{"title":"内隐偏见的检验:价值观、心理测量学和科学传播","authors":"Nick Byrd, Morgan Thompson","doi":"10.1002/wcs.1612","DOIUrl":null,"url":null,"abstract":"Our understanding of implicit bias and how to measure it has yet to be settled. Various debates <i>between</i> cognitive scientists are unresolved. Moreover, the public's understanding of implicit bias tests continues to lag behind cognitive scientists'. These discrepancies pose potential problems. After all, a great deal of implicit bias research has been publicly funded. Further, implicit bias tests continue to feature in discourse about public- and private-sector policies surrounding discrimination, inequality, and even the purpose of science. We aim to do our part by reconstructing some of the recent arguments in ordinary language and then revealing some of the operative norms or values that are often hidden beneath the surface of these arguments. This may help the public learn more about the science of implicit bias. It may also help both laypeople and scientists reflect on the values, interests, and stakeholders involved in establishing, justifying, and communicating scientific research.","PeriodicalId":501132,"journal":{"name":"WIREs Cognitive Science","volume":"37 19","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Testing for implicit bias: Values, psychometrics, and science communication\",\"authors\":\"Nick Byrd, Morgan Thompson\",\"doi\":\"10.1002/wcs.1612\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Our understanding of implicit bias and how to measure it has yet to be settled. Various debates <i>between</i> cognitive scientists are unresolved. Moreover, the public's understanding of implicit bias tests continues to lag behind cognitive scientists'. These discrepancies pose potential problems. After all, a great deal of implicit bias research has been publicly funded. Further, implicit bias tests continue to feature in discourse about public- and private-sector policies surrounding discrimination, inequality, and even the purpose of science. We aim to do our part by reconstructing some of the recent arguments in ordinary language and then revealing some of the operative norms or values that are often hidden beneath the surface of these arguments. This may help the public learn more about the science of implicit bias. It may also help both laypeople and scientists reflect on the values, interests, and stakeholders involved in establishing, justifying, and communicating scientific research.\",\"PeriodicalId\":501132,\"journal\":{\"name\":\"WIREs Cognitive Science\",\"volume\":\"37 19\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-06-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"WIREs Cognitive Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1002/wcs.1612\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"WIREs Cognitive Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1002/wcs.1612","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Testing for implicit bias: Values, psychometrics, and science communication
Our understanding of implicit bias and how to measure it has yet to be settled. Various debates between cognitive scientists are unresolved. Moreover, the public's understanding of implicit bias tests continues to lag behind cognitive scientists'. These discrepancies pose potential problems. After all, a great deal of implicit bias research has been publicly funded. Further, implicit bias tests continue to feature in discourse about public- and private-sector policies surrounding discrimination, inequality, and even the purpose of science. We aim to do our part by reconstructing some of the recent arguments in ordinary language and then revealing some of the operative norms or values that are often hidden beneath the surface of these arguments. This may help the public learn more about the science of implicit bias. It may also help both laypeople and scientists reflect on the values, interests, and stakeholders involved in establishing, justifying, and communicating scientific research.