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

Burn, Ian ORCID: 0000-0001-5351-5524, Firoozi, Daniel, Ladd, Daniel and Neumark, David (2023) Stereotypes of older workers and perceived ageism in job ads: evidence from an experiment. Journal of Pension Economics and Finance, 22 (4). pp. 1-27.

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Official URL: http://dx.doi.org/10.1017/s1474747222000270

Abstract

<jats:title>Abstract</jats:title> <jats:p>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.</jats:p>

Item Type:	Article
Uncontrolled Keywords:	Age discrimination, age stereotypes, hiring, job search
Divisions:	Faculty of Humanities and Social Sciences > School of Management
Depositing User:	Symplectic Admin
Date Deposited:	10 Jan 2023 10:43
Last Modified:	19 Sep 2023 09:30
DOI:	10.1017/s1474747222000270
Related URLs:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3166966