A new study digs into 25 languages to explore the gender stereotypes in language that undermine efforts to support equality across science, technology, engineering, and mathematics careers.
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.
The researchers set out to examine the effect of language on career stereotypes by gender. They found that the language we speak strongly predicts implicit gender associations. Their work suggests that linguistic associations may be causally related to people’s implicit judgement of what women can accomplish.
The results appear in Nature Human Behavior.
“Young children have strong gender stereotypes as do older adults, and the question is, ‘where do these biases come from?'” says first author Molly Lewis, special faculty at Carnegie Mellon University. “No one has looked at implicit language—simple language that co-occurs over a large body of text—that could give information about stereotypical norms in our culture across different languages.”
In general, the team examined how words co-occur with women compared to men. For example, how often is ‘woman’ associated with ‘home,’ ‘children,’ and ‘family,’ where as ‘man’ was associated with ‘work,’ ‘career,’ and ‘business.’
“What’s not obvious is that a lot of information that is contained in language, including information about cultural stereotypes, [occurs not as] direct statements but in large-scale statistical relationships between words,” says senior author Gary Lupyan, an associate professor at University of Wisconsin-Madison.
“Even without encountering direct statements, it is possible to l ..
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