Globally, careers in science, technology, engineering and math (STEM) remain male-dominated with little female representation. One way to change this could be to simply soften the language of job postings, results from a new experiment suggest. Softer language in job postings instils confidence of a greater match among job seekers.
In the study, researchers Lisa Abraham and Alison Stein, conduct an experiment using 616 job postings for Uber’s U.S. corporate offices. These postings, which were open for a four-month period starting August 2018, were viewed by 60,000 job applicants and included roles in fields ranging from finance to design. As part of the experiment, researchers altered job postings without compromising on the core job description. The alterations included removal of optional qualifications such as “preferred” before PhD; deletion of adjectives such as “excellent” before skill-set descriptions; and broadening words such as “fluency” to more general terms such as “experience” to indicate knowledge of language skills
At an overall level, simplified job postings witnessed a 7% increase in the number of responding applicants. While applications from women candidates went up by 5%, male applications increased by 7%. Crucially, the authors find that ads where the language was simplified reduced the gender skill gap by generating more applications from equally-credentialed women.
The study highlights the importance of perceptions among job seekers when they assess their suitability for a position. The researchers argue that the choice of words used to signal the expected qualifications for a job may be a dissuading factor and may lead to under-reporting of skills, especially among women candidates.
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