e-space
Manchester Metropolitan University's Research Repository

    Striving to be super: the contradictions of academic success in high-achieving, working-class girls’ pathways to high-tariff universities

    Davey, Katherine ORCID logoORCID: https://orcid.org/0009-0003-0340-4422 (2024) Striving to be super: the contradictions of academic success in high-achieving, working-class girls’ pathways to high-tariff universities. British Journal of Educational Studies. ISSN 0007-1005

    [img]
    Preview
    Published Version
    Available under License Creative Commons Attribution.

    Download (1MB) | Preview

    Abstract

    Although higher education is positioned as a site of opportunity for young women in the UK, not all female applicants experience straightforward pathways into this arena. This paper focuses on a group of sixteen high-achieving girls from working-class backgrounds who are striving for academic success, in the form of top grades and places at high-tariff UK universities. Against the backdrop of neoliberalism and postfeminism, the stereotype of an academic ‘supergirl’ incites these young women to construct their pathways to high-tariff universities individualistically and to invest in aspirational futures beyond where they grew up. However, this stereotype also places a heavy burden on them, as young women from working-class backgrounds, to take responsibility for their own outcomes. Using Margaret Archer’s concept of ‘autonomous reflexivity’ to analyse the research findings, the paper shows how the girls find themselves pincered between the powerfully enabling and constraining effects of their social class alongside their academic success. It highlights complexities and contradictions of striving to be a high-achieving, working-class girl that are not currently well understood within the research literature or widening access and participation agenda.

    Impact and Reach

    Statistics

    Activity Overview
    6 month trend
    28Downloads
    6 month trend
    20Hits

    Additional statistics for this dataset are available via IRStats2.

    Altmetric

    Repository staff only

    Edit record Edit record