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Cesario's framework for understanding group disparities is radically incomplete

Published online by Cambridge University Press:  13 May 2022

Morgan Weaving
Affiliation:
School of Historical and Philosophical Studies, The University of Melbourne, Victoria3010, Australia. mweaving@student.unimelb.edu.au; cfine@unimelb.edu.auhttps://findanexpert.unimelb.edu.au/profile/126041-cordelia-fine
Cordelia Fine
Affiliation:
School of Historical and Philosophical Studies, The University of Melbourne, Victoria3010, Australia. mweaving@student.unimelb.edu.au; cfine@unimelb.edu.auhttps://findanexpert.unimelb.edu.au/profile/126041-cordelia-fine

Abstract

Cesario argues that experimental studies of bias tell us little about why group disparities exist. We argue that Cesario's alternative approach implicitly frames understanding of group disparities as a false binary between “bias” and “group differences.” This, we suggest, will contribute little to our understanding of the complex dynamics that produce group disparities, and risks inappropriately rationalizing them.

Type
Open Peer Commentary
Copyright
Copyright © The Author(s), 2022. Published by Cambridge University Press

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References

Boe, J. L., & Woods, R. J. (2018). Parents’ influence on infants’ gender-typed toy preferences. Sex Roles 79(5–6):358373, https://doi.org/10.1007/s11199-017-0858-4.CrossRefGoogle ScholarPubMed
Breda, T., Jouini, E., Napp, C., & Thebault, G. (2020). Gender stereotypes can explain the gender-equality paradox. Proceedings of the National Academy of Sciences of the United States of America 117(49):3106331069, https://doi.org/10.1073/pnas.2008704117.CrossRefGoogle ScholarPubMed
Cheryan, S., Drury, B. J., & Vichayapai, M. (2013). Enduring influence of stereotypical computer science role models on women's academic aspirations. Psychology of Women Quarterly 37(1):7279, https://doi.org/10.1177/0361684312459328.CrossRefGoogle Scholar
Cheryan, S., Plaut, V. C., Davies, P. G., & Steele, C. M. (2009). Ambient belonging: How stereotypical cues impact gender participation in computer science. Journal of Personality and Social Psychology 97(6):10451060, https://doi.org/10.1037/a0016239.CrossRefGoogle ScholarPubMed
Hess, C., Ahmed, T., & Hayes, J. (2020). Providing Unpaid Household and Care Work in the United States: Uncovering Inequality (Briefing Paper No. IWPR #C487). Institute for Women's Policy Research. https://iwpr.org/wp-content/uploads/2020/01/IWPR-Providing-Unpaid-Household-and-Care-Work-inthe-United-States-Uncovering-Inequality.pdf.Google Scholar
Hines, M., Pasterski, V., Spencer, D., Neufeld, S., Patalay, P., Hindmarsh, P. C., & Acerini, C. L. (2016). Prenatal androgen exposure alters girls’ responses to information indicating gender-appropriate behaviour. Philosophical Transactions of the Royal Society B: Biological Sciences 371, 20150125. http://dx.doi.org/10.1098/rstb.2015.0125.CrossRefGoogle ScholarPubMed
Hyde, J. S., Lindberg, S. M., Linn, M. C., Ellis, A. B., & Williams, C. C. (2008). Gender similarities characterize math performance. Science, 321(5888):494495, http://dx.doi.org/10.1126/science.1160364.CrossRefGoogle ScholarPubMed
National Science Board (2018) Science & Engineering Indicators. https://www.nsf.gov/statistics/2018/nsb20181/assets/nsb20181.pdf.Google Scholar
Penner, A. M. (2008). Gender differences in extreme mathematical achievement: An international perspective on biological and social factors. American Journal of Sociology 114(SUPPL. 1):138170, https://doi.org/10.1086/589252.CrossRefGoogle ScholarPubMed
Ridgeway, C. L., & Correll, S. J. (2004). Unpacking the gender system: A theoretical perspective on gender beliefs and social relations. Gender and Society 18(4):510531, https://doi.org/10.1177/0891243204265269.CrossRefGoogle Scholar
Stephens, N. M., Markus, H. R., & Fryberg, S. A. (2012). Social class disparities in health and education: Reducing inequality by applying a sociocultural self model of behavior. Psychological Review, 119(4), 723–744. https://doi.org/10.1037/a0029028CrossRefGoogle ScholarPubMed
Stoet, G., & Geary, D. C. (2018). The gender-equality paradox in science, technology, engineering, and mathematics education. Psychological Science 29(4):581593, https://doi.org/10.1177/0956797617741719.CrossRefGoogle ScholarPubMed
Williams, J. (2001) Unbending gender: Why family and work conflict and what to do about it. Oxford University Press.Google Scholar
Williams, J., & Smith, J. (2015) The Myth That Academic Science Isn't Biased Against Women. The Chronicle of Higher Education. https://www-chronicle-com.eu1.proxy.openathens.net/article/the-myth-that-academic-science-isnt-biased-against-women/?cid2=gen_login_refresh.Google Scholar
Young, I. M. (1990). Five faces of oppression. In Young, I. M. (Ed.), Justice and the politics of difference (pp. 3963). Princeton University Press.Google Scholar