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  1.  29
    Testing for Implicit Bias: Values, Psychometrics, and Science Communication.Nick Byrd & Morgan Thompson - 2022 - WIREs Cognitive Science.
    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 (...)
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  2. How Should We Think About Implicit Measures and Their Empirical “Anomalies”?Bertram Gawronski, Michael Brownstein & Alex Madva - 2022 - WIREs Cognitive Science:1-7.
    Based on a review of several “anomalies” in research using implicit measures, Machery (2021) dismisses the modal interpretation of participant responses on implicit measures and, by extension, the value of implicit measures. We argue that the reviewed findings are anomalies only for specific—influential but long-contested—accounts that treat responses on implicit measures as uncontaminated indicators of trait-like unconscious representations that coexist with functionally independent conscious representations. However, the reviewed findings are to-be-expected “normalities” when viewed from the perspective of long-standing alternative frameworks (...)
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  3.  31
    Assessing the Implicit Bias Research Program: Comments on Brownstein, Gawronski, and Madva Versus Machery.Shannon Spaulding - 2022 - WIREs Cognitive Science.
    Michael Brownstein, Alex Madva, and Bertram Gawronski articulate a careful defense of research on implicit bias. They argue that though there is room for improvement in various areas, when we set the bar appropriately and when we are comparing relevant events, the test–retest stability and predictive ability of implicit bias measures are respectable. Edouard Machery disagrees. He argues that theories of implicit bias have failed to answer four fundamental questions about measures of implicit bias, and this undermines their utility in (...)
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