Kean Study Finds Age-Biased Language in Nearly 1 in 10 Job Ads
A job advertisement seeking a “digital native” or a “high energy” employee may communicate more than the qualities an employer values. For Kean University researcher Gata Goumou ’26, those phrases were part of a study into how seemingly ordinary language can signal preferences for younger or older workers.
Goumou and his collaborators found age-biased language in nearly 10% of the 4,369 job postings they analyzed. Although that language was less widespread than earlier research suggested, its presence raises questions: How do applicants respond to age-coded wording, and could removing it affect older candidates’ intentions to apply?
“The goal was to figure out which group of people, when applying for jobs, are discriminated against,” Goumou said.
Goumou began the work as an undergraduate at Kean, collaborating with Assistant Professor Irina Gioaba, Ph.D., as well as fellow students Jasmin Langomas and Sherwin Prince. Their work was presented at Kean Research Days 2026.
Their project, Decoding Discrimination: Ageist Language in Job Postings, examined thousands of advertisements from four U.S.-based job boards. The team used artificial intelligence platforms to collect and clean the data, then analyzed job descriptions using a dictionary of age-related stereotypes developed from management and organizational psychology research.
Phrases such as “technologically savvy,” “high energy,” “adaptable” and “digital native” were examined for potential associations with age stereotypes. Postings in education, retail and aquatics had some of the highest rates of age-biased language.
“What drove me to research was that I wanted to challenge myself and just continue to learn,” Goumou said. “I think this research was the perfect opportunity to do that and help others.”
For Gioaba, his enthusiasm stood out from the beginning.
“We were looking for computer science students with technical skills,” Gioaba said. “He stood out and was very energetic and enthusiastic about the project. I was very impressed by the work he did.”
Goumou’s undergraduate experience has grown into a new opportunity. After earning a bachelor’s degree in computational science and engineering, Goumou is now conducting new research as a National Science Foundation (NSF) fellow and graduate research assistant at Kean.
He is also pursuing a Master of Science at Kean and taking on a lead role within the NSF research group, gaining experience coordinating and collaborating with other researchers.
Gioaba will continue the next phase of the age-bias research, moving beyond identifying age-coded language to examining applicants’ responses and test whether changing the wording of a job advertisement affects older candidates’ intentions to apply.
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