Journal of Personality and Social Psychology · 2019 · 60 citations · 94 references
Social SciencesPsychologySocial PsychologyIntergroup RelationsPrejudiceSocial PerceptionEthnic PrejudiceImmigrant PrejudiceMotivational Bases Of PrejudicePrejudice MeasurementSelf-enhancement MotivesSelf-esteemAnti-immigrant PrejudiceAnti-muslim PrejudiceImmigrant AttitudesImmigration AttitudesPerceived Threat Toward ImmigrantsPrejudice Against RefugeesSelf-enhancement ValuesSelf-transcendence Values
Although human values and value dissimilarity play pivotal roles in the prejudice literature, there remain important gaps in our understanding. To address these gaps, we recruited three British samples (N = 350) and presented Muslim immigrants, refugees, and economic migrants as target groups. Using polynomial regression analyses, we simultaneously tested effects of individuals' own values, their perceptions of immigrant values, and self-immigrant value dissimilarities on prejudice. Results indicated that favorability toward immigrants is higher when individuals hold higher self-transcendence values (e.g., equality) and lower self-enhancement values (e.g., power), and when they perceive immigrants to hold higher self-transcendence values and lower self-enhancement values. In addition, prejudice toward immigrants is higher when individuals who hold higher conservation values (e.g., security) perceive immigrants to value openness (e.g., freedom) more, suggesting a value dissimilarity effect. No value dissimilarity effects emerged when immigrants were perceived to be higher in conservation, self-transcendence, or self-enhancement values. Overall, these results showed that effects of values and value dissimilarity differ depending on which value dimension is considered. Additionally, the results revealed support for a novel mechanism with the motivation to be nonprejudiced underpinning the links between individuals' values and prejudice. Our discussion highlights the multifaceted manner in which values are linked to prejudice. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
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R: A Language and Environment for Statistical Computing
R Core Team · 2000 · 353K citations · Full text
Natural Sciences, Computer Science, Statistical Computing +10
Fitting Linear Mixed-Effects Models Using <b>lme4</b>
Douglas M. Bates, Martin Mächler, Benjamin M. Bolker et al. · Journal of Statistical Software · 2015 · 85.6K citations · Full text