Help Really Wanted? The Impact of Age Stereotypes in Job Ads on Applications from Older Workers

Burn, Ian; Firoozi, Daniel; Ladd, Daniel; Neumark, David

doi:10.3386/w30287

2022

DOI: 10.3386/w30287

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Help Really Wanted? The Impact of Age Stereotypes in Job Ads on Applications from Older Workers

Ian Burn¹,

Daniel Firoozi²,

Daniel Ladd³

et al.

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Stereotypes of older workers and perceived ageism in job ads: evidence from an experiment

Burn

Firoozi²,

Ladd³

et al. 2023

Journal of Pension Economics and Finance

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We explore whether ageist stereotypes in job ads are detectable using machine-learning methods measuring the linguistic similarity of job-ad language to ageist stereotypes identified by industrial psychologists. We then conduct an experiment to evaluate whether this language is perceived as biased against older workers searching for jobs. We find that job-ad language classified by the machine-learning algorithm as closely related to ageist stereotypes is perceived by experimental subjects as biased against older job seekers. These methods could potentially help enforce anti-discrimination laws by using job ads to predict or identify employers more likely to be engaging in age discrimination.

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Stereotypes of older workers and perceived ageism in job ads: evidence from an experiment

Burn

Firoozi²,

Ladd³

et al. 2023

Journal of Pension Economics and Finance

Self Cite

View full text Add to dashboard Cite

show abstract

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Help Really Wanted? The Impact of Age Stereotypes in Job Ads on Applications from Older Workers

Cited by 1 publication

References 0 publications

Stereotypes of older workers and perceived ageism in job ads: evidence from an experiment

Stereotypes of older workers and perceived ageism in job ads: evidence from an experiment

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