Clotilde Napp (PNAS Nexus, November 2023)
Gender stereotypes contribute to gender imbalances, and analyzing their variations across countries is important for understanding and mitigating gender inequalities. However, measuring stereotypes is difficult, particularly in a cross-cultural context. Word embeddings are a recent useful tool in natural language processing that permits the measurement of collective gender stereotypes embedded in a society. In this work, we used word embedding models pre-trained on large text corpora from more than 70 different countries to examine how gender stereotypes vary across countries. We considered stereotypes associating men with careers and women with family, as well as those associating men with math or science and women with arts or liberal arts.
Relying on two different sources (Wikipedia and Common Crawl), we found that these gender stereotypes are all significantly more pronounced in the text corpora of more economically developed and more individualistic countries. Our analysis suggests that more economically developed countries, while being more gender-equal along several dimensions, also have stronger gender stereotypes. Public policy aiming at mitigating gender imbalances in these countries should take this feature into account. Additionally, our analysis sheds light on the “gender equality paradox,” i.e., the fact that gender imbalances in a large number of domains are paradoxically stronger in more developed/gender-equal/individualistic countries. In our framework, gender biases about careers, math, and science are all stronger in the text corpora of more economically developed and individualistic countries.
Gender stereotypes harm people of both genders—and society more broadly—by steering and sometimes limiting people to behaviors, roles, and activities linked with their gender. Widely shared stereotypes include the assumption that men are more central to professional life while women are more central to domestic life. Other stereotypes link men with math and science and women with arts and liberal arts.
Perhaps surprisingly, research has shown that countries with higher economic development, individualism, and gender equality tend to also have more pronounced gender differences in several domains, a phenomenon known as the gender equality paradox. We suggest caution in interpreting the results, which are based on big data analysis in an international context and may involve various underlying mechanisms. The cause of this pattern remains to be established with certainty. Nevertheless, it echoes theoretical work suggesting that in societies where beliefs about the inherent inequality of men and women have declined, beliefs about the equality but inherent differences of men and women may have emerged to replace older hierarchical ideas.
Another explanation, which is not mutually exclusive with the previous explanation, is that the biased associations reflect existing gender differences in behaviors that are stronger in wealthy countries. The presence of gender stereotypes in the online text corpora used to train AI could reinforce these stereotypes in artificial intelligence models.