Maximizing the effects of intergroup contact: structuring the contact setting

According to social psychologists, intergroup contact is amongst the most effective strategies for prejudice-reduction (Allport, 1954; Brown & Hewstone, 2005; Davies et al., 2011; Hodson & Hewstone, 2013; Pettigrew & Tropp, 2011; Tropp & Barlow, 2018; Vezzali & Stathi, 2017a). Decades of research have shown that contact reduces prejudice across contexts, age, and target-groups and by using experimental, correlational, and longitudinal methodologies (Pettigrew & Tropp, 2006). Moreover, the effects of contact generalize to outgroups not directly involved in the contact situation (Pettigrew, 2009) and are not weakened by individuals’ initial prejudicial beliefs (Hodson, Turner, & Choma, 2017).

The contact hypothesis, however, does not ‘simply’ state that contact between members belonging to different groups will reduce prejudice. One of the greatest contributions of Allport’s (1954) seminal work on intergroup contact is not only the acknowledgment that contact can reduce prejudice (which is - at least after decades of research evidence - quite obvious) but that he specified the conditions under which this can happen. In fact, sometimes contact can also increase prejudice, as everyday experiences related to, for example, increasing rates of immigration clearly show (Graf & Paolini, 2017). Despite specifying these ‘optimal’ conditions (which were not systematically tested, as we will show later on in the chapter), the original formulation of the contact hypothesis was not clear about how to structure the contact setting in order to maximize positive effects. Note that the contact hypothesis deals with extremely critical social issues, such as prejudice and social equality, and it originally aimed to describe but also to drive social change (Clark, 1953; cf. J. Dixon, 2017). Therefore, it is not only important to know that contact reduces prejudice but also to understand how we can make this happen. In other words, intergroup contact theory should also specify how contact should be practically implemented in order to improve intergroup relations.

This chapter aims at discussing how contact should be structured in order to favor prejudice-reduction. In the first part of the chapter, we focus on the role of optimal conditions as specified by Allport (1954). Next, we move to theories that explain how contact should be structured in order to reduce prejudice, focusing on social categorization. Then, we review naturalistic interventions, including some from our own line of research, that provide direct or indirect evidence for the role of social categorization in contact settings. Finally, we draw conclusions on the importance of conducting experimental research in the field.

The optimal conditions of contact

According to Allport (1954; see also Pettigrew, 1998), contact will reduce prejudice when members of different groups (a) have similar status within the contact situation, (b) interact cooperatively, (c) seek to achieve a common goal, and (d) contact is supported by authorities and norms (for reviews, see Koschate & Van Dick, 2011; Pettigrew, 1998; Pettigrew & Tropp, 2011).

The role of optimal conditions has been widely debated in contact research. On the one hand, early contact researchers continued to propose ‘necessary’ conditions, creating a long list that could only be applied to very few contact situations. This approach limited the appeal of the contact hypothesis as, practically, ‘ideal’ intergroup contact was deemed unfeasible (cf. Pettigrew, 1998). On the other hand, although Allport (1954) considered the suggested optimal conditions essential, it has been found that contact can be effective in reducing prejudice even in their absence. The meta-analysis by Pettigrew and Tropp (2006) demonstrated in fact that these conditions can facilitate the contact effects. However, albeit smaller, the contact effects persist even in their absence.

Optimal conditions were often assessed by means of external observers and/or coders (as in the meta-analysis by Pettigrew & Tropp, 2006) or using a combination of participants’ and external observers’ ratings (Koschate & Van Dick, 2011). However, as stated by Pettigrew and Tropp (2011), it is also important to examine how individuals perceive the contact situation to be, specifically the extent to which these conditions are valued and internalized by individuals. In addition, when it comes to deciding whether optimal conditions are present in a contact situation, external coders necessarily rely on information provided in articles (e.g., in the meta-analysis by Pettigrew & Tropp, 2006), which may be limited or interpreted subjectively.

It is worth noting that optimal conditions were generally tested in the literature as moderators of the effects of contact (Pettigrew & Tropp, 2006), rather than as predictors of contact. Even when they were tested as predictors of contact effects, studies did not include contact measures and considered them as a replacement for the measurement of intergroup contact; that is, optimal conditions were used as contact measures (Koschate & Van Dick, 2011; Lipponen & Leskinen, 2006). As an example, Molina and Wittig (2006) merged both contact and optimal conditions into a composite score reflecting interracial school climate. Therefore, clear evidence as to whether optimal conditions predict (future) contact is scarce. Recent research focused on the distinction between positive and negative contact rather than on the presence or lack of optimal conditions and found that they have opposite effects on prejudice, such that positive contact reduces prejudice whereas negative contact increases it (Graf & Paolini, 2017; for a meta-analysis on the generalization following positive or negative experiences, see Paolini & McIntyre, 2019). Driven from the initial theorization of the contact hypothesis, we argue that optimal conditions may be also conceptualized as predictors of contact, in addition to being considered as moderators. We suggest that this is important because finding that optimal conditions are strongly predictive of positive contact can suggest that their implementation is one of the keys to the success of a contact intervention. This consideration has been slightly downplayed following the finding of the meta-analysis by Pettigrew and Tropp (2006) that optimal conditions are facilitating variables. Note that considering optimal contact conditions as independent variables is not inconsistent with considering them as moderators. Rather, we argue that the two perspectives are complementary. In the former case, the hypothesis (consistent with Allport s formulation) is that optimal contact conditions should be implemented for contact to be effective (therefore, their implementation is predictive of more positive contact). Conceptually, implementation of contact conditions precedes contact; in addition, whereas independent variable and moderator should ideally be independent from each other, it is clear that the implementation of optimal contact conditions is meant to influence contact, especially its positivity. In the latter case, in contrast, the hypothesis is that contact will be maximally effective when it is structured to include the optimal conditions. Also note that considering the optimal contact conditions as independent variables or moderators may be dependent upon the specific context under investigation. In particular, considering them as moderators is especially relevant when the sample is recruited in heterogeneous contexts, so their implementation largely varies across participants (this is the case, for instance, when conducting meta-analyses).

To test optimal contact conditions as antecedents of contact, we conducted a cross-sectional study within a workplace context, considering both high- and low- status group members1 (Di Bernardo, Vezzali, Birtel, et al., 2019). Participants were Italian and immigrant workers of three enterprises located in Northern Italy. As a measure of optimal conditions, we combined responses to four items, tapping on the extent to which participants believed that each optimal condition (cooperation, common goals, equal status, institutional support) was present within the contact (workplace) situation. The choice of combining them into a single measure, rather than considering them separately, slightly departs from the broader literature, which considered them as separate factors or did not consider all four conditions. Instead, in line with Allports (1954) and Pettigrew and Tropp s (2011) contentions, we were interested in whether Allport’s optimal conditions work together, specifically in whether they are predictive of positive contact. As a contact measure, rather than assessing frequency of contact (which would not be particularly informative since we were investigating a non-voluntary contact setting, where contact was unavoidable), we adapted a measure of psychological organizational climate (Koys & DeCotiis, 1991). This variable assessed the positive intergroup climate within the work setting, driven by positive Italian and immigrant intergroup interactions, tapping therefore on the quality of intergroup contact. As outcome variables, we included a measure of support for social policies favoring immigrants (therefore relating to collective action and social change research; see Chapter 7) and two behavioral measures assessing intergroup behavior at work (altruism) and outside work (socializing together). Outgroup stereotypes were included as a potential mediator. The tested model is presented in Figure 1.1.

First, we found that the optimal conditions and contact, despite being highly correlated, were empirically distinct. This suggests that assessing the optimal conditions is different than assessing contact (Molina & Wittig, 2006), since they tap on different constructs both conceptually and empirically. We also found that, for the high-status group (in this case, Italians), the optimal conditions were strongly predictive of positive contact and indirectly affected, via contact and improved outgroup stereotypes, support for social policies favoring immigrants, as well as intergroup behavior both within and outside the workplace. Results for the low- status group (immigrants) were less clear. Although the optimal conditions were strongly predictive of positive contact, which in turn was associated with improved outgroup stereotypes as well as social policies support and behavior outside work (behavior in the workplace was not included in the final model because the latent factor did not significantly load on the relative indicators), the mediation was only significant for social policies support.

Model testing the association of optimal contact conditions with social policies support and with behavior at work and outside work via contact and stereotypes

FIGURE 1.1 Model testing the association of optimal contact conditions with social policies support and with behavior at work and outside work via contact and stereotypes

Source: Di bernardo, Vezzali, birtel, et al., 2019

The results of this study support the importance of structuring the contact setting according to the optimal conditions specified by the contact hypothesis (Allport, 1954; Pettigrew, 1998).

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