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  • Title: Examining adolescent daughters' and their parents' academic-gender stereotypes: Predicting academic attitudes, ability, and STEM intentions.
    Author: Lapytskaia Aidy C, Steele JR, Williams A, Lipman C, Wong O, Mastragostino E.
    Journal: J Adolesc; 2021 Dec; 93():90-104. PubMed ID: 34717265.
    Abstract:
    INTRODUCTION: Women continue to be underrepresented in Science, Technology, Engineering, and Mathematics (STEM) and research suggests that academic-gender stereotypes can be a contributing factor. In the present research, we examined whether adolescent daughters' and their parents' gender stereotypes about math and liberal arts would predict the academic orientation of daughters at a critical time of career related decision-making. METHODS: Participants included girls in late adolescence (N = 185, Mage = 17) and at least one parent (N = 230, Mage = 49), resulting in 147 mother-daughter dyads and 83 father-daughter dyads. Implicit academic-gender stereotypes were measured using an Implicit Association Test (IAT) and explicit stereotypes, academic attitudes, academic ability, and daughters' intentions to pursue a degree in STEM were measured using self-reports. RESULTS: Neither mothers' nor fathers' implicit or explicit academic-gender stereotypes predicted adolescent daughters' implicit stereotypes; however, fathers' explicit stereotypes predicted daughters' explicit stereotypes. In addition, daughters' academic orientation, a latent variable composed of adolescent girls' academic attitudes, academic ability, and intentions to pursue a degree in STEM, was predicted by daughters' own implicit and explicit stereotypes. This was the case for relative orientation toward math versus liberal arts, as well as math (but not liberal arts) orientation. CONCLUSIONS: These findings suggest the importance of challenging academic-gender stereotypes during adolescence and suggest that at this stage in development, mothers' and fathers' academic stereotypes might have limited relation to daughters' own implicit associations with academic domains.
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