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Double Trouble: How Being Outnumbered and Negatively Stereotyped Threatens Career Outcomes of Women in STEM

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    Abstract

    Masculine work contexts form an important source of social identity threat for working women. But what aspect of masculine work contexts is most threatening to women's gender identity at work: A numerical majority of male colleagues (i.e., numerical male dominance), working in a profession in which women are negatively stereotyped (i.e., normative male dominance), or the combination? The current study aimed to disentangle these two aspects of masculine work contexts by testing its combined impact on the experience of gender identity threat among women and men who work in the STEM sector (i.e., Science, Technology, Engineering and Mathematics). A field study was conducted among women (N = 177) and men (N = 630) graduates holding an academic degree in a STEM educational program. Respondents either worked in- or outside the STEM sector (i.e., stronger vs. weaker gender stereotype) and estimated the ratio of men to women in their direct work environment. Results from a Structural Equation Model demonstrated that women in STEM face double trouble: The combination of working almost solely with male colleagues (being outnumbered) and working in the technical sector (where women are negatively stereotyped) predicted the highest levels of experienced gender identity threat, particularly among women who highly identified with their gender group. Gender identity threat, in turn, negatively predicted women's work engagement and career confidence. Men did not face double trouble: Their experience of gender identity threat was not related to working in a masculine STEM sector. Importantly, considering that the women in this sample already hold a degree in STEM, and have proven their competence in STEM and resilience to gender stereotypes, this research reveals how in naturalistic work settings, prevailing social identity threats continue to affect women's professional careers.

    Original languageEnglish
    Article number150
    JournalFrontiers in psychology
    Volume10
    DOIs
    Publication statusPublished - 19 Feb 2019

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 5 - Gender Equality
      SDG 5 Gender Equality

    Keywords

    • social identity threat
    • gender identification
    • masculine work contexts
    • gender (under)representation
    • work engagement
    • career confidence
    • Science Technology Engineering Math (STEM)

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