When blame avoidance backfires: Responses to performance framing and outgroup scapegoating during the COVID‐19 pandemic

Abstract

Public officials use blame avoidance strategies when communicating performance information. While such strategies typically involve shifting blame to political opponents or other governments, we examine how they might direct blame to ethnic groups. We focus on the COVID‐19 pandemic, where the Trump administration sought to shift blame by scapegoating (using the term “Chinese virus”) and mitigate blame by positively framing performance information on COVID‐19 testing. Using a novel experimental design that leverages machine learning techniques, we find scapegoating outgroups backfired, leading to greater blame of political leadership for the poor administrative response, especially among conservatives. Backlash was strongest for negatively framed performance data, demonstrating that performance framing shapes blame avoidance outcomes. We discuss how divisive blame avoidance strategies may alienate even supporters.

Patients’ Clinical and Psychological Status in Different COVID-19 Waves in Italy: A Quanti-Qualitative Study

“…This finding might be explained from a sociological perspective: blaming an outgroup can be an effective coping strategy to face uncertainty and worries that were mainly experienced during the first wave. Some studies described similar scapegoating reactions as a strategy to regain a sense of control in the face of medical and socio-political uncertainty [ 45 , 46 ]. However, further studies are necessary to better understand this issue.…”

From fear to hate: Sources of anti‐Asian sentiment during COVID‐19

“…2020; Porumbescu et al. 2023). With the likely origin of the novel coronavirus being Wuhan China, people of Chinese or other Asian descent have become easy targets.…”