Competition between gender and racial discriminations. The reason of the understatement of gender discriminations in quantitative surveys?

Maud Lesné, Institut National d'Études Démographiques (INED)

Discrimination remains difficult to measure in quantitative surveys. Gender discrimination in particular is almost invisible. As a result, data collected doesn’t tend to show the high levels of inequality between men and women that we know exists. The percentage of gender discrimination reported in a recent French survey illustrates this understatement. Only 3.5% of female respondents report having experienced gender discrimination during the past 5 years. The aim of this paper is to study gender discrimination reporting, using an intersectional approach which combines both gender and race. This approach will enable us to separate gender and racial discrimination statements and to evaluate the potential competition between the two. First, we examine the figures for gender, racial and intersectional (combining gender and race) discrimination reported in survey women from four different racial groups (the mainstream population born in France with both parents born in France, descendants of immigrants from South Europe, North Africa and sub-Saharan Africa). Then we look at how both types of discrimination are articulated in terms of the race of the respondents. Why do women declare so little gender discrimination? How does belonging to a visible minority influence their perception? Does the saliency of racial discrimination contribute to the downplaying of gender discrimination? Is the perceived reason for discrimination always considered exclusive, or do respondents identify intersectional discrimination? Finally, we use logistic regression to identify the factors which increase the probability of women declaring gender discrimination. We will see that the low reporting of gender discrimination can’t only be explained by a competition effect with racial discrimination. We observe an emerging trend of multiple discrimination reporting. In order to understand the understatement of gender discrimination, alternate hypotheses must be explored.

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Presented in Poster Session 2