Does the Name-Race Implicit Association Test Measure Racial Prejudice?

Author(s):  
Don van Ravenzwaaij ◽  
Han L. J. van der Maas ◽  
Eric-Jan Wagenmakers

Research using the Implicit Association Test (IAT) has shown that names labeled as Caucasian elicit more positive associations than names labeled as non-Caucasian. One interpretation of this result is that the IAT measures latent racial prejudice. An alternative explanation is that the result is due to differences in in-group/out-group membership. In this study, we conducted three different IATs: one with same-race Dutch names versus racially charged Moroccan names; one with same-race Dutch names versus racially neutral Finnish names; and one with Moroccan names versus Finnish names. Results showed equivalent effects for the Dutch-Moroccan and Dutch-Finnish IATs, but no effect for the Finnish-Moroccan IAT. This suggests that the name-race IAT-effect is not due to racial prejudice. A diffusion model decomposition indicated that the IAT-effects were caused by changes in speed of information accumulation, response conservativeness, and non-decision time.

2007 ◽  
Vol 93 (3) ◽  
pp. 353-368 ◽  
Author(s):  
Karl Christoph Klauer ◽  
Andreas Voss ◽  
Florian Schmitz ◽  
Sarah Teige-Mocigemba

2020 ◽  
pp. 174569161989796 ◽  
Author(s):  
Michelangelo Vianello ◽  
Yoav Bar-Anan

In this commentary, we welcome Schimmack’s reanalysis of Bar-Anan and Vianello’s multitrait multimethod (MTMM) data set, and we highlight some limitations of both the original and the secondary analyses. We note that when testing the fit of a confirmatory model to a data set, theoretical justifications for the choices of the measures to include in the model and how to construct the model improve the informational value of the results. We show that making different, theory-driven specification choices leads to different results and conclusions than those reported by Schimmack (this issue, p. ♦♦♦). Therefore, Schimmack’s reanalyses of our data are insufficient to cast doubt on the Implicit Association Test (IAT) as a measure of automatic judgment. We note other reasons why the validation of the IAT is still incomplete but conclude that, currently, the IAT is the best available candidate for measuring automatic judgment at the person level.


2004 ◽  
Vol 63 (2) ◽  
pp. 107-111 ◽  
Author(s):  
Marianne Schmid Mast

The goal of the present study was to provide empirical evidence for the existence of an implicit hierarchy gender stereotype indicating that men are more readily associated with hierarchies and women are more readily associated with egalitarian structures. To measure the implicit hierarchy gender stereotype, the Implicit Association Test (IAT, Greenwald et al., 1998) was used. Two samples of undergraduates (Sample 1: 41 females, 22 males; Sample 2: 35 females, 37 males) completed a newly developed paper-based hierarchy-gender IAT. Results showed that there was an implicit hierarchy gender stereotype: the association between male and hierarchical and between female and egalitarian was stronger than the association between female and hierarchical and between male and egalitarian. Additionally, men had a more pronounced implicit hierarchy gender stereotype than women.


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