Despite decades of positive messaging to encourage women and girls to pursue education tracks and careers in STEM, women continue to fall far below their male counterparts in these fields. A new study at Carnegie Mellon University examined 25 languages to explore the gender stereotypes in language that undermine efforts to support equality across STEM career paths. The results are available in the August 3^rd issue of Nature Human Behavior.

Molly Lewis, special faculty at CMU and her research partner, Gary Lupyan, associate professor at University of Wisconsin-Madison, set out to examine the effect of language on career stereotypes by gender. They found that implicit gender associations are strongly predicted by the language we speak. Their work suggests that linguistic associations may be causally related to people’s implicit judgement of what women can accomplish.

[...]“Our study shows that language statistics predict people's implicit biases — languages with greater gender biases tend to have speakers with greater gender biases,” Lupyan said. “The results are correlational, but that the relationship persists under various controls [and] does suggest a causal influence.”