Introducing the Special Issue on “Social Justice: Lessons Learned and Needed Research”

In their conceptual article, Baumert, Adra and Li investigate how the impact of individual differences in the justice sensitivity perspective contribute to shaping group-level processes. Justice sensitivity captures individual differences in the readiness to perceive injustice, the intensity of cognitive and emotional reactions to perceived injustice, and the resulting motivation to restore justice (Schmitt, 1996). The four perspectives include victim sensitivity, which is the perception of unjust own victimization; beneficiary and perpetrator sensitivities, which are the perception of oneself as benefitting from or actively committing injustices, respectively; and observer sensitivity, which is the perception of injustice that affects others.

Drawing on social identity theory (Tajfel & Turner, 1979), intergroup-emotions theory (Smith, 1993), and the dynamic dual-pathway model of approach coping with collective disadvantage (van Zomeren et al., 2012), the authors propose a theoretical framework to understand how and under which conditions individual differences in justice sensitivity should influence intergroup experiences, attitudes, and behaviors. Additionally, the authors analyze how justice sensitivity might invoke potential psychological conflicts between group-level and personal concerns and how the justice sensitivity perspective might function depending on the advantaged, disadvantaged, or bystander status of one’s ingroup. The authors end their paper with a discussion of how their framework can direct future research toward a more complete understanding of the justice sensitivity perspectives in intergroup contexts.

The article by De Cremer and McGuire relates directly to the realm of future research by social justice scholars. It addresses the fairness-based receptivity of artificial intelligence (AI) for decision-making in workplace organizations, pointing to ways that many companies have already begun putting algorithmic decision-making practices in place (cf. De Cremer, 2020a, 2020b). The relevance for future research is apparent, given the trajectory of likely increased management-by-algorithm implementation. De Cremer and McGuire illustrated one path for such a trajectory by conducting two studies.

Study 1 participants took the role of decision makers faced with an algorithm/human-participation tradeoff under one of six conditions. Those variations differed in the costs of adopting a plan with a human voice/decision-control option. Although participants in all conditions considered the voice/decision-control option fairer than the exclusively algorithmic option, they became willing to choose the latter when the high costs of the former loomed large (for related research on tradeoff dilemmas for decision-makers in other contexts, see Folger & Whiting, 2020). Study 2 implemented extensions to the Study 1 paradigm by presenting respondents with program implementations that ranged in 10% increments from total algorithmic control to total control by a human decision-maker. Responses included the acceptability of the proposed program, its fairness, and their own preferred division of decision-making responsibility. The results showed that increased human participation in decision-making made the program more acceptable (mediated partially by fairness), but only up to a point. Notably the preferred participation division represented a 60%/40% split of the human/algorithm combinations. These preliminary findings about the fairness-based acceptance of algorithmic decision-making clearly warrant a programmatic series of investigations in the future.

In their conceptual article, Kay and Gibbs reflect on the tension between conducting basic research and applied research in the pursuit of social justice. They describe having developed and worked on social scientific theory that has allowed them to shift between various applied research questions while remaining programmatic and thematic. In particular, the authors trace the trajectory of compensatory control theory (CCT; Kay et al., 2008)—from its initial investigations to a current initiative aimed at understanding military and civilian transitions.

CCT (Kay et al., 2008, 2009) suggests that people embrace ideologies that emphasize personal, societal, or religious control to ease worries they experience when they perceive randomness and disorder in their lives. This need to perceive the world as nonrandom suggests a motivated substitutability between personal control and secular and religious sources of external control. The authors describe their research on CCT in the context of veterans transitioning from military to civilian life and have sought to expand the theory by exploring the consequences of having external sources of control become a substantial method of satisfying a person’s pursuit of order and structure. The authors note basic theory can help inform applied issues and how transporting basic theory to new applied contexts can help inform and refine the theory itself.

Okimoto, Konradt, Krys, and Dawson’s contribution centers on restorative justice and how, as a response to perpetrator transgressions, endorsement of it varies from one person to the next. As they point out, the vast amount of work done on reactions to perceived workplace injustices contrasts with the comparatively small amount directed to understanding how organizations might seek to “recover” via restorative justice. Moreover, they note that although restorative justice might generally be accepted as one response to offenders’ transgressions (e.g., as collaborating with offenders to revalidate shared values and standards of conduct, to reach mutual understanding of the harm done and routes to recovery from it), not much at all is known concerning how its perceived appropriateness might be moderated by different kinds of conditions, especially as those relate to the domain of workplace employment.

This research used an experimental policy-capturing design. Participants responded to scenario manipulations of workplace situations involving a manager’s poor treatment of a subordinate, which varied across a range from not unfair to extremely unfair. The dependent variables were measures of restorative justice and justice sensitivity (Schmitt et al., 2010)—the latter from the perspective of the victim. The authors predicted and found an overall curvilinear and concave trajectory of the endorsement of restorative justice. A third of the respondents instead showed a preference for restorative justice even at the lowest levels of unfairness, however, and a linear increase after that. This evidence for two classes of individuals, with differing response trajectories, points to the importance of taking into account heterogeneity not only in terms of perceived injustice but also in terms of favored responses to it.

In his conceptual article, Van Prooijen explains the connection between belief in evidence-free conspiracy theories and justice judgments, and how individuals come to form conspiracy theory beliefs. First, conspiracy theories necessarily involve assumptions of cause-and-effect patterns, agency, threat, and secrecy and involve the belief and coordinated actions of groups (Van Prooijen, 2018; Van Prooijen & Van Vugt, 2018). He argues that individuals come to develop conspiracy theory beliefs through two distinct processes. In the first process, existential threats motivate biased mental processing that allows individuals to be susceptible to these beliefs. In the second process, the existence of out-groups precipitates unrealistic perceptions of reality due to strong in-group allegiances. Once developed, conspiracy theory beliefs are maintained through motivated reasoning processes that reinforce the belief.

Van Prooijen argues that conspiracy theory beliefs hold unique implications for social justice research beyond justice judgments. Given that conspiracy theory beliefs are evidence-free, it is difficult to design interventions to modify such beliefs, which typically involve the presentation of evidence in justice research. Additionally, the second process involved in conspiracy theory belief suggests that group allegiances themselves can act as a justice cue, sparking much potential for future research on conspiracy theories and social justice.

It is clear from this collection that the “next generation” of justice researchers are pushing the frontiers of the field forward in new directions by asking new kinds of questions. Procedural justice researchers previously sought to answer questions about what would make people care about justice in the first place, especially if fair procedures produced unfair outcomes. Answers included an instrumental motive (e.g., Thibaut & Walker, 1975), a self-identification with group values and “expressive” values (e.g., Lind & Tyler, 1988). Subsequently that was expanded to include caring about fairness as a moral value (Folger, 2001)—which in turn has also been extended to apply to moral values in general, whether instrumental or expressive (Folger & Whiting, 2020; Folger et al., 2013).

Since that earlier period, much research has explored the antecedents and the consequences of justice motivation. What stands out within the entries in this special issue is the ever-broadening trajectory of research contexts on both fronts. That tendency appears, for example, in the explorations of justice sensitivity by Baumert et al. and Okiomoto et al. Both include measurement of that variable, but the differences in contexts (antecedents of group-level processes vs. heterogeneity in “groupings” at the individual level) yielded unique insights. Both types of investigations expand justice horizons in ways open to programmatic research.

Diverse settings, expanded horizons, and new insights also characterize the remaining contributions, especially in terms of applied contexts. Van Pooijen’s explorations of susceptibility to thinking in terms of conspiracy theories adds yet another layer to aspects of people’s “sensitivity” to (perceived) injustice, and the way DeCremer and McGuire examine preferences for shared decision-making control—namely between humans and AI algorithms—shows the sensitivity to degrees of that control. The applicability to future contexts also shows up in the work presented by Kay and Gibbs, not only in the context of variations in control and reactions to it, but also in the context of interventions shaped by justice concerns.

These contributions make a very fine addition to the justice literature. Collectively they provide abundant evidence that justice theorizing and research constantly uncovers new domains of interest. Justice scholars will, therefore, find much to inspire pursuits in those domains by seizing on the insights these articles provide. We recommend them with enthusiasm!.