{"title":"Prejudice model 1.0: A predictive model of prejudice.","authors":"Eric Hehman, Rebecca Neel","doi":"10.1037/rev0000470","DOIUrl":null,"url":null,"abstract":"<p><p>The present research develops a predictive model of prejudice. For nearly a century, psychology and other fields have sought to scientifically understand and describe the causes of prejudice. Numerous theories of prejudice now exist. Yet these theories are overwhelmingly defined verbally and thus lack the ability to precisely predict when and to what extent prejudice will emerge. The abundance of theory also raises the possibility of undetected overlap between constructs theorized to cause prejudice. Predictive models enable falsification and provide a way for the field to move forward. To this end, here we present 18 studies with ∼5,000 participants in seven phases of model development. After initially identifying major theorized causes of prejudice in the literature, we used a model selection approach to winnow constructs into a parsimonious predictive model of prejudice (Phases I and II). We confirm this model in a preregistered out-of-sample test (Phase III), test variations in operationalizations and boundary conditions (Phases IV and V), and test generalizability on a U.S. representative sample, an Indian sample, and a U.K. sample (Phase VI). Finally, we consulted the predictions of experts in the field to examine how well they align with our results (Phase VII). We believe this initial predictive model is limited and bad, but by developing a model that makes highly specific predictions, drawing on the state of the art, we hope to provide a foundation from which research can build to improve science of prejudice. (PsycInfo Database Record (c) 2024 APA, all rights reserved).</p>","PeriodicalId":21016,"journal":{"name":"Psychological review","volume":" ","pages":"1235-1265"},"PeriodicalIF":5.1000,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Psychological review","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.1037/rev0000470","RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/2/22 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"PSYCHOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
The present research develops a predictive model of prejudice. For nearly a century, psychology and other fields have sought to scientifically understand and describe the causes of prejudice. Numerous theories of prejudice now exist. Yet these theories are overwhelmingly defined verbally and thus lack the ability to precisely predict when and to what extent prejudice will emerge. The abundance of theory also raises the possibility of undetected overlap between constructs theorized to cause prejudice. Predictive models enable falsification and provide a way for the field to move forward. To this end, here we present 18 studies with ∼5,000 participants in seven phases of model development. After initially identifying major theorized causes of prejudice in the literature, we used a model selection approach to winnow constructs into a parsimonious predictive model of prejudice (Phases I and II). We confirm this model in a preregistered out-of-sample test (Phase III), test variations in operationalizations and boundary conditions (Phases IV and V), and test generalizability on a U.S. representative sample, an Indian sample, and a U.K. sample (Phase VI). Finally, we consulted the predictions of experts in the field to examine how well they align with our results (Phase VII). We believe this initial predictive model is limited and bad, but by developing a model that makes highly specific predictions, drawing on the state of the art, we hope to provide a foundation from which research can build to improve science of prejudice. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
期刊介绍:
Psychological Review publishes articles that make important theoretical contributions to any area of scientific psychology, including systematic evaluation of alternative theories.