Climate Justice: High‐Status Ingroup Social Models Increase Pro‐Environmental Action Through Making Actions Seem More Moral. (23rd December 2015)

• Record Type: Journal Article
• Authors: Sweetman, Joseph; Whitmarsh, Lorraine E.
• Is Part Of: Topics in cognitive science. Volume 8:Number 1(2016:Jan.)
• Page Start: 196
• Page End: 221
• Publication Date: 2015-12-23
• Subjects: Social model -- Status -- Pro‐environmental action -- Fairness -- Morality -- Efficacy -- Social identity; Cognitive science -- Periodicals; Cognitive Science -- Periodicals; 153.05
• DOI: 10.1111/tops.12178
• Languages: English
• ISSNs: 1756-8757

Abstract

Abstract: Recent work has suggested that our cognitive biases and moral psychology may pose significant barriers to tackling climate change. Here, we report evidence that through status and group‐based social influence processes, and our moral sense of justice, it may be possible to employ such characteristics of the human mind in efforts to engender pro‐environmental action. We draw on applied work demonstrating the efficacy of social modeling techniques in order to examine the indirect effects of social model status and group membership (through perceptions of efficacy, pro‐environmental social identity and moral judgments of how fair it is for individuals to perform particular pro‐environmental actions) on pro‐environmental action tendencies. We find evidence that high‐ (vs. low‐) status models increase pro‐environmental action, in part, through making such actions seem morally fairer to undertake. This effect of high‐status models only occurs when they share a meaningful ingroup membership with the target of influence. Further, we find evidence that this conditional effect of high‐status models may also have a direct impact on action tendencies. While the exact behaviors that are influenced may vary across student and non‐student samples, we argue that a focus on the "justice pathway" to action and the social‐cognitive features of models may offer a good opportunity for cognitive and behavioral scientists to integrate insights from basic research with those stemming from more applied research efforts.