At the Heart of a Conflict

Abstract

Value-based conflicts are prone to escalation and rather insensitive to standard conflict resolution techniques. To understand why this is the case, we assessed self-regulatory and cardiovascular (CV) responses to test how people cope with conflict, depending on whether values versus resources are at stake. Our results show that a value conflict induces a CV threat profile and raises a prevention focus. Conversely, a resource conflict induces a CV challenge profile and decreases prevention focus. These results suggest that value conflicts are linked to more prevention-focused motivational profiles than resource conflicts. This knowledge can foster the development of specific strategies to facilitate resolution of value conflicts.

Keywords

cardiovascular response threat morality interpersonal conflict regulatory focus

Many conflicts are not just about the division of scarce resources such as money, oil, or land. Often they refer to moral values—who is wrong and who is right—for example, when people adhere to different religious or political systems. It is crucial to resolve those conflicts in order to keep (global) communities safe and stable. Unfortunately, most conflict resolution techniques—such as negotiation—have been developed to resolve resource conflicts and cannot easily be applied to value conflicts, while resolution techniques for value conflicts have largely escaped academic attention. As a first step toward developing conflict resolution techniques that target value conflicts, we compare the motivational states and coping strategies raised by conflicts referring to values versus resources. We argue that people feel more threatened in value conflicts compared to resource conflicts, and show that this affects cardiovascular (CV) responses as well as the adoption of self-regulation strategies.

Values Versus Resources

Previous research has established that there are important differences between value conflicts and resource conflicts (Harinck & De Dreu, 2004; Harinck, De Dreu, & Van Vianen, 2000; Harinck & Van Kleef, 2012; Kouzakova, Ellemers, Harinck, & Scheepers, 2012; Wade-Benzoni et al., 2002). Value conflicts emerge when parties disagree on normative convictions about what is right or just in a particular situation. When people have conflicting values they differ in their beliefs about the best way to behave toward others, have different notions of justice, or hold different convictions about what is morally right or wrong. Resource conflicts emerge when parties disagree about the allocation of scarce resources, for instance, about how to distribute time, money, space, or valuable goods between them (De Dreu, 2010; Pruitt & Carnevale, 1993).

In general, value-based conflicts are harder to resolve than conflicts about scarce resources (Cohen et al., 2007; Harinck & De Dreu, 2004; Harinck et al., 2000; Harinck & Van Kleef, 2012; Kouzakova et al., 2012; Tetlock, 2003; Tetlock, Kristel, Elson, Green, & Lerner, 2000; Wade-Benzoni et al., 2002). An important reason why this is the case is that value conflicts tend to be taken more personally than resource conflicts (Harinck & Van Kleef, 2012; Kouzakova et al., 2012). That is, a value conflict implies that the validity of one’s personal norms and values is questioned by another party. By contrast, in resource conflicts, the disagreement is about some commodity (e.g., space, money) external to the self. As a result, in value conflicts more than in resource conflicts the individual’s identity is at stake. Thus, for parties in a value conflict, maintaining and defending their position is a way to validate and protect their identity—in addition to their preferred outcome (Cohen et al., 2007). Accordingly, Kouzakova, Ellemers, Harinck, and Scheepers (2012) revealed that people experience more self-involvement and perceive less common ground with their opponent in a conflict situation when the opposing positions are explained by referring to different values, rather than indicating disagreement over the distribution of scarce resources. Furthermore, Harinck and Van Kleef (2012) showed that when people face an angry counterpart, they tend to give a more defensive reaction in a value conflict than in a resource conflict. When the other party in a value conflict expresses anger, people remain more firm in their position, become angrier themselves, and are less willing to yield than when anger is expressed in a resource conflict (Harinck & Van Kleef, 2012).

A second—and related—reason is that a number of behaviors and strategies known to be effective in the resolution of resource conflicts are considered less acceptable as a way to handle value conflicts. Whereas people are inclined to compromise, yield, or trade-off as a way to deal with resource conflicts, they are reluctant to engage in such strategies when their core values are at stake (Harinck & De Dreu, 2004; Harinck et al., 2000; Tetlock et al., 2000; Wade-Benzoni et al., 2002). Giving in or trading off on one’s personal principles or values is considered unacceptable. More generally, it is very difficult for people to compromise on what they consider good or bad, or on core values that are central to their sense of self and identity. Tetlock, Kristel, Elson, Green, and Lerner (2000) have noted that people may see such values as “sacred,” and demonstrated that the consideration of trade-offs on such core values raises moral outrage. Harinck, De Dreu, and Van Vianen (2000) observed that people reach lower joint outcomes in value-based negotiations compared to resource-based negotiations due to their lower level of logrolling (trading of less important issues for more important issues). Likewise, whereas Harinck and De Dreu (2008) showed that people can switch to a more cooperative, integrative negotiation style during breaks in negotiations, these benefits of negotiation breaks do not extend to value-based negotiations, because the more integrative or yielding style is considered less feasible or acceptable in value-based negotiations than in resource-based organizations.

In practice, many conflicts are “mixed” in that the resources they involve can also be used to support important values (e.g., Druckman, Broome, & Korper, 1988; Druckman & Zechmeister, 1970). Nevertheless, Druckman and colleagues also noted that conflicts are harder to solve when values are intertwined with resources (e.g., when people have value-related preferences about the division of a monetary budget). Our current aim is to assess how people respond to conflicts depending on whether resources or values are at stake. This can only be established when these different underlying concerns are separated. We do so in the present research by comparing responses to the same conflict issue, while we induce participants to think of the underlying reasons for their opposing positions either as stemming from diverging values or from diverging preferences about a scarce resource (see Kouzakova et al., 2012, for a similar methodology).

Value Conflict as Identity Threat

Our central hypothesis is that value conflicts are more self-threatening than resource conflicts. When others advocate different (moral) values, this can easily be seen as calling into question the validity or appropriateness of one’s own values (Branscombe, Schmitt, & Harvey, 1999; Byrne et al., 1971; Effron, Miller, & Monin, 2012; Hornsey, Oppes, & Svenson, 2002; Shalvi, Handgraaf, & De Dreu, 2011). Holding an opposing position in a value conflict thus may challenge the core of one’s identity, as it can be seen to undermine one’s personal integrity (Aquino & Reed, 2002; Cohen et al., 2007; Ellemers, 2001; Scheepers & Ellemers, 2005; Skitka, Bauman, & Sargis, 2005). Thus, especially when norms or values central to someone’s sense of self are at stake, this is likely to be experienced as a threat to one’s identity. This is the case, first, because accepting information (or seeing as reasonable an alternative position) that disconfirms the validity of one’s own values would also imply having to adapt one’s view of the self as being a good and reasonable person (Cohen et al., 2007). Indeed, people may fear they need to compromise or yield values important to them to be able to resolve a value conflict, making the disagreement more threatening for their moral self-evaluation than in the case of a resource conflict (Tetlock et al., 2000). Second, acceptance of identity-challenging information or alternative value positions may incur additional social costs, when this results in rejection by others who share the same identity-defining values, or exclusion from groups that are important to the self (Ellemers & Van den Bos, 2012).

We tested this prediction by assessing two different indicators of threat, namely CV measurements and self-regulation strategies. First, based on the biopsychosocial model of arousal regulation (Blascovich & Mendes, 2010), we distinguish between a threat motivational state (resulting from the evaluation that one has insufficient resources to deal with the demands of a situation) and a challenge motivational state (resulting from the evaluation that one has the resources to deal with the situation; Blascovich & Mendes, 2010; Blascovich & Tomaka, 1996). Such differences in perceived coping ability are marked by specific changes in CV responses. A motivational state of threat is indicated by low cardiac output (CO) and high vascular resistance (total peripheral resistance [TPR]), whereas a motivational state of challenge is indicated by high CO and low vascular resistance (Blascovich & Mendes, 2010; Blascovich & Tomaka, 1996). Thus, we expect people in a value conflict to show a stronger CV threat profile compared to people in a resource conflict (Hypothesis 1).

Second, in terms of self-regulation, regulatory focus theory (Higgins, 1997, 1998) distinguishes between two types of goals—safety and security on one hand and attainment and growth on the other (Liberman, Idson, Camacho, & Higgins, 1999). The goal of safety and security is related to a prevention focus in which people guard against loss. While there are individual differences in people’s chronic promotion or prevention orientations, situational features (such as task characteristics) can also enhance the temporary salience of promotion goals or prevention goals (Higgins, 1997; see also Crowe & Higgins, 1997; Förster, Higgins, & Idson, 1998). People in a prevention focus aim to avoid undesired end states and are highly sensitive to the absence and presence of negative outcomes (Liberman et al., 1999). The goal of attainment and growth is related to a promotion focus in which people aim to reach desirable goals. People in a promotion focus try to reach a desired end state—such as the attainment of valuable goods or a valuable position—and are more sensitive to the absence and presence of positive outcomes (Liberman et al., 1999). Prior research has shown that a prevention focus is related to less openness to change (Liberman et al., 1999) and has established that a person’s regulatory focus influences conflict management styles in intimate relationships (Winterheld & Simpson, 2011).

We posit that value conflicts and resource conflicts should make salient different goal-relevant concerns, and as a result, will give rise to different self-regulation strategies. We argued above that a value conflict raises concerns with maintaining—and not losing—one’s moral integrity. People in a value conflict thus mainly aim to prevent that they have to give in on their norms and values, and resist change as a way to avoid compromising their identity. As a result, we expect that a value conflict raises self-regulation strategies related to a prevention focus (Brodscholl, Kober, & Higgins, 2007). By contrast, the primary motivation in a resource conflict relates to the possibility of attaining a desired commodity. Thus, when people engage in a value conflict, this is more likely to raise a prevention focus than when they enter a resource conflict (Hypothesis 2).

Method

Participants and Design

Sixty-four undergraduate students (78% females, mean age = 20) at Leiden University were randomly assigned to one of the two experimental conditions (value conflict [n = 31] vs. resource conflict [n = 33] and received 8 € for participation. Men and women were distributed equally across conditions.

Procedure and Independent Variable

During the experiment, all information, tasks, and manipulations were delivered via computer. Upon arrival, participants were seated in a cubicle where sensors for physiological recording were applied. Then, participants’ CV baseline responses were collected while participants sat quietly for 5 min. Next, we measured participants’ negative emotions to rule out that the two types of conflict differentially affected such emotions. Participants were informed that this experiment studied how people reach a joint decision when they either agree or disagree on a particular topic. Participants were then told that they were randomly coupled with another participant (actually one of the two confederates) together with whom they would complete this experimental session. We had a male and a female student acting as another participant to control for the possible gender effects of the interaction. There was no interaction between the condition and the confederate’s gender on the dependent measures (Fs < 1). All communications from the confederate were prerecorded.

After instructing participants on the usage of webcam, they watched the confederate’s introduction via webcam, after which participants introduced themselves via webcam. Participants were then asked to imagine that they were to travel to a certain vacation destination in Spain together with their interaction partner. While their destination is equally accessible by various travel means (e.g., train, car, airplane), they were to reach a joint decision on air travel as travel means during a face-to-face discussion at the end of the experiment. (In fact, no discussion took place and the experiment ended beforehand.) Next, all participants were asked to express their preference either pro or against air travel. Although the conflict issue remained the same for all participants (air travel), the underlying conflict reasons differed between the conditions. In the value conflict condition, participants were instructed to base their choice on their values (“I find air travel too damaging to the environment to take an air plane to Spain” vs. “I find air travel not too damaging to the environment to take an air plane to Spain”). In the resource conflict condition, participants were instructed to consider their financial interest in making this same decision (“I find air travel too expensive to take an air plane to Spain” vs. “I find air travel not too expensive to take an air plane to Spain”; this methodology was extensively pretested by Kouzakova et al., 2012). After participants made their choice (25.8% in the value conflict condition and 75.8% in the resource conflict condition chose in favor of air travel¹), they received a message that their partner chose an opposite standpoint due to different environmental values or financial interests (depending on condition). The experiment was programmed to appear as if participants could receive each other’s responses in real time. Participants were then given some time to generate at least five arguments in favor of their standpoint. At this point, it was explained that they would exchange these arguments with their partner via webcam ostensibly in preparation for a more extensive face-to-face discussion later on. Participants first watched their partner’s presentation and then presented their arguments via webcam for the maximum of 2 min. During the presentation of their arguments, participants’ CV responses were measured. Subsequently, participants completed self-report measures to assess their self-regulation strategy. Then, participants evaluated their partner’s likability and the conflict situation, as well as their negative emotions (posttest). Finally, after probing participants for hypothesis awareness and assessing their background information, they were thanked, paid, and debriefed. None of the participants had accurately guessed the experimental purpose.

Dependent Variables

Cardiovascular Responses

Impedance cardiographic signals, electrocardiographic signals, and blood pressure were continuously measured during the experiment using a Biopac MP150 system (Biopac Systems Inc., Goleta, CA). Physiological data were stored using Acqknowledge software (Biopac Systems) and scored using AMS-IMP software (Free University, Amsterdam, The Netherlands). In addition to CO and TPR, we measured heart rate (HR) and preejection period (PEP; a measure of ventricular contractility as indicator of activation of the sympathetic nervous system). HR and PEP are functional in identifying the experimental context as a motivated performance situation, which is the domain to which the biopsychosocial model of challenge and threat applies. That is, decreases in PEP and increases in HR mark task engagement, which is a defining feature of motivated performance. Although in initial work on the biopsychosocial model PEP was used to differentiate challenge from threat (in that a shorter PEP was more indicative of challenge, e.g., Blascovich, Mendes, Hunter, Lickel, & Kowai-Bell, 2001), in more recent work the primary function of PEP is marking task engagement (e.g., Blascovich, Seery, Mugridge, Norris, & Weisbuch, 2004). In all formulations of the biopsychosocial model that have been postulated, HR has been described as irrelevant for distinguishing between challenge and threat; rather, HR exclusively functions as an indicator of task engagement.

Self-Regulatory Strategy

We assessed participants’ self-regulation strategies using 9 items adapted from Sassenberg, Jonas, Shah, and Brazy (2007). Specifically, participants responded 9 times to the general question (during the upcoming discussion I shall aim to:…) by placing a cross on a line that represents a continuum between a promotion and prevention-oriented option (e.g., “strive for success” vs. “prevent a failure”). The mean regulatory focus consisted of the average score on the 9 items (Cronbach’s α = .79). The higher score (up to 100) indicated more prevention-focused strategies and a lower score (down to 1) indicated more promotion-focused strategies.

Control Variables

All items were measured on a 7-point scale (1 = not at all to 7 = very much).

Conflict-Type Manipulation Check

We checked the extent to which the conflict descriptions were seen to tap into either diverging values or resources by asking participants to indicate on a single bipolar scale whether the conflict more strongly reflected different financial interests (1) or values (7).

Conflict Intensity Check

In order to ensure that framing the same conflict in terms of values versus resources did not affect perceptions of conflict intensity, we asked participants to judge the extent to which they experienced the situation as a conflict between themselves and the other person.

Interaction Partner’s Likability

We asked participants to indicate how likable, friendly, and warm (Cronbach’s α = .62) they found their interaction partner.

Negative Emotions

Negative emotions such as anger and fear may affect conflict perception and conflict development (Steinel, Van Kleef, & Harinck, 2008; Van Kleef, 2009). To rule out that the two types of conflict differentially affected participants’ negative emotions, we asked participants to indicate how sad, angry, gloomy, and fearful they felt on the pretest (Cronbach’s α = .80) and on the posttest (Cronbach’s α = .82).

Results

Conflict-Type Manipulation Check

Participants in the value conflict condition evaluated the conflict more as a value conflict (M = 4.58, standard deviation [SD] = 1.43) than the participants in the resource conflict condition (M = 3.12, SD = 1.59), F(1, 62) = 14.75, p < .001, η² = .19.

Conflict Intensity Check

As intended, the participants in the value conflict condition (M = 3.65, SD = 1.28) and the participants in the resource conflict condition (M = 3.61, SD = 1.35) evaluated the conflict to be equally intense, F(1, 62) = 0.01, p = .906.

Interaction Partner’s Likability

As intended, the partner’s likability was rated similarly across conditions, F(1, 62) = 0.26, p = .613, with the grand mean around the midpoint of the scale (M = 3.57, SD = 0.85).

Negative Emotions

There were no differences in the extent of participants’ negative emotions on both the pretest, F(1, 62) = 1.40, p = .240, and on the posttest, F(1, 62) = 0.71, p = .404, thus ruling out differential mood as an alternative explanation for observed condition effects.

Dependent Variables

Cardiovascular Response

In preparation for analyses of the CV responses, we first calculated average levels of HR, PEP, CO, and TPR for the last minute of the baseline and the first minute of the speech task (for procedure, see Blascovich et al., 2004; Mendes, Reis, Seery, & Blascovich, 2003). In line with general procedure (Seery, Weisbuch, Hetenyi, & Blascovich, 2010), we calculated reactivity scores by subtracting baseline responses from speech task responses. The resulting reactivity scores are presented in Table 1. There were no univariate outliers (defined as values higher than 3 SDs from the average).

Table 1.

Cardiovascular Reactivity as a Function of Condition.

	Value Conflict			Resource Conflict
	M	SD	n	M	SD	n
Heart rate (HR)	20.38*	16.41	31	16.21*	12.22	33
Preejection period (PEP)	−25.55*	19.70	31	−22.67*	15.12	33
Cardiac output (CO)	0.33	2.18	31	0.66*	0.59	33
Total peripheral resistance (TPR)	−70.68	1175.70	31	−402.11*	998.68	33
Threat–challenge index (TCI)	−0.29	2.05	31	0.23	1.05	33
Reactivity scores controlled for participants’ gender and HR:
CO	0.31	1.82	31	1.01*	1.88	33
TPR	92.66	1271.56	31	−512.13*	1311.94	33
TCI	−.455	1.83	31	.554	1.89	33

Note. Reactivity scores indicated with * differ significantly from 0 (i.e., baseline levels, p < .05). This indicates task engagement in both conditions (i.e., PEP and HR). Moreover, in the resource conflict condition this indicates a significant increase in CO and a decrease in TPR, which represents, in absolute terms, the “challenge” pattern (e.g., Blascovich, Mendes, Hunter, Lickel, & Kowai-Bell, 2001). In the value conflict condition, neither CO nor TPR differed significantly from baseline levels, which represents, in absolute terms, the “threat” pattern.

We first established that the speech task was sufficiently engaging by testing for significant decreases in PEP and increases in HR compared to baseline. In both conditions, PEP decreased (ts > 7.21, ps < .001), while HR increased (ts > 6.90, ps < .001) significantly from baseline levels, indicating task engagement, which is an important prerequisite of further analyses of CV reactivity in terms of challenge and threat motivational states. There were no significant differences between conditions on PEP and HR (Fs < 1.34, ps > .251).

In addition to analyzing CO and TPR separately, we calculated a single threat–challenge index (TCI). In line with common practice, TCI is calculated not only to simplify the analyses, but also because CO and TPR are two related measures of the same SAM (sympatheticadrenomedullary axis) versus PAC (pituitary-adrenocortical axis) activation (Blascovich et al., 2004; Kassam, Koslov, & Mendes, 2009). Moreover, using TCI increases the reliability of the CV measures (De Wit, Scheepers, & Jehn, 2012; Seery et al., 2010). We calculated TCI by converting participants’ CO and TPR scores into z scores, and then subtracting TPR from CO, which means that higher values on the resulting index indicate a stronger challenge motivational state, whereas lower values indicate a stronger threat motivational state (Blascovich et al., 2004).

To test our prediction that a value conflict results in a relatively stronger threat motivational state, whereas a resource conflict results in a relatively stronger challenge motivational state, we subjected the data to a univariate analysis of variance with the conflict condition as factor and CV reactivity as the dependent variable. In addition, in order to control for differences in task engagement (see Seery, Weisbuch, & Blascovich, 2009 for a similar procedure), HR reactivity scores were added as a covariate in the analyses. Moreover, we controlled for gender because of well-documented differences between men and women in CV processes (Allen, Stoney, Owens, & Matthews, 1993; Girdler, Turner, Sherwood, & Light, 1990; Kudielka, Buske-Kirschbaum, Hellhammer, & Kirschbaum, 2004; Whited & Larkin, 2009).

Although we did not find significant differences between the conditions regarding CO and TPR separately (Fs < 3.55, ps > .064), we did find a significant difference between the conditions on the combined TCI, F(1, 59) = 4.77, p = .033, η² = .08. In line with Hypothesis 1, participants in the value conflict condition were relatively more threatened (M = −0.455, SD = 1.83) than participants in the resource conflict condition (M = 0.554, SD = 1.89), who were relatively more challenged.²

Regulatory Focus Motivational Strategy

We examined the effect of conflict condition on the adoption of a particular regulatory focus motivational strategy. In line with Hypothesis 2, participants in the moral conflict condition were more likely to adopt prevention-focused strategies (M = 45.85, SD = 10.69) than participants in the resource conflict condition (M = 39.82, SD = 11.73), F(1, 62) = 4.60, p = .036, η² = .07.³

Discussion

Value conflicts are prone to escalation and are less susceptible to typical conflict resolution techniques such as negotiation and compromising than resource conflicts. Our results present first evidence for the distinct motivational processes raised when conflicts refer to value disagreement. Specifically, we found that a conflict referring to diverging values was more likely to induce a motivational state of threat and to raise a prevention-focused motivation. By contrast, when the conflict referred to divergent preferences about allocation of resources, this was more likely to induce a motivational state of challenge and a decreased focus on prevention of losses.

Theoretical Implications

The present study offers a new perspective on different types of conflict that may inform the development of additional conflict resolution techniques. We argue that affirmation might be a fruitful intervention technique to help people solve their value conflict. Although value conflicts are generally harder to solve than resource conflicts, even in value conflicts, there are circumstances under which people become more flexible and may even accept trade-offs. For example, the present research complements recent findings documenting the effectiveness of self-affirmation (Cohen et al., 2007; Derks, Scheepers, van Laar, & Ellemers, 2011). Cohen et al. (2007) showed that self-affirmation could overcome inflexibility in resource conflict, whereas Derks, Scheepers, van Laar, and Ellemers (2011) revealed that self-affirmation could reduce identity threat. Together, these lines of research suggest that affirmation might be an interesting intervention to use in value conflict.

Prior work of Tetlock and colleagues (Tetlock, 2003; Tetlock et al., 2000) demonstrated that whereas people generally avoid trade-offs in value conflict, they might find them acceptable under certain circumstances. People are generally reluctant to accept trade-offs that pit values against resources—such as saving the life of a patient versus saving 1 million dollar in the hospital budget. However, they are more likely to accept trade-offs when two values are pitted against each other—for example, the importance of saving either patient A’s life or patient B’s life. He noted that reframing the issues at hand might sometimes help overcome resistance to a value trade-off (Tetlock, 2003). These findings are in line with recent research by Rexwinkel, Ellemers, & Harinck (2013). They showed that trade-offs concerning values seemed more acceptable when these were framed as personal preferences rather than as general principles.

Our findings extend recent research by Shalvi, Handgraaf, and De Dreu (2011), which showed that people try to avoid situations in which they potentially could deceive others. Our data suggest that people may avoid situations in which they are tempted to behave immorally because this poses a threat to their self-image as being a morally good person.

These data also complement prior research by De Wit, Scheepers, and Jehn (2012). They showed that CV reactivity was related to rigidity in a joint decision-making task. More specifically, they showed that people with a CV threat response were less likely to adjust their initial point of view in the joint decision-making task. Our research shows that such a threat response, and the related rigidity, is more likely to appear in a value conflict rather than a resource conflict. Thus, when people have different viewpoints in a decision-making task, rigidity may be stronger when these viewpoints are based on values rather than on the attainment of resources.

As mentioned in the introduction, many real-life conflicts are mixed cases of values and resources. In this study, we have disentangled values and resources to study their effects separately. The more a real conflict focuses on either values or resources, the more it will look like one of our experimental conditions, and the clearer it may be which intervention may solve the conflict. However, as Druckman and colleagues showed (Druckman et al., 1988; Druckman & Zechmeister, 1970, 1973), conflicts are harder to solve when values are intertwined with resources. Future research should investigate these “mixed” conflicts, and study whether it is possible for people to disentangle the conflict into different conflict issues or whether it is more suitable to take an integrated approach to the conflict.

Conclusion

Our current data document some crucial differences between value conflicts and resource conflicts. People feel more threatened in value conflict compared to resource conflict, and we argue that this threat is one of the reasons why value conflict is so hard to resolve. As long as people feel threatened and are compelled to defend themselves as being a right and good person, this will stand in the way of constructive conflict resolution.

Footnotes

Declaration of Conflicting Interests

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

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by The Netherlands Organization for Scientific Research (432-08-016) awarded to Naomi Ellemers, Fieke Harinck, and Daan Scheepers.

Notes

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