ALLYSHIP AT YOUR OWN RISK: THE ROLE OF INTERPERSONAL RISK IN DECISIONS TO ENGAGE IN ALLYSHIP By Rachael H. Pyram A THESIS Submitted to Michigan State University in partial fulfillment of the requirements for the degree of Psychology—Master of Arts 2023 ABSTRACT Allyship has been touted as a method to combat discrimination and cultivate inclusive environments in the workplace (Hebl et al., 2020). Extant perspectives on allyship predominantly focus on what factors engender engagement in allyship. Taking an alternative perspective, this study sought to examine why individuals are demotivated from allyship engagement. Given there are social costs associated with allyship behavior, the current study examined allyship through the lens of prosocial risk-taking (i.e., prosocial behaviors that carry a social cost), and posited that prosocial tendencies, tolerance to risk, and their interaction would positively impact allyship. As hypothesized, the results suggest that prosocial tendencies are important for allyship. Contrary to the hypotheses, risk tolerance did not significantly predict allyship or moderate the relationship between prosocial tendencies and allyship. Yet, as risk tolerance was significantly correlated to allyship behaviors, this study provides tentative evidence that future research should consider the role risk plays in deterring engagement in allyship. Keywords: allyship, prosocial behavior, social costs, interpersonal risk-taking TABLE OF CONTENTS INTRODUCTION .......................................................................................................................... 1 A REVIEW OF ALLYSHIP ........................................................................................................... 5 INTERPERSONAL RISK ............................................................................................................ 19 THE CURRENT STUDY: INTERPERSONAL RISK IN ALLYSHIP....................................... 29 METHODS ................................................................................................................................... 33 RESULTS ..................................................................................................................................... 36 DISCUSSION ............................................................................................................................... 40 CONCLUSION ............................................................................................................................. 53 REFERENCES ............................................................................................................................. 54 APPENDIX A: SURVEY MATERIALS ..................................................................................... 65 APPENDIX B: SUPPLEMENTARY ANALYSES ..................................................................... 67 iii INTRODUCTION In the last several years, there has been an increased focus on diversity, equity, and inclusion (DEI) in the workplace. This has become especially salient in industrial-organizational psychology, as concerns around social injustice have continued to have implications for talent management (Bhatia & Baruah, 2020). Perceptions of workplace discrimination have deleterious effects on employees’ job satisfaction, organizational commitment, work effort, and engagement in organizational citizenship behaviors (Ensher et al., 2001; Heiserman & Simpson, 2023), and increases both physical and psychological withdrawal from work (Volpone & Avery, 2013). Further, discrimination has been linked to several negative health outcomes (Pascoe & Smart- Richman, 2009; Mays et al., 2007). Resultingly, cultivating a positive, identity-affirming environment for diverse populations has become progressively crucial for organizations; indeed, evidence suggests that organizational efforts to support diversity can positively affect their diverse talent (Chrobot-Mason & Aramovich, 2013; Madera et al., 2012; Triana et al., 2010). Allyship has been suggested as a method by which one can reduce inequality and inequity, and further organizational goals for DEI (Gates et al., 2021; Hebl et al., 2020). It can provide direct interpersonal support to individuals experiencing discrimination or injustice (e.g., intergroup benevolence; Gates & Lillie, 2021; Gates & Hughes, 2021), but also has potential for broader sociocultural change in systems of inequality (e.g., collective action; Louis et al., 2019). Accordingly, the existing literature has sought to understand why and how people engage in allyship. Allies are thought to go through a life-long and continuous process of development (Chrobot-Mason et al., 2020). They must first learn why systemic oppression occurs, how it impacts marginalized populations, and how their unearned privilege contributes to the marginalization of groups without privilege (Edwards, 2006). Research has suggested that the 1 motivation to support marginalized populations derives from altruism, morality, self- gratification, or expectation of reward (Radke et al., 2020). These motivations for engaging in allyship are thought to be impacted by similar antecedent factors, indicating that irrespective of motive, allyship engagement is likely to preceded by beliefs, values, and emotions that stand in opposition to discrimination (Louis et al., 2019; Radke et al., 2020; Adra et al., 2020; Fletcher & Marvel, 2023). The literature considers allyship behavior to be learning about the causes of discrimination, communicating with others about oppression, and advocating for the rights of marginalized groups (Salter & Miglaccio, 2019). Overall, allyship behaviors are thought to reflect activism, which is why allyship is considered a method to reduce discrimination and increase inclusivity (Louis et al., 2019). Recent work has even gone so far as to examine how allyship can go awry and potentially harm disadvantaged populations and social change efforts, especially in instances where allies endorse saviorism or are performative (Kutlaca & Radke, 2023; Selvanathan et al., 2020). However, it is important to note that current perspectives on what factors drive allyship share the same assumption: that individuals are always willing to enact allyship. As noted in the literature on allyship development, allyship behaviors can engender social costs, as allyship can be controversial, disrupt the status quo, and incur negative responses from both marginalized group members and dominant group members (Warren et al., 2021; Salter & Miglaccio, 2019; Chrobot-Mason et al., 2020). Despite the recognition that allyship bears the potential threat of incurring social costs, existing work has yet to formally consider how this inherent interpersonal risk might deter individuals from engaging in allyship or where in the process of allyship individuals can experience this deterrence. Incorporating the role of interpersonal risk in allyship decision-making processes challenges the underlying assumption in the allyship literature that 2 individuals are unilaterally willing to engage in allyship, and, in considering demotivating forces, provides an opportunity to increase the robustness of current perspectives on how to engender allyship. To examine what demotivates allyship, the proposed research seeks to examine a noted challenge of allyship: interpersonal risk. I first review the literature on allyship, explicating how allyship is thought to operate, under what conditions it functions, and how the effect of possible negative social evaluations is underexplored in current conceptualizations of allyship processes. In order to examine how interpersonal risk assessment affects allyship behavior, I begin by reviewing risk regulation theory, which explores how individuals assess risk in relational contexts and use this to inform their behavior (Murray et al., 2008). To capture how individuals incorporate interpersonal risk assessment into decisions to engage in prosocial support behaviors that carry a threat for social costs, I integrate prosocial risk-taking theory, and generate hypotheses for how propensity for risk taking and levels of prosociality affect engagement in allyship (Do et al., 2017). Using a within-subjects vignette study (see Atzmuller & Steiner, 2010), I will test hypotheses using regression. This research contributes to understanding allyship in several ways. First, this research addresses the question of if people are willing to engage in allyship despite the risk. This contributes to a broader understanding of how to engender allyship—and thus cultivate its espoused benefits of anti-discrimination and inclusivity—by considering if the perception of social costs deter engagement in allyship. Secondly, this study examines allyship in relation to other kinds of prosocial helping behaviors. Existing research has not sought to define allyship as a prosocial behavior, but conceptually allyship aligns with the definitions, antecedents, and drivers noted in the prosocial helping behavior literature. Thus, in characterizing allyship’s 3 relationship with prosocial behavior, it offers the opportunity to examine allyship through the theoretical mechanisms outlined by the prosocial behavior literature, extending current parameterizations of allyship. Finally, this study formally considers the role of social costs in allyship by characterizing these costs as a type of interpersonal risk. In doing so, theories on interpersonal risk and prosocial risk-taking from other areas in psychology are integrated into existing conceptualizations of allyship and prosocial behavior at work, highlighting the decision- making process individuals undergo when helping behaviors have associated threats of social cost. As interpersonal risk is not often evaluated in workplace helping behaviors, incorporating these perspectives affords the opportunity to advance understandings of interpersonal helping in organizations. 4 A REVIEW OF ALLYSHIP When confronted with the harsh consequences of systemic oppression, disadvantaged populations can incite social change in order to improve their group status, and in doing so, engage in a struggle for power and status with the advantaged group (Simon & Klandermans, 2001). When a disadvantaged group member engages in behaviors to improve the conditions of their group, they are engaging in collective action, which is when an in-group member’s participation in social change derives from a concern for the collective and intends to improve outcomes for the entire group, as opposed to just themselves (Van Zomeren et al., 2008). However, it is possible for advantaged group members to participate in social change that seeks to improve conditions of disadvantaged group members. This participation constitutes allyship, which, broadly defined, refers to behaviors enacted by advantaged group members that are done to support and advocate for oppressed populations (Washington & Evans, 1991). As advantaged members, or members of dominant social groups, are afforded privileges through inequitable systems of oppression, they are better positioned to confront the exploitation of members of nondominant social groups because of their disparate privilege (Edwards, 2006). Allyship has been looked at as it applies to men supporting women, cisgendered people supporting those who fall elsewhere on the gender spectrum, heterosexual-identifying individuals supporting sexual minorities (e.g., lesbian, gay, bisexual, pansexual, and asexual persons), or White people supporting people of color (Warren et al., 2021; Duhigg et al., 2010; Erksine & Bilimoria, 2019). Despite this default binary (advantaged vs. disadvantaged), allyship is intersectional (Atcheson, 2018). Therefore, affiliation with a nondominant social group in one facet does not inhibit engagement in allyship in another facet where one does hold dominant group membership. For instance, a cisgendered White woman might experience privileges associated with her racial 5 identity, but experience inequities as a woman. In this scenario, she could be an ally to non- White individuals, while simultaneously benefitting from allyship enacted by a man. There are several dimensions under the broad umbrella of allyship that have been explored in the literature. Researchers have explored the antecedents of allyship, how allies develop, what motivations underscore allyship, and what behaviors constitute allyship. I will review the extant literature, highlighting how much of this existing work has considered why individuals choose to engage in allyship but has neglected to consider what factors inhibit allyship engagement. Drivers of Allyship To understand why individuals engage in allyship, it is important to consider why those from advantaged groups are driven to support and advocate for disadvantaged group members. Radke and colleagues (2020) proposed four orientations that characterize how the desire to engage in allyship varies based on the role of a focal ally’s internal motivations. The first orientation is a personal motivation for allyship, which is when advantaged group members support disadvantaged group members out of a desire to gratify their personal needs or self- image. Therefore, support behaviors are being performed for the purpose of personal reward and the motives of the enactor are individualistic and self-aggrandizing. Individuals operating from this orientation may be inclined towards narcissistic exhibitionism, resulting in an over-emphasis of advantaged group member contributions in efforts to support disadvantaged group members (e.g., White saviorism; performative allyship), which ultimately derogates support behaviors (Sue et al., 2019; Kutlaca & Radke, 2023). As there is a reliance on rewards to encourage motivation, a personal motivational orientation is unlikely to be sustainable over time, as individuals may become deterred from engaging in allyship once they stop benefitting from it. Research on extrinsic motivation (e.g., rewards, incentives) and its relationship with intrinsic 6 motivation and performance are mixed (Deci et al., 1999; Wiersma et al., 1992; Gerhart & Fang, 2015). Meta-analytic results suggest that when extrinsic incentives are indirectly related to performance (e.g., not formally evaluated in performance criteria), intrinsic motivation is more important for performance than when extrinsic incentives are directly related to performance (Cerasoli et al., 2014). This aligns with the stronger observed relationships between intrinsic motivation, rather than extrinsic motivation, and organizational citizenship behaviors (OCBs), which are a type of extra-role performance that improves organizational functioning and often includes support behaviors between coworkers (Finklestein, 2011; Piccolo & Colquitt, 2006). As allyship in the workplace is a support behavior that exceeds formal job requirements, findings on the relationships between intrinsic vs. extrinsic motivation and OCBs may help explain why the contingency of reward in a personal motivational orientation can result in a demotivation for allyship in the absence of rewards. An in-group focused motivation, like a personal motivation, tends to be viewed unfavorably and is thought to result in less sustainability over time. This orientation enacts support behaviors only in instances when their own group will benefit, or when it will result in positive reflections on their group (Radke et al., 2020). Individuals are thus likely to be motivated by emotions associated with negative reflections on their group (e.g., anger); for instance, Louis et al. (2019) found White guilt preceded White individuals’ engagement in allyship. Those with an in-group orientation may hold high social dominance orientations, and act to reinforce inequity between their in-group and subordinate groups (Fletcher & Marvell, 2023). Actions motivated from an in-group focus are conditional; as such, those with this purview may be demotivated to support and advocate for disadvantaged groups when they cannot also benefit from their actions. In the case of both personal motivation and in-group 7 focused motivation, even if positive outcomes are reached through support behaviors, individuals with these orientations operate from a place of patronization and paternalism that panders to disadvantaged groups’ issues while reinforcing the power structure that disparately benefits advantaged group members (Chrobot-Mason et al., 2020). Aligning with a personal motivational orientation, those with an in-group orientation are likely to experience demotivation for allyship when support behaviors do not benefit the needs of the enactor due to the necessity of extrinsic reward. In the case of an in-group motivation, the extrinsic reward is impression management, which is the maintenance of a desirable image (Bolino et al., 2008). Indeed, research suggests that when individuals engage in OCBs for the purpose of impression management, extrinsic motivation is more important than intrinsic motivation (Finklestein, 2011). Thus, when considering what is likely to deter persons with an in-group orientation, the predominant risk in performing allyship is consequences that would reflect poorly on the individual and their social group. The final two motivational orientations for allyship tend to be viewed more favorably. A motivation derived from one’s morals predisposes engagement in allyship when one’s moral principles are violated. Erksine and Bilimoria (2019) support this claim, noting that an individual’s values are likely antecedents of allyship; specifically, values like integrity, equity, justice, and empathy. Similar to the in-group orientation, emotions play a large role for individuals motivated by morality, as moral violations tend to evoke strong emotional responses (e.g., moral outrage). For example, Russell (2011) found that heterosexual individuals who held principles of justice and fairness took action on behalf of LGBTQ+ rights. In the same vein, Erksine and Bilimoria (2019) stated that “indignation and sadness about the racial and gender climate that spurred the #BlackLivesMatter and #MeToo movements may also serve as affective 8 antecedents of allyship.” However, there are morals and beliefs that might contribute to further subjugation of a non-dominant group; for example, if one’s religion prohibits same-sex relationships, then individuals who hold these religious beliefs may enact behaviors that would decrease the rights of LGBTQ+ individuals. Allyship from a moral motivational orientation is thought to lead to sustained change, as moral beliefs are intrinsically motivating, and can supersede group norms and other contextual boundaries (Roskies, 2003). This might indicate that experience of risk is suppressed, as one’s morals outweigh possible negative repercussions for enacting support behaviors. Given the saliency of individuals’ morals and values, those operating from this orientation may be more resilient to factors that would deter or demotivate them from allyship. The final motivational orientation—and the one most associated with allyship—is an out- group focused motivation. This orientation is characterized by a genuine effort to improve the status of marginalized groups, and does not include personal gratification, moral righteousness, or in-group aspirations (Radke et al., 2020). Given the focus in an out-group motivation is on benefiting others, and not oneself, it aligns with definitions of prosocial motivation (McNeely & Meglino, 1994). Grant (2008) found that intrinsic motivation is important for the relationship between prosociality and performance. Thus, like a moral motivation, an out-group focused orientation is likely to be more sustainable over time. individuals should be entirely intrinsically motivated, as they would not be seeking reward. When considering these various motivational orientations, there is an inherent assumption across all orientations that advantaged group members have a stable desire to support (or be viewed as supporting) disadvantaged group members. Radke et al. (2020) discuss how even though individuals may operate from personal or in-group motivations, they may conceal this in favor of socially desirable out-group or moral 9 motivations, for fear of negative consequences or backlash (e.g., being viewed as selfish or opportunistic, being ousted from the movement). This highlights how allyship is favorable and being perceived as an ally is socially desirable. Yet, despite this favorability, there is not a clear understanding of why individuals would not enact allyship when doing so would be socially desirable, and they hold morals, values, and motivational orientations that align with allyship. As Hebl (2020) notes, the first step in allyship is perceiving discrimination, whether that be for developing as an ally or enacting a support behavior. Though existing work has examined what drives allyship, it has not considered how these drivers affect individuals’ ability to perceive discrimination, assess possible penalties to allyship, and how this assessment impacts subsequent behavior. This indicates that understanding what drives individuals to be allies is not sufficient to explain if, when, or how they enact allyship. To better conceptualize the boundary conditions for allyship, it is relevant to consider how individuals become allies. Developmental Stages in Allyship Edwards (2006) discuss six stages in the identity development of an ally. These stages reflect Helms’ (1995) model for White racial identity development but generalize well to ally development for any marginalized group. Mirroring the dominant perspective in the literature, the stages for ally development operate from the perspective that individuals want to be allies. In the first stage (i.e., contact), individuals still hold naïve beliefs about their dominant group. For instance, they may endorse colorblindness, which is a view that divorces individuals from their group identification with the intention of downplaying race and racial identities (Brown et al., 2023); though this ideology has historically been lauded as a way to achieve equity and inclusion, it can actually be harmful to ethnic minorities as it minimizes and denies their racial realities and negates experiences of racial oppression (Knowles et al., 2009; Bonilla-Silva, 2006; 10 Kim et al., 2019). The second stage (i.e., disintegration) brings an awareness of how systems of oppression cause disparate treatment between dominant and nondominant groups. For example, a heterosexual person might learn about the restrictions homosexual men experience when donating blood in the United States, highlighting how their sexual orientation confers privilege (Shaw, 2020). Stages 1 and 2 provide context for how individuals can begin developing the skillset necessary to detect discrimination when it occurs, which instills allies with an understanding of the root causes of discriminatory treatment. Without moving through these initial developmental stages, support behaviors are unlikely to be effective, regardless of why an individual is driven to be an ally, because an enactor cannot engage meaningfully with discrimination if they consider discriminatory incidents without the context of underlying systems of oppression. The required learning that occurs in these stages may exist as a deterrent to budding allies; for instance, if developing an understanding of systemic oppression results in negative reflections on an individual or their in-group, allyship may be disregarded by those with a personal or in-group motivational orientation. In the third stage (i.e., reintegration), individuals must reckon with their privilege, and tend to regress into their dominant group whilst grappling with negative emotions, like guilt and anger. Once individuals are able to recognize how their dominant group engages in the systemic oppression of nondominant group members, they have moved to the fourth stage of ally identity development (i.e., pseudo-independence); however, in this stage, individuals are not yet able to meaningfully confront issues of oppression and discrimination because they direct anger at the dominant group while holding the false belief that they do not participate in systematic oppression. One’s motivational orientation can inform how individuals move through these stages, or why they may stagnate at a stage. For instance, though strong morals are thought to 11 prompt allyship, if reflecting on one’s privilege violates values an individual holds about themselves, this realization may deter continued progress in allyship development. One’s motivational orientation may also explain which stage is crucial in ally development; for example, the reality of systemic oppression in stage 4 may motivate in-group-oriented individuals to take action to improve their in-group’s image. It is relevant to note that thus far, developing allies have been coming to terms with the ways that systems of oppression afford them and their dominant group unearned privilege while simultaneously disadvantaging nondominant groups. These developmental stages reflect some of the antecedents and motivational orientations referenced earlier, suggesting that across the span of ally development, different drivers for allyship engagement might be salient at different points, and may exist to both encourage and deter allyship. While this has not been explored in the literature, this exemplifies the degree to which the process of allyship is underexamined, where within this process individuals may be demotivated to enact allyship, and from what sources demotivation originates. In the final two stages of ally identity development, individuals begin applying the learning they have done in earlier stages into action. In stage 5 (i.e., immersion-emersion), budding allies have shifted from trying to change the nondominant group to trying to change the dominant group they belong to. The sixth and final stage (i.e., autonomy) is when one’s privileged identity has been internalized as opposed to intellectualized, thus enabling the creation of alliances with people of nondominant groups to tackle the systems of oppression at work. As highlighted earlier, understanding what drives engagement in allyship is just one piece of the puzzle; to conceptualize allyship, it is also important to understand the process by which individuals who are driven towards allyship arrive at the decision to enact allyship when given 12 the opportunity. The stages of allyship development provide insight into how allies learn to identify instances of discrimination when they arise and understand how these instances reflect a broader social issue. Yet, once an individual is able to recognize discrimination, they must be willing and able to enact appropriate behaviors in response to it (Hebl et al., 2020). This mirrors the process of bystander intervention, where after noticing and classifying a situation as critical, bystanders must make the conscious decision to execute helping behaviors (Fischer et al., 2011); thus, as allies are witnesses (i.e., bystanders) to discriminatory incidents, their decisions to enact allyship behavior are contingent on their desire to engage in allyship, their ability to classify an incident as discriminatory, and the conscious decision to perform an allyship behavior in response to the discriminatory incident. As the final stages of allyship development are more action-oriented, in order to understand what demotivates an ally’s transition to the final stages of development, it is crucial to consider what factors inhibit behavioral representations of allyship. Edwards (2006) discusses that within these stages of development, the inherent privilege individuals hold affects their engagement with allyship and the efficacy of their allyship. This too is highlighted in the process of bystander intervention, where the enactment of helping behaviors is affected by a bystander’s self-assessment of their efficacy to deliver support (Fischer et al., 2011). Thus, privilege due to one’s advantaged group status is likely to factor into individuals’ decisions to engage in allyship. Further, even when individuals are motivated to be allies and have undergone the process to detect discrimination, they may be demotivated to engage in allyship due to their social position. In order to characterize what other factors decrease engagement in allyship behaviors, it is relevant to explore what behaviors are classified as allyship. 13 Contextualizing Behavioral Enactments of Allyship Salter and Migliaccio (2019) highlight three overarching categories of allyship behavior: knowledge and awareness, communication and confrontation, and action and advocacy. First, paralleling Edwards’ stages, allies must educate themselves about the lived experiences of nondominant populations and how mechanisms, both social and institutional, cause discrimination. Additionally, they must engage in critical self-reflection. For example, White allies must go through the process of interrogating their own Whiteness and learning about their privilege. Erksine and Bilimoria (2019) expand on this, suggesting that interrogating one’s own Whiteness requires examining the ways that Whiteness has been normalized, and challenging the societal and organizational messaging and structures that centralize the monolithic White perspective as the default point of comparison (i.e., the status quo). Similarly, Duhigg and colleagues (2010) found in qualitative interviews with heterosexual allies that there were common themes regarding the process of self-reflection they undertook; heterosexual allies had to realize how they were socialized with respect to their sexual orientation, understand homophobic fears about being mis-labeled as homosexual, and contextualize the ways in which their heterosexuality affords them privilege. This educational process is lifelong, and allies must continuously make strides to self-reflect (Chrobot-Mason et al., 2020). As it applies to the stages of ally development, this first behavioral category mirrors stages 1-4. In engaging in education and critical self-reflection, individuals have explored the systems of oppression that exist, as well as their role in these systems. While negative emotions (e.g., guilt, shame, anger) tend to be associated with these processes of self-reflection and self-learning, the literature has not explored if or when negative emotions are a deterrent to allyship self-development, or what factors would influence this. The motivational orientations referenced earlier do discuss the likelihood of 14 sustainable action, with moral motivation and out-group focused motivation having the greatest propensity to provide sustained motivation as they are preceded by action-oriented emotions (i.e., moral outrage and group-based anger, respectively; Radke et al., 2020). Knowledge and awareness behaviors are defined by intraindividual learning behaviors. However, the next two behavioral categories describe allyship behaviors in interpersonal contexts; with the addition of an interpersonal context, there are new factors that could demotivate allyship engagement that must be considered. The second behavioral category for allyship is communication and confrontation; this emphasizes the need to go beyond one’s own learning and self-reflection, in order to engage in conversation with others about issues of social injustice and confront instances of discrimination or prejudice when they arise (Salter & Migliaccio, 2019). Like stages 1-4 in ally development enable stages 5 and 6, the first behavioral category of knowledge and awareness affords allies with the ability to detect discrimination and begin engaging in behaviors that respond to it. This behavioral category is in-part defined by interacting with others; accordingly, characteristics of these interactions inform how individuals develop and engage in allyship behaviors. For instance, a dominant group member that is communicating with others about privilege must be aware of certain social rules, and of their audience, to communicate well. As Edwards (2006) notes, a person’s privilege affects their evaluation and interpretation of social rules. Thus, allies need to be aware of their social environment, as there is risk for interpersonal and social costs when going against the status quo or dominant culture (Warren et al., 2021; Erskine & Bilimoria, 2019). This social component of allyship behaviors that require interpersonal interaction brings a unique threat that may exist to deter allyship: interpersonal risk. For example, nondominant group members may react negatively if they feel a purported ally is centralizing themselves in a 15 discussion or taking up space in such a way that it prevents nondominant group members from participating equally (e.g., White saviorism; Radke et al., 2020); thus, allies must be aware that their allyship may be perceived negatively by the disadvantaged groups they seek to support. Similarly, communicating with other dominant group members can be equally challenging as they may be made to feel uncomfortable, like they are the “bad guy,” and they may react defensively (Chrobot-Mason et al., 2020); resultingly, allies must also be aware that their allyship may be perceived negatively by members of their advantaged in-group. This threat of negative consequences is highlighted in the research on motivational orientations for allyship, where less favorable orientations (i.e., personal and in-group motivations) are concealed in favor of moral or out-group motivations in order to avoid negative perceptions. The need to be aware of one’s social environment extends to the confrontation part of this behavioral category. To confront discrimination, individuals must be attuned to the behaviors of others in their social environment. Once identifying a need for allyship, individuals must then act appropriately. The decision to respond to discrimination is affected by the perceived social dynamics of the incident. For instance, individuals may be motivated to not respond (i.e., bystander passivity) even when they recognize a behavior as unacceptable because of a perceived diffusion of responsibility, a fear of retaliation (i.e., evaluation apprehension), or an overreliance on other’s reactions to prompt behavior (i.e., pluralistic ignorance; Fischer et al., 2011). Thus, decisions to confront discrimination—and thereby engage in an allyship behavior— are reached by considering other individuals in the social context and evaluating the likelihood that intervening will result in negative consequences. Communication and confrontation behaviors inherently consider how relationships with other individuals in a social environment affect the way an ally enacts behaviors. This relational perspective extends to the final category 16 of allyship behavior proposed by Salter and Migliaccio (2019): action and advocacy. This centers around demonstrable advocacy for nondominant groups; these behaviors can be private (e.g., signing a petition) or public (e.g., attending a protest; Radke, et al., 2020). Notably, action and advocacy behaviors build upon the role of privilege highlighted in communication and confrontation behaviors. Utilizing one’s social position as an advantaged group member allows for progress to be made in spaces where non-dominant perspectives might not register as strongly. Erksine and Bilimoria (2019) discuss how allies are best positioned to “infiltrate” an organization or group from the inside because they possess sociocultural knowledge of norms for their group, which enables the introduction of non-dominant group advocacy in a manner that gently disrupts the status quo to motivate change. Additionally, shifts in opinion or purview are better facilitated by same-group members. For example, conservative men were more willing to support abortion after discussing the topic with a liberal man as compared to a liberal woman (Maass et al., 1982); similarly, men were significantly more likely to be willing to intervene in a sexual violence situation when they perceived that other men would also be willing to intervene (Fabiano et al., 2003). Thus, not only must individuals interpret their social environment to decide whether or not to enact allyship, they must also evaluate how the social environment will impact the efficacy of their ally behaviors in order to effectively intervene. This again relates to the process of bystander intervention wherein conscious decisions to intervene are impacted by self-evaluations of intervention efficacy (Fischer et al. 2011). The behaviors proposed by Salter and Miglaccio provide some clarity for how an ally engages in the development of their identity. Additionally, they indicate that to understand allyship, one needs to go beyond the dominant perspective in the literature that seeks to explain allyship through individual motives and antecedents of allyship engagement, and alternatively, 17 extend current perspectives to consider how allyship’s relational nature provides unique influences that affect decisions to engage in allyship. As decisions to communicate about social justice, confront discrimination, advocate for disadvantaged groups, and enact collective action occur in a social environment, it is relevant to consider how this environment may hinder individuals’ willingness to engage in allyship. The consideration of the social environment highlights two important factors. First, that the threat of social costs affects decisions to engage in allyship, and secondly, that individuals are likely to evaluate social costs differently based on their inherent privilege; notably, these two factors are considered in the bystander intervention literature to understand why bystanders remain passive in the face of a critical situation that requires intervention. In taking the perspective that there are factors that influence allies to remain passive, the assumption that people who view allyship favorably have a consistent and unshakeable desire to engage in allyship whenever the opportunity arises is challenged. This affords the opportunity to consider how the relational nature of allyship may exist as a deterrent to engaging in allyship behaviors; further, in taking the perspective that there are factors that demotivate allies from enacting support behaviors, current work on how allyship functions can be applied to better understand how the individual differences for allyship and the development of allies are reciprocally impacted by the factors that demotivate allyship. Given that allyship is discussed as interrupting the status quo, resulting in the risk of social costs, one critical factor that may demotivate allyship and keep allies passive in the face of discriminatory events is the perception of interpersonal risk. 18 INTERPERSONAL RISK As noted above, the confrontation of discrimination comes with interpersonal risk. Thus, evaluations of interpersonal risk affect how people decide to enact allyship, which is highlighted in the decision-making process that underlies bystander intervention, where individuals’ factor their fear of retaliation into whether or not they enact support behaviors. To conceptualize how interpersonal risk affects individuals’ desires to perform helping behaviors, it is relevant to understand how individuals define and assess risk. I lean on risk regulation theory, which provides a foundation for explaining how individuals interpret risk in interpersonal relationships and use information about their relationship to shape their behaviors. Then, to consider how risk assessment occurs when risky behaviors are done to support others—as they would be in the case of allyship—I delve into prosocial risk-taking theory. This provides a framework for explaining how risk taking interacts with prosocial tendencies to affect how individuals respond in social dilemmas. In reviewing the literature on risk regulation and prosocial risk-taking, I will highlight what factors are relevant to consider in interpersonal risk assessment, specifically in prosocial risk assessment, and how this informs decisions to engage in allyship. Assessing Risk in Interpersonal Contexts Risk is broadly defined as behaviors that incur possible costs and rewards, where the likelihood of an outcome is variable and the consequences of said outcome are uncertain (Holton, 2004). Typically, risk has been construed negatively, and is thought to constitute antisocial, illegal, impulsive, or reckless behaviors; accordingly, negative risk can compromise the person making a risky decision, as well as others, through possible dangerous or undesirable outcomes (Fryt et al., 2021). However, there are instances in which risk can be positive. Positive risk-taking behavior is considered socially acceptable, personally constructive, and typically non- 19 threatening to one’s health, safety, or well-being; thus, positive risk can help with the acquisition of new skills, identity development, personal responsibility, goal-setting, and social competence (Duell & Steinberg, 2019). Though positive and negative risk vary wildly in the severity and context of their associated outcomes, these behaviors both have unknowable and probabilistic consequences, and thus, require individuals to evaluate the potential costs and rewards (Fryt & Szczygiel, 2021). Risk regulation theory posits that when assessing risks, individuals must strike a balance between pursuing goals that protect them from costs and goals that expose them to reward. In interpersonal contexts, if individuals are pursing goals that protect them from costs, they are usually seeking to avoid hurt or rejection; on the other hand, when individuals are pursuing reward goals in relational contexts, they are motivated to engender connectedness or belongingness (Cavallo et al., 2013; Murray et al., 2008). As self-protection goals are designed to avoid interpersonal costs, they minimize dependence on others, and accordingly, retain an individual’s control over their own outcomes. This is especially salient when risk is perceived as immediate or severe, as this kind of risk heightens concerns about experiencing a negative outcome and favors exercising caution. Connectedness goals, on the other hand, seek to pursue interpersonal rewards, thus increasing dependence on others and yielding control over one’s outcomes to another. When risk is perceived as distal or minute, it affords more opportunity to pursue connectedness goals, as the threat of a negative outcome is attenuated. Risk regulation theory has most often been applied to romantic relationships, however, the assessment process it proposes provides a generalizable framework for considering how characteristics of a relationship affect decisions to engage in risky behavior. In order to explicate how individuals choose which goals to pursue (i.e., self-protection vs. connectedness), risk regulation theory asserts that individuals seek to optimize their sense of assurance in a relationship, and 20 accordingly, prioritize either protection goals or connectedness goals based on their perceptions of their counterpart’s regard; this process is made up of three stages: appraisal, signaling, and response (Murray et al., 2006). In appraisal, individuals attempt to assess risk by gauging their counterpart’s regard, or the likelihood they will experience rejection or acceptance from this person; the formation of this opinion incorporates implicit beliefs about their counterpart, beliefs about themselves, and beliefs about the relationship. Appraisal seeks to answer: “how confident am I that my counterpart will accept or reject me?” Assessing the likelihood of acceptance or rejection informs whether individuals have leeway to decrease self-protection goals and increase connectedness goals. Further, this stage considers that leeway differs between-person, as some individuals have resources (e.g., disparate privilege) that allows them to withstand the impact of receiving a negative outcome. In the signaling stage, individuals are motivated to detect the discrepancy between the current appraisal of their counterpart’s regard and the desired appraisal of their counterpart’s regard. Individuals also use this discrepancy to evaluate themselves. Signaling seeks to answer: “how will possibilities of acceptance vs. threats of rejection affect me?” This stage considers perceptions of counterpart acceptance and rejection, but also whether the focal individual is seeking acceptance or rejection. Therefore, how individuals are expected to feel is considered, with rejection typically evoking negative emotions and acceptance typically evoking positive emotions. The final stage—behavioral response—uses the forecasted outcomes from the signaling stage to dictate what behavioral response will appropriately balance self- protection goals and connectedness goals. This stage answers the question: “how should I behave in order to retain feelings of safety in this relationship?” The process proposed by risk regulation theory highlights that when assessing interpersonal risk, individuals evaluate the possibility of 21 rejection and consider how this rejection will affect them before deciding whether or not a risky behavior should be performed (Murray et al., 2006). This pattern has been found in established relationships and novel relationships, indicating that the longevity of a relationship is not the most important factor in assessing risk (Cavallo et al., 2013). As the forecasted impact of being perceived negatively by one’s counterpart can be buffered by privilege (or disparate resources), and privilege is also important for allyship efficacy, this indicates that privilege may be especially relevant for allyship because it impacts the perception of risk. Risk regulation theory is useful for exploring why the threat of social costs can demotivate allyship. The theory allows for the consideration of how contextual factors in the social environment might deter allyship by explicating how risk evokes a motivational conflict in individuals. It incorporates the effect of relational characteristics on risk assessment by highlighting that individuals are driven by a desire to retain feelings of safety in relationships, and this is strongly impacted by their perceptions of their counterpart’s regard. It also acknowledges risk is appraised differently between individuals, based upon their estimation of the impact a possible social cost would have on them. Applying this to allyship, risk regulation would suggest that when allies decide to engage in allyship behaviors, they consider what behavior they have resources to enact that would allow them to retain feelings of safety, and how this behavior will affect the allyship recipient’s regard for them. However, it is relevant to draw attention to the fact that the motivational conflict proposed by risk regulation theory is centered around the avoidance of potential costs associated with risk and the pursuit of potential rewards that risk can produce. From this perspective, motivations for avoiding costs and obtaining rewards are done for the gratification of the focal individual; even in situations where outcomes 22 may benefit the relationship between two individuals, the positive and negative risk outcomes are primarily regulated to engender positive outcomes for the focal risk-taker. Allyship, however, is meant to primarily advance the rights of disadvantaged group members. Thus, the intrinsic motivational conflict represented in risk regulation does not account for how risk is regulated when the potential for costs and rewards might also exist outside of the focal risk-taker; put otherwise, risk regulation does not formally consider how individuals assess risk when they are taking risks for others, and not solely for themselves. Further, it does not consider how decisions to engage in risk occur when possible costs are at the expense of the focal risk-taker and possible rewards are intended to only benefit someone else. As allyship reflects these conditions, it is critical to understand how risk-taking functions when decisions are prosocial in nature. Prosocial Helping Behaviors In order to characterize the impact of risk in allyship behaviors, it is relevant to discuss how allyship relates to the broader literature on behaviors that are enacted to support others. Though current work has not sought to define allyship as a type of support behavior, definitions of allyship align with conceptualizations of prosocial or helping behaviors. As defined by Dovidio (1984), prosocial behaviors are behaviors that one’s society deems valuable, and helping behaviors are a type of prosocial behavior that are performed voluntarily to assist another person. Prosocial and helping behaviors tend to be referred to interchangeably (e.g., McNeely & Meglino, 1994; Thielmann et al, 2020; Penner et al., 2005). Given prosocial helping behaviors are positive social acts done to cultivate and maintain the well-being of others, they typically constitute behaviors like volunteering, cooperating, and organizational citizenship (McNeely & Meglino, 1994; Armstrong-Carter et al., 2021), and in organizational contexts, these behaviors 23 can be extra-role or in-role (Ng & Van Dyne, 2005). Recall that allyship is defined as support and advocacy from advantaged group members which contributes to social change that improves the conditions of disadvantaged group members (Washington & Evans, 1991; Kutlaca & Radke, 2023). Thus, allyship reflects the intention to improve the well-being of others that underlies prosocial behavior. Like current perspectives on allyship, the literature on prosocial behavior has sought to conceptualize why and when people engage in prosocial behavior. Penner and colleagues (2005) highlight that helping is derived from affect and arousal processes, wherein the emotional reactions that prompt helping behavior occur by witnessing others’ distress. Despite the importance of affect and arousal for helping, the presence of these components alone cannot explain why individuals are motivated to help. Prosocial behavior is thought to stem from conditioning (Grusec et al., 2002; Staub, 2002; Eisenberg & Fabes, 1991); a desire to satisfy personal needs and retain a positive self-image (Schwartz & Howard, 1984; Omoto & Snyder, 1995; Wedekind & Braithwaite, 2002); via norms for social responsibility and reciprocity (Dovidio, 1984; Boster et al., 2001); and from the experience of strong emotions which prompt individuals to help in situations of distress (Davis, 1994). The pursuit of helping goals can be either egoistic or altruistic in motivation. For instance, individuals may choose to help in order to relieve the negative mental state caused by witnessing someone else’s distress (i.e., egoistic motivation), or they may be motivated to improve the welfare of the person in distress (i.e., altruistic motivation). The theorized drivers of prosociality mirror motivations for allyship. Egoistic motives for prosocial behavior that prioritize an enactor’s personal needs reflect a personal or in-group motivational orientation for allyship; on the other hand, when individuals are motivated towards prosocial behavior out of a desire to benefit others without the expectation 24 of reward, this reflects a moral or out-group focused motivational orientation for allyship. It is important to highlight that while egoism and altruism may help explain why individuals are motivated to engage in prosocial behavior, there is no requirement that prosocial behaviors must be motivated by altruism in order to be prosocial (Batson & Powell. 2003). Further, in focusing on only one’s motivational orientation, the impact of the social context is ignored (Feigin et al., 2014). Resultingly, researchers have called for the incorporation of interpersonal influences on prosocial behaviors (Simpson & Willer, 2015). To examine how the interpersonal environment gives rise to risk, and how this subsequently affects prosocial behavior, it is relevant to explicate how social costs are defined in prosocial behavior. Risk in Prosocial Behavior Prosocial helping behaviors can often incur a cost to the enactor (Thielmann et al., 2020), and some researchers believe that prosocial exchanges must incur a cost to the enactor in order to benefit another (Barrett et al., 2002). Though cost in the prosocial behavior literature is not well- defined, in general, high-cost behaviors are viewed as requiring personal resources to be expended (Kayser et al., 2010), requiring moral courage (Zhang & Epley, 2009), or requiring a large commitment from the enactor (Padilla-Walker & Fraser, 2014); thus high-cost behaviors tend to be classified as civic engagement, volunteering, or helping strangers, and parallel the behaviors defined as allyship in the literature. Given high-cost behaviors require more personal resources, when individuals choose to be prosocial, they must consider whether the associated costs of a behavior are permissible based on the resources they have available (Barrett et al., 2002). In prosocial behaviors, the cost of a behavior is known (Do et al., 2017); for instance, individuals are aware that in signing up to volunteer, they are committing time and energy to a 25 cause. Thus, individuals can factor known costs into whether or not they choose to engage in prosocial behavior. However, there are instances where costs are not known. As noted previously, behaviors that incur possible costs and rewards, where the likelihood of an outcome is variable and the consequences of outcomes are uncertain are classified as risky behaviors (Holton, 2004). Prosocial risk is when the intention of a behavior primarily benefits another individual and not oneself, and additionally, the action incurs an unknown cost in the form of a risk, which is typically social (Do et al., 2017). Prosocial risk-taking theory explicates how the distinct, and often contradictory, constructs of prosociality and risk interact to inform prosocial risk-taking behavior, which is defined as “engaging in a risky decision with the intention of helping other individuals” (Do et al., 2017). Prosocial risk-taking was originally proposed to understand how prosociality and risk-taking affect adolescents’ social development (Armstrong-Carter et al., 2021). However, the prosocial risk-taking framework is well-suited to describe allyship, as allyship is an out-group focused helping behavior that has the threat of interpersonal risk when enacted. The prosocial risk-taking framework affords a formal opportunity to examine how the prosocial intention behind allyship behaviors are affected by the threat of interpersonal risk, thus enabling the exploration of how interpersonal risk can inhibit decision to engage in allyship. Prosocial risk-taking considers how an individual’s levels of prosociality and risk-taking jointly affect whether they engage in helping behaviors during a social dilemma. Further, it is crucial to consider that individuals are differentially deterred from the social costs associated with prosocial behaviors, as tolerance to costs are informed by the resources an individual is willing and able to expend (Kawamura & Kusumi, 2018). Do and colleagues (2017) proposed that the intersection of prosocial and risk-taking tendencies, there are four types of individuals: prosocial 26 risk takers, who are high is prosociality and risk-taking; antisocial risk takers, who are low in prosociality and high in risk-taking; empathetic bystanders, who are high in prosociality and low in risk-taking; and indifferent bystanders, who are low in both prosociality and risk-taking. Looking at prosocial risk-taking theory alone, the only delineation between behavioral types occurs through their levels of risk-taking and prosociality. From this perspective, prosocial risk takers are functionally as similar to antisocial risk takers as they are to empathetic bystanders, due to a shared high standing on one individual difference variable. Thinking about the process of risk assessment proposed by risk regulation theory allows for the consideration of how the behavioral types proposed in prosocial risk-taking theory engage in decision making about risky behavior. The addition of risk regulation theory can help to better parse out what drives risk-taking behavior between the behavioral types. To exemplify, consider that prosocial risk takers desire connectedness and their inherent tolerance to risk allows them greater flexibility to pursue connectedness goals. Perhaps this occurs because in risk regulation, prosocial risk takers are less likely to assess the threat of rejection in the appraisal stage or the consequence of rejection is less salient to them in the signaling stage, allowing for the pursual of connection in the response stage. For an empathetic bystander, who like the prosocial risk taker desires connectedness, the way they perceive and react to rejection threat in the appraisal and signaling stages may be what differentiates them from a prosocial risk taker. Further, when considering an antisocial risk taker, their appraisal and signaling stages may reflect the risk regulation process of a prosocial risk taker, as they are equally risk tolerant, but they could be entirely driven by self-protection goals and thus act in way that minimizes their dependence on another. Therefore, risk regulation theory contributes a lens into the decision-making process that underlies engagement in prosocial risky behavior. 27 Integrating prosocial risk-taking theory with risk regulation theory’s insight into how risk is appraised in interpersonal contexts highlights what impacts individuals’ decisions to engage in risk that is prosocial in nature. Specifically, it affords the opportunity to consider how the risk associated with prosocial behavior can impede engagement in prosocial behavior, even when individuals endorse prosociality and desire to behave as such. This perspective addresses a concern I highlight in the allyship literature, which presumes that individuals always want to engage in allyship if presented with an opportunity to do so. Understanding how prosocial risk appraisal functions allows for the consideration of how the social costs associated with allyship behavior impact decisions to engage in allyship. Given the complexity in what factors individuals use to assess risk in a social environment, and how this assessment impacts their intentions to engage in prosocial helping behaviors, I will now explicate how interpersonal risk is expected to affect decisions to engage in allyship. 28 THE CURRENT STUDY: INTERPERSONAL RISK IN ALLYSHIP The proposed study sought to investigate why individuals who view allyship favorably are deterred from engaging in it. Current perspectives on allyship have explored the individual differences and motivations that drive allyship engagement but have failed to consider that there are instances in which individuals are demotivated to be allies. As allyship is controversial and is associated with the possibility of incurring social costs, perceptions of interpersonal risk in an allyship scenario might exist as a possible deterrent. An allyship scenario, for the purposes of this study, constitutes an instance in which discrimination occurs and a bystander is faced with the dilemma of whether to enact allyship or not; thus, allies are enactors of allyship, and recipients of allyship can either be victims of discrimination (i.e., targets) or instigators of discrimination, as allyship can both support marginalized persons and confront discriminatory actions. The literature on interpersonal risk highlights that in interpersonal relationships, individuals desire positive regard from their counterpart; yet they are faced with the quandary of wanting to protect themselves against negative consequences and needing to risk said negative consequences in order to cultivate connection with others. They evaluate whether to engage in interpersonal risk depending upon their perceptions of their partner’s regard and whether they are able to afford the possibility of suffering a negative response. In instances where interpersonal risk is prosocial in nature, and does not stand to benefit the focal risk-taker, individuals’ desire to be prosocial is attenuated by the degree to which they are willing to engage in risk; this too is affected by their ability to tolerate associated costs. As allyship incurs prosocial risk, individual tendencies towards prosociality and risk are expected to impact whether or not individuals decide to perform allyship behaviors. I will now explicate the relationships between prosocial tendencies, tolerance to risk, and allyship behavior. Figure 1 depicts the expected relationships for the current study. 29 Figure 1 The Proposed Model Note: All hypothesized relationships are positive. Dashed lines represent a moderation effect. Prosociality and Allyship As prosociality is crucial to understanding why people engage in helping behaviors for others, it is relevant to consider the relationship between prosocial behavior and allyship. Prosocial behavior constitutes actions that are designed to benefit others, and these behaviors tend to be “societally acceptable” as opposed to anti-social or harmful (McNeely & Meglino, 1994). Allyship is behavior that seeks to support social change efforts that improve the status and conditions of marginalized populations (Kutlaca & Radke, 2023); further, due to increased social awareness around systemic oppression, allyship has gained traction, especially in the workplace (Melaku et al, 2020). Accordingly, there has been a rise in organizational efforts to support diverse talent and cultivate inclusivity (Chrobot-Mason & Aramovich, 2013; Madera et al., 2012; Triana et al., 2010). This suggests that allyship is socially favorable, and as it is intended to help others, it aligns with definition of prosocial behavior. Thus, I hypothesize that prosocial tendencies will positively relate to allyship. Hypothesis 1: Prosocial tendencies will be positively related to allyship. 30 Risk and Allyship Allyship is thought to include the threat of social costs. This occurs because allyship seeks to disrupt the status quo and dominant culture, and in doing so, can expose an ally to opposition from other dominant group members (Warren et al., 2021; Erksine & Bilimoria, 2019). In challenging the status quo and advocating for disadvantaged populations, other dominant group members might feel uncomfortable, guilty, or angry, and become defensive (Chrobot-Mason et al., 2020). This is discussed in the stages of ally development, wherein allies initially regress into their dominant culture once learning about how they have been historically afforded unearned privilege and benefit from systems of oppression that harm others (Edwards, 2006). The threat of enmity from allyship also exists when interacting with marginalized populations. If disadvantaged groups view an ally’s advocacy as performative, or if an ally centralizes themselves and minimizes marginalized voices in social change efforts, they may experience negative consequences (Radke et al., 2020). Thus, allies must be aware that their allyship may be perceived negatively by the disadvantaged groups they seek to support and by members of their in-group. The threat of being viewed unfavorably is noted in work on motivational orientations for allyship, wherein individuals operating from motivations that stem from a desire for personal gratification or reward may conceal their reasons for engaging in allyship in order to evade negative perceptions (Radke et al., 2020). The possibility for negative pushback constitutes risk, which is defined as outcomes that have unknown and variable consequences (Holton, 2004). Prosocial risk-taking theory proposes that individuals’ combined levels of prosociality and risk tolerance inform whether they are likely to engage in prosocial risk, like allyship (Do et al., 2017). Thus, it is likely that individuals who both endorse prosociality and are tolerant to risk will be more willing to engage in allyship, as they have a 31 strong desire to engage in altruistic support behaviors and are willing to incur possible social costs in order to do so. Therefore, I hypothesize that there will be a positive relationship between propensity for risk and allyship, and additionally, risk tolerance will positively moderate the relationship between prosocial tendencies and allyship. Hypothesis 2: Risk tolerance will be positively related to allyship. Hypothesis 3: Risk tolerance will positively moderate the relationship between prosocial tendencies and allyship. 32 Participants and Procedure METHODS Participants were recruited from the survey platform Prolific, which has been found to provide high-quality data as compared to other platforms (Palan & Schitter, 2018). To qualify, participants had to live in the United States and work at least 20 hours/week. Prior to data collection, required power was estimated across 10,000 simulations in the R package InteractionPoweR, which indicated that 400 respondents would sufficiently power the analyses (Baranger et al., 2022). A total of 439 participants completed the survey; 8 participants failed the attention check and to ensure high data quality were screened out, resulting in final sample of 431 participants. The survey took approximately 10 minutes to complete, and participants were compensated at approximately $12 an hour. The sample was gender-balanced with 48.3% female, 49.4% male, and the remaining 2.3% identifying as non-binary or other. Most participants were White (75.4%) and had a 4-year degree or above (62.9%). Participant age ranged from 19 to 71 (M = 36.53, SD = 10.37). The survey was a single time point vignette study. Vignette studies present constructed descriptions of systematic combinations of characteristics of interest (Atzmuller & Steiner, 2010); thus, to capture how participants choose to respond to an allyship dilemma, participants read a vignette depicting an instance of workplace discrimination that might warrant an ally intervention. The vignette was adapted from Basford et al. (2014) and depicts an instance of gender discrimination; in their study, participants were able to detect discrimination from the vignette and indicated they expected it would have negative work outcomes on the target, so this scenario was selected to ensure the vignette would have discernable discrimination present and that the negative impacts of said discrimination would be salient. Participants read the allyship 33 dilemma vignette from the perspective of a bystander and indicated whether they would enact allyship behaviors in support of the target of discrimination in the vignette. See Appendix A for the experimental vignette. Participants also filled out measures capturing their prosocial tendencies, tolerance to risk, and endorsement of allyship ideologies. Measures Prosocial tendencies. Prosocial tendencies were captured with the revised version of the Prosocial Tendencies Measure (PTM-R; Carlo et al., 2003). The PTM-R captures six types of prosocial behavior: (1) public behavior, (2) anonymous behavior, (3) behavior in dire settings, (4) emotional behavior, (5) behavior that is compliant, and (6) altruistic behavior. Participants rated agreement with items on 1-5 Likert scale. Example items include “I get the most out of helping others when it is done in front of other people” and “I often make donations without anyone knowing because it makes me feel good”. See Appendix A for a full list of the items. Risk tolerance. Tolerance to risk was captured using the social subsets of the Multi- Domain Risk Tolerance scale (MDRT; Shou & Olney, 2022). Participants rated agreement with items on 1-5 Likert scale. An example item is “Talking about a sensitive topic with someone when there is a risk that the person may react badly”. See Appendix A for a full list of the items. Allyship endorsement. To capture whether participants endorse attitudes about allyship, participants responded to the allyship measure proposed by Gates et al. (2021), which includes items like “When I see people from marginalized groups being treated unfairly, I stand up for them”. Participants were provided with a definition of marginalized groups in the United States and were instructed to think about these groups when responding to item. Question phrasing was altered to not specify the type of allyship being enacted (i.e., racial vs. gendered allyship). Participants rated agreement with items on 1-5 Likert scale. See Appendix A for the full item list. 34 Allyship intentions. To evaluate whether individuals would respond to the experimental vignette like an ally, participants filled out items by from an adapted version of the Trans Allyship Intentions scale by Fletcher & Marvell (2023). They were instructed to think about the target of discrimination in the vignette. An example item is “I would be a visible ally to this person in my organization”. Question phrasing was altered to not specify the type of allyship being enacted (i.e., racial vs. gendered allyship). Participants rated agreement with items on 1-5 Likert scale. See Appendix A for the full item list. Controls. Membership in an advantaged group has been theorized to impact allyship due to the privilege associated with dominant group membership (Edwards, 2006). Accordingly, participant gender (1 = male, 0 = female and other) and participant race (1 = White, 0 = Other) was entered into the model as control variables. 35 RESULTS The descriptive statistics, correlations, and scale reliabilities are in Table 1. Hypotheses were evaluated using moderated multiple regression and followed best practices by Aguinis & Gottfredson (2010). The results of the regression analyses for allyship endorsement and allyship intentions are in Table 2 and Table 3, respectively. Table 1 Descriptive Statistics, Correlations, and Scale Reliabilities Variable M (SD) 1 2 3 4 5 6 1. Prosocial tendencies 2.79 (0.46) (0.77) 2. Risk tolerance 3.08 (0.67) 0.29** (0.79) 3. Allyship endorsement 3.35 (0.76) 0.23** 0.07 (0.86) 4. Allyship intentions 3.67 (0.64) 0.28** 0.15* 0.44** (0.91) 5. Gendera 6. Raceb 0.49 (0.50) 0.13** 0.05 -0.08 -0.09 - 0.75 (0.43) -0.06 0.07 -0.03 0.09 0.04 - Note. N = 431. Cronbach’s alpha is reported along the diagonal. aGender: 1 = male, 0 = female and other. bRace: 1 = White, 0 = other. Prosocial tendencies, risk tolerance, allyship endorsement, and allyship intentions were rated on a 5-point scale with higher values indicating greater magnitude or agreement. *p < .05, **p < .01. Hypothesis 1 asserted that there would be a positive relationship between prosocial tendencies and allyship. Prosocial tendencies were significantly positively correlated with both allyship endorsement (r = .23, p < .01), which measured whether participants endorsed allyship ideals, and with allyship intentions (r = .28, p < .01), which measured whether participants would engage in allyship to support the target of discrimination in the vignette. Prosocial tendencies significantly predicted allyship endorsement (b = .18, SE = .04, p < .01) and allyship intentions (b = .20, SE = .04, p < .01). Thus, hypothesis 1 was supported. 36 Table 2 Regression Results for Allyship Endorsement Variable Step 1 Gendera Raceb Step 2 Gendera Raceb Prosocial tendencies Risk tolerance Step 3 Gendera Raceb Prosocial tendencies Risk tolerance Prosocial tendencies x risk tolerance b -.12 -.05 -.16 -.02 .18 .01 -.16 -.02 .18 .01 .01 SE .08 .09 .08 .09 .04 .04 .08 .09 .04 .04 .03 β R2 -.08 -.03 -.11* -.01 .24** .01 -.11* -.01 .23** .01 .01 .01 .06** .06** Note: aGender: 1 = male, 0 = female and other. bRace: 1 = White, 0 = other. *p < 0.05, **p < 0.01. Hypothesis 2 proposed that risk tolerance would be positively associated with allyship. Though risk tolerance had a significant positive correlation with allyship intentions (r = .15, p < .05), it was not significantly correlated to allyship endorsement (r = .07). Risk tolerance was not found to significantly predict allyship endorsement (b = .01, SE = .04) or allyship intentions (b = .04, SE = .04), therefore, hypothesis 2 was not supported. Similarly, hypothesis 3’s proposal that the interaction between risk tolerance and prosocial tendencies would positively affect allyship was not significant for allyship endorsement (b = .01, SE = .03) or allyship intentions (b = .01, SE = .03). Only a small proportion of the variance was explained in both models. For allyship endorsement, there was no change in R2 between the model with just the predictors (R2 = .06, F(4, 366) = 6.11, p < .05) and the model that added the interaction term (R2 = .06, F(5, 365) = 4.89, p < .05); similarly, no change in R2 was observed in allyship intentions before the inclusion of the 37 interaction term (R2 = .12, F(4, 279) = 9.58, p < .05) and after its addition (R2 = .12, F(5, 278) = 7.67, p < .05). Therefore, hypothesis 3 was not supported. Figures 2 and 3 depict the interactions for allyship endorsement and allyship intentions, respectively. Table 3 Regression Results for Allyship Intentions Variable Step 1 Gendera Raceb Step 2 Gendera Raceb Prosocial tendencies Risk tolerance Step 3 Gendera Raceb Prosocial tendencies Risk tolerance Prosocial tendencies x risk tolerance b -.12 .13 -.18 .17 .20 .04 -.17 .17 .20 .04 .01 SE .08 .09 .07 .08 .04 .04 .07 .08 .04 .04 .03 β R2 -.09 .09 -.14* .12* .30** .06 -.14* .12* .30** .06 .02 .02 .12** .12** Note: aGender: 1 = male, 0 = female and other. bRace: 1 = White, 0 = other. *p < 0.05, **p < 0.01. Following recommendations from Carlson and Wu (2012), control variables should be both theoretically and statistically relevant in order to justify inclusion. Despite a theoretical rationale for the inclusion of gender and race, race was not significantly correlated to any of the variables in the model. Analyses were re-run excluding race, but the pattern of results did not change; results are in Appendix B. 38 Figure 2 The Moderating Effect of Prosocial Tendencies and Risk Tolerance on Allyship Endorsement Note: The figure depicts a nonsignificant interaction between prosocial tendencies and risk tolerance on the endorsement of allyship ideologies. Figure 3 The Moderating Effect of Prosocial Tendencies and Risk Tolerance on Allyship Intentions Note: The figure depicts a nonsignificant interaction between prosocial tendencies and risk tolerance on the behavioral enactments allyship on behalf of the target of discrimination. 39 DISCUSSION The purpose of this study was to investigate whether individuals’ prosocial tendencies and tolerance to risk impacts their decisions to engage in allyship. The results were mixed. There was a clear positive relationship between prosocial tendencies and allyship, both when allyship was construed as an ideology to be endorsed and when allyship was construed as behavioral intentions to support a target of discrimination. Contrary to the hypotheses, the results indicated that there was no significant relationship between risk tolerance and allyship, and risk tolerance did not significantly moderate the relationship between prosocial tendencies and allyship. Below the potential implications of these results are discussed. Prosocial Tendencies and Allyship The literature on allyship does not formally specify prosocial tendencies as a necessary antecedent to allyship, nor does it characterize allyship as a type of prosocial behavior. Yet these literatures—while distinct—overlap in several ways. Prosocial behaviors are socially valued, provide voluntary assistance, and cultivate and maintain the well-being of others (Dovidio, 1984; McNeely & Meglino, 1994). While allyship is not explicitly defined as such, and does not specify behavior along these criteria, the way allyship is described aligns with conceptualizations of prosociality. As allyship is the participation in social change movements that advance the rights and improve the conditions of marginalized populations, and is suggested as a way to decrease discrimination and increase inclusivity, it is inherently prosocial in nature (Washington & Evans, 1991). Further, allyship and prosociality construe behavioral influences (e.g., egoistic vs. altruistic motivations) similarly, indicating that allyship and prosocial behavior may share sources of motivation and that these sources may have similar effects on discretionary support behaviors. The results of this study demonstrate that there is a relationship between prosociality 40 and allyship. Prosocial tendencies were positively related to both allyship endorsement and allyship intentions; allyship endorsement captured participants’ attitudes about allyship, whereas allyship intentions captured participants’ indications that they would respond to the discriminatory event in the vignette by supporting the target of discrimination. Observing this relationship in both measures of allyship suggests that prosociality may be important for allyship both ideologically and behaviorally. Accordingly, the literature on prosocial behaviors can contribute to current perspectives of allyship. There is a vast literature on what factors influence prosocial and helping behaviors. Dispositional factors like job satisfaction, empathy, concern for others, and personality, namely conscientiousness, agreeableness, and extraversion, are positively related to interpersonal helping (King et al., 2005; McNeely & Meglino, 1994). Empathy and concern for others are variables considered in antecedents for allyship (Erksine & Bilimoria, 2019), but other dispositional factors in prosocial helping have yet to be explored and can inform how to engender allyship in workplace settings. Prosocial helping behaviors are also impacted by situational factors like reward equity, recognition, and expected reciprocity, which in addition to affect and moral reasoning, reflect the social exchange perspective of helping behavior antecedents (Deckop et al., 2003). The allyship literature has predominantly focused on dispositional factors, which is potentially attributable to the stipulation that allyship should be altruistically motivated (Radke et al., 2020). However, though work on prosocial behavioral motivations has debated whether altruism is important, prosocial behavior does not require an altruistic motivation and highlights the importance of social factors on the enactment of prosocial behavior (Pfattheicher et al., 2022; Simpson & Willer, 2015); accordingly, the social exchange perspective in the prosocial literature can inform what situational factors are likely to impact allyship, especially within the context of 41 organizations. As current perspectives on allyship have primarily focused on what engenders allyship, approaching the study of allyship from a social exchange perspective affords the opportunity to advance this study’s guiding research question. This study sought to examine what factors deter engagement in allyship by considering the potential interfering role of interpersonal risk, but the situational factors proposed by social exchange theory that affect prosocial behavior may also impact allyship. A noted situational factor is norms for reciprocity within a group or organization. This, in conjunction with assertions that the benefits of helping behaviors are more likely to emerge from collective behavior, rather than isolated individual behavior, indicates a need to consider how characteristics of one’s work group impact the enactment of helping behaviors (Bommer et al., 2007). As argued in this paper, factors of the social environment are expected to impact the enactment of allyship and the efficacy of allyship’s purported outcomes (e.g., creating inclusive environments); thus, team-level influences must be considered. When considering antecedents of helping behaviors in teams, team diversity in age, tenure, hierarchical status, and extraversion were positively related to team helping, whereas diversity in gender, education, conscientiousness, agreeableness, and openness were negatively related to team helping (Liang et al., 2015; Choi, 2009). The social identity and self- categorization perspective has been used in team investigations of prosocial behavior to suggest that similarities in dispositional factors like surface-level (i.e., demographic characteristics) and deep-level similarities (i.e., personality, values) will lead to increased cooperation and helping, but only in the case of in-group relations. However, in prosocial team helping, it is evident that certain surface-level and deep-level traits impact team outcomes differently, given team helping is decreased by gender diversity, but increased by age diversity. In applying the social identity and self-categorization theoretical perspective to team-level allyship, the influence of one’s in- 42 group categorization on behavior is also likely to be complex. For instance, in-group affiliation can be transcended by highly salient morals and values, and allyship developmental processes suggest advantaged group members distance themselves from their in-group as they unpack their privilege; on the other hand, in-group affiliation can emphasized if individuals want to amplify their in-group’s status, and when individuals are forced to reckon with the role they play in systemic oppression (Edwards, 2006; Radke et al., 2020). Situational factors are also likely to impact social identity and self-categorizations processes; in team-level prosociality, characteristics of one’s leader, cooperative group norms, group cohesion, as well as less disparity in the amount of helping between members were positively related to group-level helping (Choi, 2009; Ng & Van Dyne, 2005). Following the assertion that collective behavior is necessary to attain the espoused benefits of helping behaviors, it is important to consider how the surface-level attributes (i.e., demographic differences), deep-level traits (i.e., personality, values), and team-level characteristics (i.e., group norms) interact in group settings and impact allyship. Given extant research on allyship favors examining allyship through the lens of individual allies’ surface-level and deep-level characteristics, the antecedents and theoretical rationale suggested by the prosocial tendencies literature can contribute to understanding how to cultivate allyship at both an individual and group level, but also provide a starting point to advance the understanding what demotivates allyship and what factors may impede its emergence as a collective behavior, specifically as it applies to allyship in the workplace. Risk Tolerance and Allyship Prosocial behaviors are associated with varying degrees of cost, due to the expenditure of personal resources and the requirement of moral courage (Kayser et al., 2010; Zhang & Epley, 43 2009). When engaging in prosocial behavior, individuals are aware of what a potential behavior is likely to cost them—yet there are instances where the cost in unknown (Do et al., 2017). As discussed in this paper, behaviors where costs (i.e., negative outcomes) are unknown are classified as risky (Holton, 2004). Accordingly, individuals’ tolerance to risk was expected to impact allyship because allyship is a behavior with associated social costs that have uncertain and variable consequences. Indeed, prosocial risk-taking theory suggests that prosocial tendencies and risk tolerance together precede prosocial behaviors that have unknown social costs (Do et al., 2017). Nonetheless, the results of this study found no significant relationship when regressing tolerance to risk onto allyship, both when allyship was construed as an endorsement of allyship ideologies and when it constituted behavioral intentions to enact allyship. There was, however, a significant correlation between risk tolerance and allyship intentions, but not with allyship endorsement, which provides some tentative evidence that risk may be relevant to behavioral enactments of allyship and not to ideological endorsements of allyship. The nonsignificant relationship between risk and allyship endorsement is likely attributable to the endorsement of allyship ideals predominantly occurring outside a social environment. Only when describing interactional allyship behavior does the mention of social costs emerge. The literature acknowledges that the learning and development processes allies undergo are impacted by external factors, but largely describes these processes insularly and discusses potential negative outcomes as autogenic (i.e., feeling guilty or ashamed for unearned privilege). Thus, unless communicated publicly, costs for privately endorsing allyship ideologies are largely emotional. Prosocial risk-taking theory notes that social costs are more salient than emotional or physical costs when assessing risk, which potentially explains why risk tolerance is 44 important for intentions to engage in allyship behaviors, but not for endorsing allyship ideologies (Do et al., 2017). Though further research is necessary, as it applies to understanding why individuals are demotivated from engaging in allyship, these results suggest that risk may not be an influential factor when examining allyship outcomes that do not take place in a social environment. This is potentially encouraging, as it suggests that the threat of social costs may not affect individuals’ willingness to engage in early stages of allyship development, where behaviors are private, which can inform conceptualizations of where in the lifecycle of allyship development demotivation occurs. Despite a theoretical rationale for the importance of risk in allyship behavior, the results were nonsignificant. There are several factors that may contribute to explaining why the hypothesized relationships were not observed. Firstly, although the selected vignette has been found to successfully depict gender discrimination (see Basford et al., 2014), a manipulation check to assess whether participants perceived threats of social costs was not included; thus, it is unclear if participants perceived risk in the vignette. The vignette was written to include the presence of a supervisor and situated the gender discrimination incident within the context of a team meeting in order to evoke perceptions of risk; being in the presence of peers and interacting with a supervisor are theorized to result in an emotionally salient environment for perceiving risk, as one is exposed to feedback that may elevate or derogate one’s social standing (Do et al., 2017; Shou & Olney, 2022). Though the social environment in the vignette was intended to evoke risk, having an audience has been shown to have complex effects on both risk assessment and intentions to engage in prosocial interventions. The presence of others can impede the enactment of support behaviors due to a fear of retaliation, diffusion of responsibility, or pluralistic ignorance, and the composition of a group can also impact individuals’ willingness to 45 engage in prosocial risk (Fischer et al., 2011; Do et al., 2017). Thus, features of the situation may result in risk being evaluated differently, indicating behavior may be impacted differently depending on the source. It was unclear who in the vignette individuals were deriving risk from, whether it be from the target of discrimination, a bystander in the social environment, the initiator of discrimination, or some combination of these actors. The allyship literature suggests that social costs can come from anyone in the environment, as advantaged group members may react defensively if allyship behaviors cause them to feel bad and disadvantaged group members may react negatively if they view the allyship behavior as ineffective or believe an ally has selfish motives (Salter & Miglaccio, 2019; Radke et al., 2020). Accordingly, the saliency and source of risk are likely instrumental in how conceptualizations of social costs are formed and factored into decisions to engage in allyship. In order to understand how risk might exist as a potential deterrent for allyship, it is relevant to consider what impacts how individuals conceive social costs. Risk has historically been examined by looking at how situational affordances result in differences in individual risk-taking behavior (Byrnes et al., 1999). The literature does note that there are differences in dispositional factors of risk-takers. Individual differences in risk-taking usually consider individuals’ tolerance to ambiguity, sensitivity to reward, and impulsivity, but prosocial risk-takers differ from other kinds of risk-takers (e.g., antisocial risk-takers) in their motives and behavior; they are less likely to be driven by sensation seeking (i.e., need for thrill or adventure), sensitivity to reward (i.e., the drive to achieve rewards), sensitivity to punishment (i.e., the drive to avoid punishment), and emotionality, and are higher in empathy, moral reasoning, self-control, and self-regulation (Levenson, 1990; Fryt & Szczygiel, 2021; Do et al., 2017; Armstrong-Carter et al., 2023; Zlatev et al., 2020). As prosocial risk-takers are high in 46 prosocial tendencies, it is understandable that they share traits associated with prosociality (e.g., empathy) and are not selfishly motivated (e.g., sensation seeking). As it applies to risk in interpersonal settings, self-esteem, trust, and interdependence are noted influences (Cavallo et al., 2013; Harris & Orth, 2020). Though these dispositional factors are expected to impact whether individuals engage in risk, the risk literature notes that characteristics of a situation may evoke different behaviors, and thus, individuals must evaluate the potential costs and rewards afforded by the situation (Mishra et al., 2017). This suggests that in order to understand how risk may be important for allyship, it is important to consider more than just individual differences and situational characteristics, but rather how these factors interact to impact decision-making. This study viewed risky decision making through the lens of risk regulation theory, which views risk within the context of interpersonal (usually romantic) relationships. This perspective posits that individuals are faced with a motivational dilemma when confronted with risk, as they must either protect themselves from negative outcomes (i.e., costs) or expose themselves to positive outcomes (i.e., rewards); the basis of decision making from the risk regulation perspective lies in perceptions of another’s regard and subsequent evaluations of how damaging experiencing a negative reaction would be (Murray et al., 2006). Thus, risk regulation defines the saliency of risk through expectations of a counterpart’s reaction and defines costs as a negative effect to an interpersonal relationship. In doing so, risk regulation predominantly considers the impact of situational affordances by way of changes to the interpersonal dynamics of a relationship. As discussed above, individuals could perceive risk from the instigator of discrimination, the target, or bystanders in the vignette. Risk regulation would suggest that risk evaluation, and subsequent definitions of cost, would depend on individual assessments of counterpart regard with each actor in the social environment. Yet, this perspective does not 47 clearly delineate how these dyadic risk evaluations would factor into overall behavioral decision- making. While it is likely the interpersonal dynamic an ally has with other actors in the social environment plays a role in how individuals are both defining and evaluating social costs for allyship, it is possible the focus on counterpart regard is more appropriate for assessing allyship risk in a in a single dyad (e.g., the relationship between an ally and the target of discrimination), and is not sufficient for understanding how individuals make attributions about risk in group settings. An alternative approach to characterize how social costs are conceptualized and impact behavior comes from the relative state model, which, like many risk theories, suggests that risky decisions are made by maximizing the potential for rewards and minimizing the potential for costs. However, this model posits that these cost/reward decisions vary based on an individual’s relative state, which is one’s competitive advantage or competitive disadvantage compared to others in a social environment (Mishra et al., 2017). Competitive advantage is determined through both socio-environmental (e.g., organizational climate) and individual difference factors (e.g., personality), and individuals tend to take risks in alignment with their competitive advantage as it maximizes their chances of reward. Thus, in decisions to engage in allyship, the relative state model suggests that individuals survey the social environment and ascertain whether they have a competitive advantage before making decisions about engaging in allyship. For instance, perhaps in the presence of subordinates, an organizational leader has competitive advantage due to socio-environmental factors (e.g., formally afforded power, inherent social capital) and individual differences factors (e.g., risk tolerance, prosocial tendencies), and thus, is more likely to engage in allyship because the threat of social costs is mitigated by their competitive advantage. This same leader may experience a change in competitive advantage in a 48 different situation; for example, in the presence of their supervisor, where their formally afforded power is diminished. Approaching the understanding of risk in allyship from this perspective allows for the inclusion of multiple factors of interest and expands on the decision-making process proposed by risk regulation. Further, it may provide some insight into how situational affordances interact with individual differences to determine an individuals’ competitive advantage, or competitive disadvantage, which can inform what factors motivate individuals against risk, thereby addressing the primary research question of this study. Contributions, Limitations, and Future Directions The results of this study suggest that prosocial tendencies are important for allyship, both conceptually and behaviorally. As it applies to cultivating sustained allyship behaviors, the results of this study point to prosocial motivations as a potential way to engender the desired benefits of allyship. In finding support that there is a relationship between prosociality and allyship behaviors, future research can explore how drivers and mechanisms of prosociality can be applied to understanding allyship in the workplace. This study also found a positive correlation between prosocial behavior and risk. As prosocial tendencies are related to risk tolerance, future research can explore how these traits interact to affect prosocial risk behavior at work, specifically as it applies to the type of allyship (e.g., public vs. private allyship) individuals employ and who an ally is willing to direct allyship towards (e.g., target of discrimination vs. instigator of discrimination). The results of this study suggest that for organizations seeking to create climates of inclusion and anti-discrimination, encouraging prosocial behavior may be instrumental. Recent research has suggested that prosocial tendencies may impact one’s ability to tolerate social risk overtime (Armstrong-Carter et al., 2023); thus, placing value on prosocial 49 behavior at work (e.g., organizational citizenship behaviors) may encourage prosocial behaviors that carry social risk. This study had several limitations. First, between-person designs decontextualize response interpretation because there is no way to characterize within-person response patterns, and as such, it is difficult to assess whether responses reflect the true judgement of respondents; a mixed design may be better suited to observing the effects of interest (Aguinis & Bradley, 2014). This is especially relevant given the scales for allyship endorsement and allyship intentions both had ceiling effects. As allyship is a socially desirable behavior and individuals are observed as engaging in it to enhance their reputation (i.e., performative allyship), it is likely that social desirability played a role in participant responses (Kutlaca & Radke, 2023). Social desirability response bias does tend to be particularly impactful in self-report data, which suggests it is possible that regardless of an individuals’ true level of tolerance to risk or prosocial tendencies, they responded in a socially desirable fashion and indicated that they endorsed allyship and would enact allyship for the target of discrimination (Bernardi & Nash, 2022). Though performative allyship and self-interested motives for allyship consider the role of social desirability, it is unclear how this relates to risky situations where prosocial behavior occurs. Engaging in workplace helping behaviors can be attributed to both prosocial motivations and impression management motivations (Grant & Mayer, 2009); yet, engaging in helping behaviors to impression manage can be taxing and be viewed unfavorably (Eissa & Lester, 2018; Halbesleben et al., 2010). Future research should consider how the perception of risk impacts the relationship between impression management (i.e., social desirability) and allyship behavior. Given the null results for risk tolerance, it is possible that risk was not effectively made salient by a vignette, as the derivation of social costs in a simulated scenario might not 50 adequately impact behavior; Vignette methodology is often critiqued due to the inability to capture reality (Rungtusanatham et al., 2011; Wilson & White, 1998). This study did not employ manipulation checks, it is difficult to assess exactly what reality individuals were experiencing. Although the selected vignette has been found to successfully depict gender discrimination (see Basford et al., 2014), perceptions of discrimination were not assessed, and thus, it is possible participants did not perceive any discrimination occurring in the vignette. As the perceiving a need to intervene is often cited as a prerequisite to enacting support behaviors, both in the allyship literature and bystander intervention literature, failing to perceive discrimination would result in no cue to enact allyship (Hebl et al., 2020; Fischer et al., 2011). If individuals did not recognize a need to confront discrimination, it is possible they perceived no risk in the scenario. There was not a manipulation check for perceiving risk, which makes it difficult to assess if and from whom participants perceived risk in the vignette, and how they incorporated these evaluations into their decisions to engage in allyship. By isolating who in a social environment individuals perceive risk from, it is possible to examine relational characteristics that may impact allyship. For instance, positive evaluations of interdependence in a relationship have been found to positively impact individuals’ prosocial behavior broadly, organizational citizenship at work, and their tolerance to risk (Podsakoff et al., 1997; Penner et al., 2003; Cavallo et al., 2013); this indicates that the degree of interdependence between individuals may be important for understanding how perceptions of interpersonal risk impact behavior. Finally, the allyship intentions scale only captured public allyship behavior, as items referred to whether participants would be a “visible ally” or stand up for the target of discrimination at work (Fletcher & Marvell, 2023). As Radke et al. (2020) note, allyship can take public and private forms, and thus, the scale used failed to capture allyship that is not publicly 51 enacted. Generally, conceptualizations of allyship behavior tend to favor public and confrontational responses to discrimination. While allyship tends to be construed as an activist form of intergroup prosociality, it is possible that allyship can also take the form of intergroup benevolence, wherein allies provide support (e.g., listening, affirmation, compassion) directly to those impacted by discrimination (Louis et al., 2019). Accordingly, it is relevant to consider that there are a variety of behaviors an ally can enact when responding to discrimination, and this is not limited to just public and confrontational responses. Further, as behaviors may vary on the spectrum of private to public, or non-confrontational to confrontational, it is also likely that different behaviors accrue different threats of social cost. For instance, directly confronting an instigator of discrimination may be evaluated as high-risk, whereas individually comforting a target of discrimination may be evaluated as lower in risk. Additionally, as this paper has argued the importance of the social environment, it would be important to consider what contextual factors influence individuals’ change in risk tolerance; for example, if an ally is typically willing to engage in a medium-risk allyship behavior (e.g., reporting to a supervisor), what factors may be important for motivating engagement in a higher risk behavior (e.g., confronting an instigator) as opposed to a lower risk behavior (e.g., direct interpersonal benevolence). Resultingly, future research should investigate what behavioral responses individuals take when faced with discrimination in the workplace and how individuals discern differing degrees of social cost from these behaviors. 52 CONCLUSION This study sought to examine why individuals may be demotivated from engaging in allyship. As allyship is a prosocial behavior that has inherent associated social costs, it was expected that prosocial tendencies and tolerance and risk would positively relate to allyship. The results indicated that prosocial tendencies are predictive of allyship, both when construed as an endorsement of allyship ideologies and when construed as an intention to support a target of discrimination. Accordingly, prosocial tendencies are likely to be important for allyship ideologically and behaviorally, and thus, may be a relevant avenue to advance allyship theory and practices for engendering allyship. Risk tolerance was not found to predict allyship endorsement or allyship intentions, but it was significantly correlated with allyship intentions and with prosocial tendencies, suggesting that being tolerant to risk may be relevant to understanding prosociality and behavioral enactments of allyship. Given null fundings for the relationship between risk tolerance and allyship, future research should consider how affordances of the risky situation (i.e., the allyship dilemma) and individual difference variables (e.g., prosocial tendencies, risk tolerance) interact to impact behavioral enactments of allyship, with consideration given to the varying degrees of risk present in different behavioral representations of allyship. 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As the team files into the conference room, John says, “The team as a whole received positive ratings, however, we struggle with being innovative in the way we do business.” Andrea, a senior research associate, offers some insight and suggestions based on her experience at her previous firm on how to address some of the roadblocks the team faces. Following Andrea, several other people offer their thoughts as well. Finally, another research associate Thomas provides exactly the same idea as Andrea originally did. John thanks Thomas for sharing his ideas and asks him to draft further details on the suggestion to pass along to senior management. Note: Participants were instructed to envision themselves in a work meeting where this scenario was taking place. Table A2 Prosocial Tendencies Measure 1. I can help others best when people are watching me 2. It makes me feel good when I can comfort someone who is very upset 3. When other people are around, it is easier for me to help others in need 4. I think that one of the best things about helping others is that it makes me look good 5. I get the most out of helping other when it is done in front of other people 6. I tend to help people who are in real crisis or need 7. When people ask me to help them, I don’t hesitate 8. I prefer to donate money without anyone knowing 9. I tend to help people who are hurt badly 10. I believe that donating goods or money works best when I get some benefit 11. I tend to help others in need when they do not know who helped them 12. I tend to help other especially when they are really emotional 13. Helping others when I am being watched is when I work best 14. It is easy for me to help others when they are in a bad situation 15. Most of the time, I help others when they do not know who helped them 16. I believe I should receive more rewards for the time and energy I spend on volunteering 17. I respond to helping others best when the situation is highly emotional 18. I never wait to help others when they ask for it 19. I think that helping others without them knowing is the best type of situation 20. One of the best things about doing charity work is that it looks good on my resume 21. Emotional situations make me want to help others in need 22. I often make donations without anyone knowing because they make me feel good 23. I feel that if I help someone, they should help me in the future 24. I often help even if I don’t think I will get anything out of helping 25. I usually help other when they are very upset Note: Items from Carlo et al. (2003); rated from 1 (strongly agree) to 5 (strongly disagree). 65 Table A3 Risk Tolerance Measure 1. Talking about a sensitive topic with someone when there is a risk that the person may react badly 2. Disagreeing on a major issue with someone of a higher social status when there is a risk that the person may be offended 3. Speaking your mind on an issue in front of coworkers during a meeting when there is a risk that your opinion may be unpopular 4. Asking your supervisor a question in front of others when there is a risk that others may think of you negatively 5. Admitting that your tastes are different from your friend, when there is a risk that your friend may react badly 6. Telling your supervisor about your ideas for improvements when there is a risk that they may have a negative reaction to your ideas Note: Items from the social subscale of the MDRT (Shou & Olney, 2022); rated from 1 (very likely) to 5 (very unlikely). Table A4 Allyship Endorsement Measure 1. I believe people from these groups face different types of structural barriers (i.e., social, economic, and cultural barriers) that contribute to their disadvantage 2. I believe people from these groups are treated in different discriminatory ways by the dominant culture (i.e., White, able-bodied, cis-gendered, and heterosexual-identifying people and institution) in this country 3. It is important to me that I know more about historical and contemporary issues affecting people from these groups 4. It is important to me that I express solidarity with these different groups in their struggle for greater representation, equal treatment, and non-stereotyping 5. When I see people from these groups being treated unfairly, I stand up for them 6. If I find that in a meeting, some of my coworkers engage in jokes that are disrespectful to these groups, I bring it to the attention of my coworkers, even though I know I may be disliked for it Note: Items from Gates et al. (2021); rated from 1 (strongly agree) to 5 (strongly disagree). Participants were provided the following instructions: “In the United States, certain groups of people face more oppression than others. Specifically, individuals who are: non-White (i.e., people of color), belong to the LGBTQ+ community, non- cisgendered (e.g., transgendered, nonbinary, etc.), or disabled. With these groups in mind, please indicate how much you agree with each statement.” Table A5 Ally Intentions Measure 1. I would stand up for this person to others in my organization 2. At work, I would give my full support to this person 3. I would be a visible ally to this person in my organization Note: Items from Fletcher & Marvel (2023); rated from 1 (strongly agree) to 5 (strongly disagree). 66 APPENDIX B: SUPPLEMENTARY ANALYSES Table B1 Regression Results for Allyship Endorsement Without Race as a Control Variable Step 1 Gendera Gendera Prosocial tendencies Risk tolerance Step 2 Step 3 Gendera Prosocial tendencies Risk tolerance Prosocial tendencies x risk tolerance Note: aGender: 1 = male, 0 = female and other. *p < 0.05, **p < 0.01. b -.12 -.16 .18 .00 -.16 .18 .01 .01 SE .08 .08 .04 .04 .08 .04 .04 .03 Table B2 Regression Results for Allyship Intentions Without Race as a Control b -.12 -.17 .19 .05 -.17 .19 .05 .02 SE .08 .07 .04 .04 .07 .04 .04 .03 Variable Step 1 Gendera Gendera Prosocial tendencies Risk tolerance Step 2 Step 3 Gendera Prosocial tendencies Risk tolerance Prosocial tendencies x risk tolerance Note: aGender: 1 = male, 0 = female and other. *p < 0.05, **p < 0.01. 67 β R2 -.08 -.11* .24** .00 -.11* .24** .01 .01 .01 .06** .06** β R2 -.09 -.14* .29** .07 -.14* .29** .07 .03 .01 .11** .11**