A total of 247 American children between 6 and 10 years of age (126 girls and 121 boys) completed Implicit Association Tests and explicit self‐report measures assessing the association of (a) me with male (gender identity), (b) male with math (math–gender stereotype), and (c) me with math (math self‐concept). Two findings emerged. First, as early as second grade, the children demonstrated the American cultural stereotype that math is for boys on both implicit and explicit measures. Second, elementary school boys identified with math more strongly than did girls on both implicit and self‐report measures. The findings suggest that the math–gender stereotype is acquired early and influences emerging math self‐concepts prior to ages at which there are actual differences in math achievement.

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Interest in unintended discrimination that can result from implicit attitudes and stereotypes (implicit biases) has stimulated many research investigations. Much of this research has used the Implicit Association Test (IAT) to measure association strengths that are presumed to underlie implicit biases. It had been more than a decade since the last published treatment of recommended best practices for research using IAT measures. After an initial draft by the first author, and continuing through three subsequent drafts, the 22 authors and 14 commenters contributed extensively to refining the selection and description of recommendation-worthy research practices. Individual judgments of agreement or disagreement were provided by 29 of the 36 authors and commenters. Of the 21 recommended practices for conducting research with IAT measures presented in this article, all but two were endorsed by 90% or more of those who felt knowledgeable enough to express agreement or disagreement; only 4% of the totality of judgments expressed disagreement. For two practices that were retained despite more than two judgments of disagreement (four for one, five for the other), the bases for those disagreements are described in presenting the recommendations. The article additionally provides recommendations for how to report procedures of IAT measures in empirical articles.

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