By Tània Verge (Universitat Pompeu Fabra)
Although the ways in which research questions are selected and the data is collected and analyzed often lead to gender-biased and incorrect conclusions, quantitative methods courses are generally taught in a gender-blind fashion. Critical omissions of gender also occur when attention is not paid to the fact that statistics anxiety, generally higher among female students, may be due to the very same teaching environments and learning practices. This contribution reflects on how engendering the curriculum of quantitative methods courses through real-life gender-related topics (like gender-based violence, women’s unpaid labor, gendered welfare-state policies, and women’s presence in political and economic institutions), the use of sex-disaggregated data, and gender-sensitive teaching strategies brings about a virtuous circle: statistics anxiety is significantly reduced while the development of the gender competence equips students to undertake more refined analyses that are also more critical of social inequalities. Gender-sensitive quantitative data enable students to observe the divergence between the rhetorical (formal) and practical (substantive) dimensions of equality while addressing gender-blindness and gender-biases in data analyses offers students the chance to assess the size of the gender gap and to dig into potential explanations that go beyond the variable ‘sex’.
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PS: Political Science & Politics / Volume 49 / Issue 03 / July 2016, pp 550-553 / Copyright © American Political Science Association 2016