a relevant superordinate identity will have both a negative direct and a positive indirect effect on support for political violence is consistent with the existing research examining political violence in the US, which provides little consensus about the role of identification with the category “American” (the relevant superordinate category). Armaly et al. (2022) demonstrated that Christian Nationalism—conceptualized as an overlap between Christian and American identities—predicted support for the January 6^th Capitol attack (although this relationship was conditioned by additional variables). Similarly, others have suggested that a strong sense of patriotism and desire to protect democracy were key predictors of support and participation (Donovan et al., 2022; Van Swol et al., 2022). However, Kacholia and Neuner (2022) reported an inconsistent relationship between American identity and support for political violence. Moreover, as previously discussed, a large body of research examining the impacts of a common ingroup identity (Gaertner et al., 1993) predicts that American identity should have a negative relationship with support for political violence. The “suppression effect” described in hypotheses 2 and 3 of the model can reconcile these disparate findings.

Moreover, on its face, ingroup projection seems well-suited for understanding political violence that occurs in contexts in which there is regular debate and disagreement about the norms, standards, and values of a shared superordinate identity. In addition, recent research investigating political violence in the US can be recast to provide indirect support for the hypothesized role of ingroup projection as a relevant mediator. For instance, Mooijman et al. (2018) provide experimental evidence that higher “moral convergence”—defined as “the belief that others share one's moral attitudes”—was predictive of participants' support for hypothetical acts of political violence toward the far-right protestors who participated in the 2017 Unite the Right rally. Likewise, Armaly et al.'s (2022) work examining Christian Nationalism showed that the perceived overlap between Christian and American identities was partially responsible for their support for the January 6^th Capitol attack.

We conducted two studies to test our general model of DIB endorsement in the context of support for political violence during two important US elections. Thus, these studies offer a test of two novel additions to the literature on predictors of American political violence—the potential role of ingroup projection and the complex suppression effect of identification with the superordinate category. Study 1 includes data collected during the run-up to the 2016 US Presidential election. Study 2 offers a preregistered replication using data collected during the run-up to the 2022 US Senate midterm elections.

Study 1

While the 2016 United States Presidential election period was notable in many regards, most relevant to the current research were the acts of political violence taken by Democrats and Republicans in the run-up and aftermath of the election. For instance, it was widely reported that on multiple occasions Trump supporters used force to remove anti-Trump protestors from rallies, in some cases causing injury (Jacobs, 2016; Nast, 2016; Tiefenthäler, 2016). Likewise, in the aftermath of Donald Trump's victory, Democrat protestors engaged in a variety of destructive actions to “resist the Trump agenda” (Berman and Lowery, 2013). In Portland, anti-Trump protestors smashed windows, lit fires, and threw objects at police, leading city authorities to declare the protests a riot (Domonoske, 2016).

These acts also received tacit support from a broader group of politically active Americans. Donald Trump won the Presidential election, and the Portland riot was part of the much broader #NotMyPresident anti-Trump movement which organized protests across the United States. In short, this moment in US history represented a real-world political context in which DIB was actually occurring, and in which support for DIB would be likely among both Democrats and Republicans.

This provided an opportunity to develop a deeper understanding of the psychological processes that underlie support for DIB, a theoretical focus decidedly different from prior work focused primarily on participation in destructive and non-destructive collective action. Likewise, clearly defined subgroups (Democrats vs. Republicans) and active intergroup debate over the standards of the broader superordinate category (Americans) provided an ideal real-world context for testing the hypothesized role of ingroup projection. Indeed, as support for political violence becomes increasingly common across the political spectrum, ingroup projection provides a (non-partisan) psychological process through which Democrats and Republicans alike may come to support a wide range of political violence.

Study 1 includes data collected in the weeks preceding the 2016 United States Presidential election. Based on the three hypotheses described in our model of DIB endorsement, we expected that Political Party Identification (as either a Democrat or Republican) would have both a positive direct effect (Hypothesis 1a) and a positive indirect effect via Ingroup Projection (Hypothesis 1b) on endorsement of DIB (in this case specific acts of political violence). We also expected a suppression effect of American Identification. Specifically, while American Identification should have a direct negative effect on endorsement of DIB (Hypothesis 2), we also predicted that it would also have an indirect positive effect on endorsement mediated by Ingroup Projection (Hypothesis 3). Finally, Study 1 also tested the generality of this model for a wider range of collective action by running the same analyses to test support for non-destructive forms of political collective action.

Method

Participants

Participants were recruited using Qualtrics' Online Research Panel. All participants lived in the United States and the sample included an approximately equal number of self-identified Democrats (N = 141) and Republicans (N = 156). The final sample included 297 participants after 32 participants were removed for failing an attention check. Participants' mean age was 43.5 years old (SD = 16.2); 216 identified as female, 76 as male, and 5 did not specify their gender; 240 identified as White, 19 as Black, 16 as Latina/o, 6 as Asian, 1 as Native American, and 15 as mixed-ethnicity.

Procedure

Participants began by indicating their Political Party affiliation, which ensured the language used in all materials and measures aligned with their self-reported political party. Next, participants completed measures of American Identification, Political Party Identification, and Ingroup Projection. They then read a news report ostensibly written by an online news outlet that described a series of incidents that occurred in the run up to the 2016 US Presidential election. First, participants read how the opposing political party (e.g., for Democrats, this was Republicans) had worked with a non-profit political organization called iDeclare to violate election standards by funneling “get-out-the-vote” funds directly into the campaign finances of their respective party's Presidential candidate (Trump or Clinton). Specifically, participants read that current election standards mandated these get-out-the-vote funds could only be used to mobilize voters in non-partisan voter turnout campaigns, and that the opposing political party's actions had clearly violated these standards.¹

The news report then described the fallout from this incident, focusing on two key points. First, it was made clear that no legal action had been taken against the opposing political party, the non-profit organization iDeclare, or the Clinton/Trump campaign for the misuse of funds. Second, the report described a series of retaliatory acts that were taken in response by members of the participant's own political party. Specifically, participants were told that members of their party had broken into the campaign offices of the opposing political party, destroyed property and valuable equipment, and injured a campaign staffer. Participants also read that these retaliatory actions were significant enough that they could impact the opposing political party's ability to win the 2016 US Presidential election. All information in the news report was fictitious and created by the research team.

After reading the news report, participants completed two measures of DIB Endorsement and provided demographic information.

Measures

Political party affiliation

Participants indicated which of six options best described their political affiliation. Participants were categorized as Republican if they indicated their political affiliation to be either “Republican” or “Trump Supporter.” Participants were categorized as Democrat if they indicated their political affiliation to be either “Democrat” or “Clinton Supporter.” Participants who indicated their political affiliation to be “Independent” or “Undecided” did not participate in the remainder of the study.

American identification

Participants completed Cameron's (2004) 13-item Ingroup Identification scale adapted for the group “Americans” (e.g., “I often think about the fact that I am American”; “In general I am glad to be American”; “I feel strong ties to other Americans”) using 7-point Likert scales (endpoints “strongly disagree” and “strongly agree”). Negatively worded items were reverse-coded. Additionally, an adapted version of Tropp and Wright's (2001) single-item Inclusion of the Ingroup in the Self scale² was included, producing a 14-item scale (α = 0.88). Higher scores indicate stronger identification with the American superordinate category.

Political party identification

Participants completed Cameron's (2004) 13-item Ingroup Identification scale adapted for the group “Democrats” or “Republicans” based on their self-reported political party affiliation (e.g., “I often think about the fact that I am a Democrat/Republican”; “In general I am glad to be a Democrat/Republican”; and “I feel strong ties to other Democrats/Republicans”) using 7-point Likert scales (endpoints “strongly disagree” and “strongly agree”). Negatively-worded items were reverse-coded. Additionally, an adapted version of Tropp and Wright's (2001) single-item Inclusion of the Ingroup in the Self scale was included, producing a 14-item scale (α = 0.90). Higher scores indicate stronger identification with one's political party.

Ingroup projection

Participants completed a 5-item measure designed to measure the degree to which participants believed American values, beliefs, and standards were the same as the values, beliefs and standards of their particular political party (e.g., “Democrats/Republicans and Americans hold a lot of the same beliefs”; “The moral standards of Democrats/Republicans and Americans are a lot alike”; and “Democrats/Republicans and Americans share many similar values”) using 7-point Likert scales (endpoints “strongly disagree” and “strongly agree”). Additionally, Tropp and Wright's (2001) single-item Inclusion of the Ingroup into the Self scale was adapted to reflect the degree to which participants saw overlap between their particular political party and America and was included as a sixth item (α = 0.89). Higher scores indicate higher levels of ingroup projection.

Situation-specific DIB endorsement

Participants were presented with the prompt “Because the authorities have done nothing to punish the Republicans/Democrats at iDeclare who deceived Democrat/Republican donors and funneled donor funds to their own Presidential candidate….” They then completed five items describing their level of support for the retaliatory actions of the members of their own party (e.g., “…the Democrats/Republicans who vandalized Republican/Democrat property did the right thing”; “…the violent responses of Democrat/Republican supporters were harsh but fair”) using 7-point Likert scales (endpoints “strongly disagree” and “strongly agree”; α = 0.94). Higher scores indicate higher levels of endorsement for the specific acts of DIB described in the news report.

General DIB endorsement

Participants completed six items designed to measure their general support for DIB against the rival political party (e.g., “Although I realize it is illegal and I don't usually support breaking the law, I think it is a good idea when Democrat/Republican computer hackers launch online attacks that disrupt Republican/Democrat websites;” “Although I realize it is illegal and I don't usually support breaking the law, I think it is a good idea when Democrats/Republicans use violent protest to disrupt Republican/Democrat rallies and conventions”) using a 7-point Likert scale (endpoints “strong disagree” and “strongly agree;” α = 0.95). Higher scores indicate higher levels of endorsement for instances of DIB that could be taken by members of the participants' own political party.

Non-destructive collective action endorsement

Participants completed five items designed to measure their general support for non-destructive forms of political collective action (e.g., “I think it is a good idea when Democrats/Republicans organize rallies to raise awareness of their party's message;” “I think it is a good idea when Democrats/Republicans make cash donations to their party”) using 7-point Likert scales (endpoints “strongly disagree” and “strongly agree”; α = 0.76). Higher scores indicate higher levels of endorsement for non-destructive political collective action taken by members of the participants' own political party.

Results

Summary statistics for all variables are provided in Table 1 and bivariate correlations in Table 2. Overall, a sizeable minority of participants endorsed DIB. Approximately 17.2% of participants scored above the midpoint on the Situation-specific DIB Endorsement measure (5.7% of participants scored ≥ 6/7). Support for general acts of DIB was lower, with approximately 8.4% of participants scoring above the midpoint on the General DIB Endorsement measure (4.7% of participants scored ≥ 6/7). Democrats and Republicans differed slightly in their levels of identification but showed no differences in their levels of Ingroup Projection nor their levels of Endorsement for both DIB and Non-destructive Collective Action. Democrats and Republicans also showed an almost identical pattern of correlations.³ Detailed descriptive statistics for individual items are included in the Supplementary material.

Table 1

Table 1. Study 1 summary statistics of all variables.

Table 2

Table 2. Study 1 bivariate correlation matrix for all variables.

IBM AMOS (Version 28) was used to test all three hypotheses in a single path model for the three measures of the dependent variable: Situation-specific DIB Endorsement, General DIB Endorsement, and Non-destructive Collective Action Endorsement. Political Party Identification and American Identification were entered as the independent variables and Ingroup Projection as the only mediator. Because previous work has demonstrated that the effects of ingroup and superordinate identities on Ingroup Projection can be both additive and non-additive (Wenzel et al., 2003, 2007), we also tested whether the interaction between these two identities would explain additional variance. To avoid issues of multicollinearity, American Identification and Political Party Identification were mean-centered. Moreover, to explore any unpredicted differences between Democrats and Republicans we ran multiple group comparisons. In all models, the two dummy-coded condition variables were entered as additional covariates. Covariations were allowed between the identification variables, between the two dummy-coded covariates, and between the three dependent variables, but not across these three categories of variables. Indirect effects were estimated using 10,000 bootstrap samples and 95% percentile-based confidence intervals.

Model comparisons revealed that neither allowing for different effects between Democrats and Republicans nor including the interaction between the two identification variables increased the model fit. More precisely, we compared an unconstrained model in which all effects were allowed to differ between Republicans and Democrats with models in which we restricted subsequently first the regression weights, then the covariances, and then the residuals to be equal between groups. Finally, we additionally restricted all relations (covariances and regression weights) of the interaction term to be zero. None of these steps produced any significant change in model fit (ps > 0.05 for all for chi-square difference tests). We therefore interpret the most parsimonious model from which the interaction term was removed, and effects are assumed to be equal for Republicans and Democrats. This model had an excellent fit (chi-square = 47.1, df = 40, p = 0.21; GFI = 0.96; RMSEA = 0.02). Detailed information on model fit for all models in the multiple group comparison (without the interaction term) can be found in the Supplementary material.

Hypotheses testing

As shown in Table 3 and Figure 1, both Political Party Identification and American Identification significantly predicted Ingroup Projection, which in turn had significant effects on all three measures of the dependent variable. As predicted by Hypotheses 1b and 3, these combined effects resulted in significant positive indirect effects on DIB Endorsement but also Non-violent Collective Action Endorsement. Consistent with Hypothesis 1a, Political Party Identification had a positive direct effect on DIB Endorsement, although this effect was only marginal in the case of Situation-Specific DIB. Thus, it seems that the correlation between Political Party Identification and Situation-specific DIB Endorsement was completely explained by the mediating process of ingroup projection. Supporting Hypothesis 2, American Identification had a negative direct effect on both measures of DIB Endorsement.

Table 3

Table 3. Study 1 direct, indirect, and total effects of the mediation model.

Figure 1

Figure 1. Standardized direct (total) effects on endorsement of situation-specific DIB/General DIB/Non-violent collective action in study 1. Two dummy-coded variables were included to control for the effects of an ineffective manipulation unrelated to the current analysis (also see Note of Table 3). *p < 0.05, **p < 0.01, ***p < 0.001.

Discussion

Overall, these results provided initial support for the proposed model of DIB endorsement. As predicted, identification with the political ingroup (Democrats/Republicans) had a positive total effect on both measures of DIB endorsement. Stronger identification with the political ingroup predicted greater support for DIB, but importantly, this effect was in large part indirect and explained by ingroup identification's positive effect on ingroup projection. In fact, the direct effect of level of identification with one's political ingroup on the support for specific DIB described in the news report did not reach traditional levels of significance. However, the indirect effect mediated by ingroup projection was significant for both the specific acts of DIB described in the news report as well as the more general acts of politically-motivated DIB. Thus, strong identification with one's political ingroup was associated with higher levels of ingroup projection, which in turn was associated with higher levels of endorsement of political violence across two different measures.

Taken together, these results are consistent with our prediction that stronger identification with either Democrats or Republicans would be associated with higher levels of support for political violence and that this relationship exists is in part because stronger identification with one's political ingroup leads people to project the values and beliefs of their political ingroup onto the larger social category of Americans. This perception that prototypical Americans are more like members of one's own political ingroup appears to provide the justification needed to support political violence when the outgroup violates the rules of that larger social category.

This study also provides support for the predicted suppression effect of identification with the superordinate category. Consistent with the well-documented prosocial outcomes of identification with a common ingroup, the current findings show that stronger identification with Americans predicted lower endorsement of DIB against the political outgroup. However, as predicted by the Ingroup Projection Model, stronger identification with Americans predicted higher levels of ingroup projection, which in turn predicted higher levels of support for political violence by other members of the political ingroup. Thus, identification with the superordinate category can, on the one hand, curb support for politically motivated acts of harm against the political outgroup, but on the other hand, can also promote support for these same acts of harm indirectly by increasing ingroup projection. Yet another source of suppression is the correlation we observed between American Identification and Political Party Identification, the latter of which was also positively related to DIB Endorsement. Therefore, although the regression model showed a significant negative total effect of American Identification on both measures of DIB Endorsement after controlling for Political Party Identification, the overall impact of this combination of both a negative direct effect and positive indirect effects on levels of DIB endorsement results in a muted (suppressed) and non-significant correlation of identification with the larger social category and DIB (Table 2).

We also tested whether this model including two levels of identification and the mediator of ingroup projection would predict more conventional non-destructive forms of collective action. Overall, the model explained a similar amount of variance in support for both destructive and non-destructive forms of collective action. Likewise, ingroup projection did mediate the indirect effects of both political ingroup and American identity on endorsement of non-destructive collective action. However, the indirect effects were smaller than those found for DIB endorsement. This may indicate that while ingroup projection is a psychological antecedent of support for non-destructive collective action, it plays a particularly important role in explaining support for DIB specifically.

In addition, the direct negative effect of American Identification did not emerge in the model predicting of Non-destructive Collective Action Endorsement, and the positive direct effect of Political Party Identification was notably larger when predicting Non-destructive Collective Action. While tentative, these results might suggest that ingroup and superordinate category identities differentially predict support for collective action depending on whether those actions are destructive vs. non-destructive. While not the primary focus of the current work, these differences could have important implications for political messaging and therefore deserve further investigation.

Study 2

Polling data suggests that in the time since the 2016 US Presidential election, support for political violence has increased across the political spectrum (Diamond et al., 2020; Kalmoe and Mason, 2022; Lerner, 2023). Likewise, several noteworthy acts of political violence have occurred since 2016, including those connected to the Charlottesville Unite the Right Rally in 2017 and the January 6^th Capitol Attack in 2021. Reports of threats against members of the US Congress increased 10-fold between 2016 and 2021 (Bergengruen, 2022). Moreover, while the vast majority of the Black Lives Matter protests that followed the death of George Floyd in 2020 were peaceful (Craig, 2020; Kishi and Jones, 2020), the riots that occurred in several American cities during this period caused an estimated $1 billion in damages (Deese, 2020).

Recognizing the evolving landscape of political violence in the US, we aimed to replicate the results of Study 1. Specifically, in Study 2 we collected data in the weeks preceding the 2022 US Senate midterm elections. Notably, we reasoned that while support for DIB might be lower in non-competitive Senate races, it might also be strongest in races that were expected to be competitive. Thus, we collected data only in states where the 2022 Senate races were expected to be close.⁴ With clearly defined political groups and vigorous debate over what were the broader American societal standards, this election once again provided an ideal real-world context for testing the hypothesized role of ingroup projection in facilitating support for DIB.

The three hypotheses tested in Study 2 were identical to those tested in Study 1. Thus, we expected that Political Party Identification (Democrat or Republican) would have both a positive direct effect (Hypothesis 1a) and a positive indirect effect mediated by Ingroup Projection (Hypothesis 1b) on levels of DIB Endorsement. We also expected a suppression effect for American Identification, such that it would exert a negative direct (Hypothesis 2) and a positive indirect effect mediated by Ingroup Projection (Hypothesis 3) on DIB endorsement. All hypotheses, methods, and measures used in Study 2 were preregistered on the Open Science Framework (see https://osf.io/7h2xm).

Method

Participants

Participants were recruited using CloudResearch Prime Panels. All participants lived in one of ten US states (see text footnote ⁴). Pre-screening was used to recruit approximately equal numbers of Democrats (N = 317) and Republicans (N = 325). Participants who failed attention checks were removed by Prime Panels,⁵ leaving a final sample of 642 participants with a mean age of 55.1 years old (SD = 17.0); 392 identified as female, 232 as male, 3 as non-binary, and 15 did not report their gender; 515 participants identified as White, 57 as Black/Caribbean, 11 as Asian, 9 as Latina/o, 3 as Native American, 35 as mixed-ethnicity, and 12 did not report their ethnicity.

Procedure

Study 2 was a preregistered replication of Study 1, and therefore the procedures were very similar. Prime Panels sorted participants into the correct version of the survey (Democrat or Republican) based on their reported political party affiliation. Participants first completed measures of American Identification, Political Party Identification, and Ingroup Projection. They then read a news report ostensibly written by an online news outlet that described an incident that occurred in the run up to the 2022 State Senate race in their own home state. Specifically, participants read that the opposing political party's campaign had violated election standards by funneling “get-out-the-vote” funds directly into the campaign finances of their own State Senate candidates.

The news report then described the fallout, focusing on two key points. First, it was made clear that no legal action had been taken against the opposing political party's campaign for the misuse of these funds. Second, it described a series of retaliatory acts that were taken in response by participants' own political party. Specifically, participants were told that members of their party had broken into the campaign offices of the opposing political party, destroyed property and valuable equipment, and injured a campaign staffer. Participants also read that these retaliatory actions were significant enough that they could impact the opposing political party's ability to win the 2022 State Senate election. The details of the news report (political parties, Senate candidate, location, etc.) were matched to reflect each participant's location and political affiliation, and all information in the news report was fictitious and created by the research team.

After reading this news report, participants completed two measures of DIB Endorsement and provided demographic information.

Measures

All variables included in the preregistered analysis (i.e. American Identification, Political Party Identification, Ingroup Projection, Situation-specific DIB Endorsement, and General DIB Endorsement) were measured using scales very similar or identical to those used in Study 1. All scale reliabilities were above α = 0.90.

Results and discussion

Summary statistics for all variables are provided in Table 4 and bivariate correlations in Table 5. At the request of our reviewers, all hypotheses were tested using structural equation modeling and the analysis used in Study 2 differs from that which was originally preregistered. However, results from the original preregistered analysis were largely consistent with those we report here and can be viewed on the Open Science Framework (see https://osf.io/6fwjm).

Table 4

Table 4. Study 2 summary statistics of all variables.

Table 5

Table 5. Study 2 bivariate correlation matrix for all variables in Study 2.

Overall, a sizeable minority of participants endorsed DIB. Approximately 20.9% of participants scored above the midpoint on the Situation-specific DIB Endorsement measure (6.7% of participants scored ≥6/7). Support for general acts of DIB was lower, with approximately 14.2% of participants scoring above the midpoint on the General DIB Endorsement measure (5.3% of participants scored ≥6/7). Detailed descriptive statistics for individual items are included in the Supplementary material. Interestingly, differing from the results obtained in Study 1, Republicans showed lower levels of DIB Endorsement on both measures. However, like Study 1, the two groups showed a very similar correlation pattern.⁶

IBM AMOS (Version 28) was used to test all three hypotheses in a single path model for the two measures of the dependent variable: Situation-specific and General DIB Endorsement. Political Party Identification and American Identification were entered as the independent variables and Ingroup Projection as the only mediator. Covariances were included between the two identification variables and between the two dependent variables. As in Study 1, preliminary model-comparisons revealed that including non-zero effects of the interaction between the two identification variables did not increase the model fit, so the interaction term was not included in the model.

The model in which all parameters (i.e., regression weights, covariances and residuals) were restricted to be equal between Republicans and Democrats—as was used in Study 1—had no acceptable model fit (chi-square = 75.00, df = 15, p < 0.001; GFI = 0.96; RMSEA = 0.08). Allowing residuals and covariances to differ between Republicans and Democrats significantly improved the model fit (ps < 0.001 for both chi-square difference tests). The resulting model in which only the regression weights (but not covariances or residuals) were constrained to be equal between Republicans and Democrats had acceptable model fit (chi-square = 20.00, df = 8, p = 0.01; GFI = 0.99; RMSEA = 0.05) and was used for our hypotheses testing. Detailed information on model fit for all models in the multiple group comparison (without the interaction term) can be found in the Supplementary material.

Hypotheses testing

As shown in Table 6 and Figure 2, both Political Party Identification and American Identification significantly predicted Ingroup Projection. Ingroup Projection, in turn, had significant effects on both measures of the dependent variable. As predicted by Hypotheses 1b and 3, these combined effects result—as in Study 1—in significant positive indirect effects on DIB Endorsement. Inconsistent with Hypothesis 1a—and different from Study 1—there was no direct effect of Political Party Identification on either measure of DIB Endorsement. However, consistent with Hypothesis 2—and again replicating the results from Study 1—American Identification had a negative direct effect on DIB. Although the total negative effect of American Identification in the regression model was significant because the effect of Political Party Identification was controlled for, the correlations between American Identification and DIB Endorsement were not significant (Table 5), as was the case in Study 1. In sum, these results largely replicated those obtained in Study 1 and—with the exception of Hypothesis 1a—provided additional support for our hypotheses.

Table 6

Table 6. Study 2 direct, indirect, and total effects of the mediation model.

Figure 2

Figure 2. Standardized direct (total) effects on endorsement of situation-specific DIB/General DIB in Study 2. Although non-standardized effects were constrained to be equal in the model, estimates of standardized effects slightly differ between Democrats and Republicans due to different covariances and residuals. ^*p < 0.05, ^**p < 0.01, ^***p < 0.001.

General discussion

Using data gathered during two recent and important American elections, we present substantial evidence supporting our model of DIB endorsement. From this evidence, two key conclusions can be drawn regarding the psychological processes which underlie support for DIB. First, seeing the values and standards of one's ingroup as highly representative of the values and standards of the larger superordinate category—a process known as ingroup projection—plays an important role in generating support for DIB. In the current research, ingroup projection served as the key mediating process through which strong identification with both a political ingroup (Democrats/Republicans) and the larger national category (Americans) combined to produce support for political violence. Second, the real impact of strong identification with the larger superordinate category on DIB endorsement may be largely disguised. While identifying more strongly with the larger, more inclusive national category of Americans reduced support for harming political outgroups, it also simultaneously encouraged support for outgroup harm by strengthening the tendency to engage in ingroup projection. As a result of these competing negative direct and positive indirect effects, the overall correlation between identification with America and support for DIB directed at the political outgroup was minimal.

Both of these key findings add to a growing body of evidence highlighting the importance of political identities in building support for political violence (e.g., Lobato et al., 2020; Wagoner et al., 2021; Armaly et al., 2022). Additionally, and in line with the well-established approach in psychological models of non-destructive collective action (e.g., Van Zomeren et al., 2008; Thomas et al., 2009; Fritsche et al., 2017), our results underscore the benefits of considering political identities alongside their identity-relevant psychological processes when exploring support for political violence.

The current work also makes important and novel contributions to our understanding of destructive intergroup behavior that hold broader implications for political violence as well. Across both studies and all measures of DIB endorsement, stronger identification with both Democrats/Republicans and with Americans related to higher levels of ingroup projection, which in turn related to higher levels of support for political violence. In fact, for Democrats and Republicans alike, the effect of political party identification on DIB endorsement were almost always mediated entirely through ingroup projection. These results point to a generalizable psychological process that can explain support for political violence across the political spectrum and the mediating role of ingroup projection in particular holds significant implications that extend beyond the scope of the current work. For instance, insofar as messages from political leaders provide cues about the values, standards, and normative characteristics of the wider superordinate category, it seems likely that political messages with a strong partisan bias run the risk of promoting ingroup projection and thus inspiring greater support for political violence. Similar concerns regarding political leaders' ability to “activate” links between relevant social identities and support for political violence have been noted elsewhere (Armaly et al., 2022). Likewise, given the well-documented “echo chamber effects” of social media (e.g., Cinelli et al., 2021), it seems that social media usage may increase support for political violence by leading people to believe that their party's political values and standards are widely shared within the relevant superordinate category. Indeed, Mooijman et al. (2018) research examining the effects of moral convergence within social media networks provides indirect evidence for this prediction.

While not the focus of the current work, the relevance of ingroup projection may also have important implications for efforts to reduce support for political violence. Indeed, one corollary of our findings is that support for political violence may be lessened by ensuring that members of a given political party have a realistic understanding of the diversity that exists in the values and standards of the wider superordinate category. Recognizing a rich level of diversity in the superordinate category places “reality constraints” (Waldzus et al., 2004) on levels of ingroup projection, thereby reducing the degree to which each political party can misperceive their ingroup identities as defining the standards of the larger society. This, in turn, should reduce support for political violence.

Our results also demonstrate the nuanced relationship that exists between strong superordinate category identification and support for DIB. Consistent with the previously demonstrated prosocial impacts of a common ingroup identity, stronger identification with Americans predicted lower levels of DIB endorsement. However, strong identification with this common ingroup also came with a cost. By increasing ingroup projection, stronger identification with Americans predicted higher levels of support for DIB indirectly. To our knowledge, this is the first time that this suppression effect has been demonstrated. While it remains to be seen whether this effect generalizes to other superordinate categories in novel social contexts, or to superordinate categories at different levels of abstraction (e.g., individual political parties, humanity), it does provide an avenue for resolving discrepancies in the literature surrounding the relationship between American identity and support for political violence specifically. Therefore, future research should continue to consider the ways in which common ingroup identities can simultaneously promote and prevent support for DIB. Moreover, attempts to reduce support for political violence in the United States specifically may benefit from harnessing the prosocial effects of American identity, so long as efforts are also taken to prevent high levels of ingroup projection.

Political transformation and social change are often punctuated by collective action. Oftentimes, collective action can voice new perspectives, produce compromise between political opponents, and drive the democratic process forward. However, collective action that involves a direct effort to cause harm to an outgroup (i.e., DIB) represents an important escalation of political conflicts. DIB can reify or worsen animosities between political opponents, limit opportunities for political compromise, and ultimately undermine democratic processes and institutions. In extreme cases, DIB can cause serious human suffering, justify and perpetuate a cycle of tit-for-tat extremism, and be used by powerful actors to maintain an unjust status quo. At the same time, it may well be that DIB plays a role in progressing social change as well. Harming the outgroup may be necessary for groups to get the attention of their opponents and the broader society. Causing financial or reputational harm to a more powerful outgroup can begin to level the playing field for groups with less power and resources. Thus, for oppressed groups or those who are engaged in intergroup conflicts with authoritarian groups and leaders, causing direct harm to the machinery or agents of their oppression may be an important step in creating social change toward greater equality.

Thus, investigating when DIB might be seen by the wider membership of a group as appropriate, necessary, and even desirable has clear societal relevance. Our results suggest that groups often endorse DIB to promote ingroup norms, standards, and goals precisely because these norms, standards and goals are believed to be shared by the wider societal category. By considering the interplay between subgroup and superordinate category identities simultaneously, the ingroup projection approach allows us to understand how and why two ideologically opposed groups can nevertheless be motivated to engage in DIB by very similar concerns about protecting shared societal values. This approach also provides a framework that can be applied to understand social change processes more generally as well, insofar as ingroup projection also motivates support for non-destructive forms of collective action. Most importantly, our results should encourage collective action researchers to move beyond a focus on a single relevant social identity and instead consider multiple relevant social identities to better understand the processes that lead group members to support actions for social change.

Data availability statement

The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: Open Science Framework; https://osf.io/6fwjm/.

Ethics statement

The studies involving humans were approved by Simon Fraser University's Research Ethics Board. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their electronic consent to participate in these studies.

Author contributions

MW: Conceptualization, Formal analysis, Funding acquisition, Investigation, Methodology, Writing – original draft, Writing – review & editing. SCW: Conceptualization, Funding acquisition, Investigation, Methodology, Supervision, Writing – review & editing, Writing – original draft. SW: Conceptualization, Funding acquisition, Supervision, Writing – review & editing. GS: Conceptualization, Methodology, Writing – original draft.

Funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This work was supported by the Social Sciences and Humanities Research Council Insight Grant [grant number 31-R640021] as well as two Social Sciences and Humanities Research Council Canadian Graduate Scholarships (Masters and Doctorate) awarded to MW. Collaborations between MW and SW were also made possible by a Mitacs Globalink Research Award, awarded to MW [grant number IT15160].

Acknowledgments

The authors acknowledge the contributions of Priscilla Lok-Chee Shum, who assisted in the preregistration of Study 2. The authors acknowledge Dr. Michael Schmitt for the supervision he provided to MW during this research. The Authors acknowledge that the Simon Fraser University Burnaby campus, where this research was conducted, is located on the traditional unceded territories of the Coast Salish peoples, including the səl̓ilw̓ətaʔɬ (Tsleil-Waututh), kʷikʷəƛ̓əm (Kwikwetlem), Sḵwx̱wú7mesh Úxwumixw (Squamish) and xʷməθkʷəy̓əm (Musqueam) Nations.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/frsps.2024.1347054/full#supplementary-material

Footnotes

1. ^This study also included a manipulation that placed participants into one of three conditions that altered the way the relevant election standards were framed. A series of t-tests revealed that this manipulation was largely ineffective (see Supplementary material). However, condition was entered as two dummy-coded covariates in all analyses to control for any potential effects of the manipulation.

2. ^This scale presents participants with a series of seven increasingly overlapping pairs of circles, one circle is labeled “Self” and the other the relevant social group (in this case, “Americans”). Participants select the pair of circles with the level of overlap that best represents their identification with that group.

3. ^There were two significant differences between the correlation coefficients of Democrat and Republican participants. Republicans showed a slightly stronger correlation between Political Party Identification and Ingroup Projection (z = −1.589, p = 0.049) and between American Identification and Non-destructive Collective Action Endorsement (z = −2.085, p = 0.018).

4. ^Participants were only recruited from Arizona, Colorado, Florida, Georgia, Nevada, New Hampshire, North Carolina, Ohio, Pennsylvania, and Wisconsin.

5. ^Given recent concerns that levels of support for political violence are overestimated and in large part reflect disengagement during the completion of surveys (e.g. Westwood et al., 2022), these attention checks ensured participants were engaged and that levels of DIB endorsement could be measured accurately.

6. ^The only correlation that was significantly different between Democrats and Republicans was the correlation between Political Party Identification and Ingroup Projection (z = −2.842, p = 0.002), which was strong for both groups but significantly stronger for Republicans than Democrats.

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