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Replication data for: Nosek and Smyth (2011): Implicit social cognitions predict math engagement and achievement

Harvard Dataverse (Africa Rice Center, Bioversity International, CCAFS, CIAT, IFPRI, IRRI and WorldFish)

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Title Replication data for: Nosek and Smyth (2011): Implicit social cognitions predict math engagement and achievement
 
Identifier https://doi.org/10.7910/DVN/Z3MV4J
 
Creator Brian Nosek
 
Publisher Harvard Dataverse
 
Description Gender stereotypes about math and science do not need to be endorsed, or even available to conscious introspection, to contribute to the sex gap in engagement and achievement in science, technology, engineering and mathematics (STEM). We examined implicit math attitudes and stereotypes among a heterogeneous sample of 5,139 participants. Women showed stronger implicit negativity toward math than men did, and equally strong implicit gender stereotypes. For women, stronger implicit math=male stereotypes predicted greater negativity toward math, less participation, weaker self-ascribed ability, and worse math achievement; for men, those relations were weakly in the opposite direction. Implicit stereotypes had greater predictive validity than explicit stereotypes. Female STEM majors, especially those with a graduate degree, held weaker implicit math=male stereotypes and more positive implicit math attitudes than other women. Implicit measures will be a valuable tool for education research and help account for unexplained variation in the STEM sex gap.
 
Subject implicit social cognition
 
Date 2011