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α: calibrated so average coauthorship-adjusted count equals average raw count
We study ageist stereotypes reflected in job-ad language and age discrimination in hiring, exploiting job-ad text and evidence on age discrimination from a correspondence study. We develop and use methods from computational linguistics and machine learning. We find that language related to stereotypes of older workers sometimes predicts hiring discrimination against older men. This is the case for all three categories of age stereotypes we consider—health, personality, and skill. For women, we find that age stereotypes about personality predict differential hiring by age. The evidence for men is quite consistent with the industrial psychology literature on age stereotypes.