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Results of Structural Equation Model Analysis. Note: All paths in this SEM (Model 1) have statistically significant regression coefficients. Standardized b coefficients are displayed beside the corresponding paths. The variables in boxes refer to observed variables; the variable in the oval refers to a latent variable. Items 1-5 refer to the five items on perceived threat of immigrants.

Results of Structural Equation Model Analysis. Note: All paths in this SEM (Model 1) have statistically significant regression coefficients. Standardized b coefficients are displayed beside the corresponding paths. The variables in boxes refer to observed variables; the variable in the oval refers to a latent variable. Items 1-5 refer to the five items on perceived threat of immigrants.

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Xenophobia and anti-immigrant attacks rose during the COVID-19 pandemic, yet this may not be solely due to the disease threat. According to theories of frustration and scapegoating, situational obstructions and deprivation can motivate prejudice against outgroups. Using a global natural quasi-experimental design, this study tests whether the restri...

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... built a multilevel SEM to examine how lockdown duration and lockdown severity predict the latent variable of perceived threat of immigrants (Model 1; Figure 2 There was also a negative two-way interaction of these two indices (b of interaction term between standardized variables = 20.104, p \ .001). ...

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Article
Government policies can be productive tools for protecting citizens while simultaneously forging more egalitarian societies. At the same time, history has shown that well-intentioned governmental actions, such as those meant to quell pandemics (e.g., blood-donation restrictions), can single out members of marginalized groups (e.g., men who have sex with men). How did government actions shape intergroup outcomes during the COVID-19 pandemic? Here, we draw from emerging research to provide informed conjectures regarding whether and how government actions affected stereotypes (e.g., beliefs about gender), prejudice (e.g., anti-Asian bias), and intergroup violence (e.g., hate crimes against Asian individuals) during the COVID-19 pandemic. We discuss research examining the impact of policies intended to curb the spread of the disease, and we consider possible effects of the strategies used to communicate about the virus. Furthermore, we highlight open questions regarding how and why pandemic policies and communication shape intergroup outcomes, propose key directions for future research, and note possible implications for future development of policy and communication strategies.