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Completed STANDARD GRANT National Science Foundation (US)

Factors Relating to Successful Recruitment of Women in Information Technology Jobs

$4.07M USD

Funder National Science Foundation (US)
Recipient Organization University of Minnesota-Twin Cities
Country United States
Start Date Apr 01, 2022
End Date Apr 18, 2025
Duration 1,113 days
Number of Grantees 2
Roles Principal Investigator; Co-Principal Investigator
Data Source National Science Foundation (US)
Grant ID 2151311
Grant Description

Science, technology, engineering, and mathematics (STEM) fields are critical drivers of economic growth and national competitiveness. Yet women remain underrepresented in many STEM fields, which has dramatic, negative consequences both for equality and for creativity and innovation, which often benefit from diverse perspectives. This award develops knowledge that increases women’s representation in STEM fields, focusing on information technology (IT).

The research is organized around two projects. Project 1 examines the characteristics of IT jobs, as described in job advertisements, that increase women’s likelihood of applying. Project 2 examines whether legislation requiring medium-term, employer-paid maternity leave changes women’s likelihood of applying to jobs and companies’ likelihood of interviewing them.

The findings inform companies regarding the job descriptions that attract female applicants and policymakers regarding the design of parental-leave policies.

This award includes two projects aimed at promoting women’s representation in STEM fields. It uses large scale data from an e-recruiting platform—including ~6 million applications to ~20,000 IT job advertisements posted by ~13,000 companies—that allows tracking of women’s progress through the hiring funnel. Project 1 identifies characteristics of job advertisements that increase the likelihood of women applying, using natural language processing and machine learning.

Findings from this project expand the literature on women’s workforce participation, specifically regarding the job descriptions that appeal to women. Since prior work uses a deductive approach, it has necessarily considered only a small set of potentially relevant characteristics. This award instead uses an inductive approach to build theory, leveraging “big” data to uncover relationships that are hard to hypothesize a priori.

Project 2 uses an event study to examine the effects of legislation mandating medium-term employer-paid maternity leave. Findings from this project expand the literature on women’s workforce participation, specifically regarding policy interventions.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

All Grantees

University of Minnesota-Twin Cities

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