Explaining the Mathematics Gender Gap: The Role of Stereotypes

Abstract

Descriptive stereotypes such as “girls are not good at mathematics” or prescriptive stereotypes, that is, fixed views about women’s societal roles, can explain the persistent gender gap in mathematics. Stereotypes lower girls’ beliefs, expectations, and incentives to put forth effort, and can constrain girls’ choices in male-dominated high-paying careers that are math-intensive and that require strong math skills. This gap slows progress toward gender equality in the labor market and hinders productivity and economic growth. Policy interventions to alleviate the negative impacts of descriptive stereotypes aim to prevent girls from internalizing socially constructed behaviors aligned with prevalent gender stereotypes regarding the innate mathematical abilities of boys and girls. Boosting girls’ confidence in their math skills includes introducing them to female role models, such as women math teachers, using gender-neutral language, and providing textbooks and other teaching materials that challenge gender stereotypes. A different set of policies focuses on altering the environment in which girls learn, rather than modifying their beliefs. By adjusting the testing methods (such as reducing the level of competition) or adapting the instructional approach to better align with the learning style of girls, it is possible to create an environment that enables more girls to achieve their maximum potential and to accurately assess their math abilities and interests, rather than simply their test-taking or classroom performance. However, interventions that aim to modify the beliefs and attitudes of girls and women ex post, as well as those that seek to alter the environment, may not work in the long term because they reinforce preexisting stereotypes and operate within the constraints of those stereotypes. For instance, while modifying the testing environment may result in higher grades for girls, it may not necessarily alter the perception that girls are incapable of excelling in math. In some cases, these interventions may even have negative consequences. Encouraging girls to “lean in” and behave like boys, for example, can lead to unequal, unjust, and inefficient outcomes because the benefits (economic returns) of doing so are lower or even negative for girls in light of existing gender stereotypes. One popular and affordable approach to combating gender stereotypes involves addressing (unconscious) biases among teachers, parents, and peers through initiatives such as unconscious bias training and self-reflection on biases. The underlying premise is that by increasing awareness of their own (unconscious) biases, individuals will engage their more conscious, non-gender-stereotypical thinking processes. However, such behavioral interventions can sometimes have unintended consequences and result in backlash, and their effectiveness may vary significantly depending on the context, so that their external validity is often called into question. The recognition of the adaptable nature of both conscious and unconscious stereotypes has led to progress in economics, with the development of social learning and information-based theories. Interventions resulting from these models can effectively counteract prescriptive stereotypes that limit girls’ education to certain fields based on societal expectations of gender roles. However, prescriptive gender stereotypes are often based on biased beliefs about the innate abilities of girls and women. Overcoming deeply ingrained descriptive stereotypes about innate abilities of boys and girls is a fruitful avenue for future economics research and can help close the gender performance gap in mathematics.