Making a case for more feminist approaches in quantitative research: How commonly used quantitative approaches in adult education research marginalise and oversimplify diverse and intersectional populations

Abstract

In contrast to qualitative and theoretical approaches, the mainstream of quantitative research often still finds it difficult to incorporate modern concepts of diversity and intersectionality into its work. This article aims to highlight various aspects in which large studies and their evaluations marginalise or ignore certain parts of the population. In surveying data, large-scale surveys like the Programme for the International Assessment of Adult Competencies (PIAAC) often not only operate on a binary gender concept but also do not differentiate between a person gender identity and their social gender. In addition, commonly used methods keep unequal distributions invisible. Nonbinary people are virtually invisible, unequal benefits for women remain hidden and the intersectional diversity inside the broad gender categories poses challenges to the mainstream of quantitative research in adult education. Therefore, there is a need for a feminist approach to statistical methods and quantitative research and in particular a feminist approach to a careful and critical interpretation.

A test for implicit bias in discretionary criminal justice decisions.

“…Our findings are consistent with previous research showing that Black women been treated more harshly than White women across the criminal justice system-from interactions with the police through sentencing and corrections (e.g., Mann, 1989;van Wormer & Bartollas, 2022). Our findings provide empirical evidence that there is something unique about the unconscious biases people hold about Black women involved in the criminal justice system that is different than for Black men, which scholars studying intersectionality are just beginning to explore (e.g., Batashtini et al, 2022;Heilmann, 2021;Hester et al, 2020).…”

Young Women, Employment and Precarity: The Face of Two Periods of Crisis in Spain (2008–2021)

“…We must bear in mind that the statistics we used hide different biases that shape the way we interpret social reality. The dominant quantitative research still does not incorporate concepts and variables of diversity and intersectionality (Heilmann 2021). The different types of statistics discussed in this article employ, for example, a binary concept of gender that excludes identities and experiences.…”