Incentivized Resume Rating is a new technique to study hiring bias
Rate resumes of hypothetical candidates created by researchers
Match with real job seekers based on recruiter preferences
Receive real opportunities in return for serving as characteristic bank for resumes
Based on our research…
There is no positive preference for female or minority candidates.
Even though… 90% of employers claim that increasing both gender and racial diversity factor into their hiring decisions.
In fact, in STEM fields, female and minority candidates need to outperform their white male counterparts.
Non-white males need to earn 0.27 GPA points more and white females need to earn 0.29 GPA points more than a white male to receive the same rating.
Firms should be cautious about unintentionally excluding candidates whose financial situations require paid work.
An internship is worth 0.21 GPA points. A work-for-money summer job is statistically the same as having nothing on the resume.
Female and minority candidates get less credit than their white male counterparts for the same prestigious internship experience.
White male candidates get the largest benefit from a prestigious internship, with a boost of 0.53 GPA points.
Firms may falsely believe female and minority candidates are harder to recruit due to other firms’ diversity preferences.
Firms believe female and minority candidates are less likely to accept their offers. But there is no positive preference for female or minority candidates in the data.
The research presented here was published as the lead article in the November 2019 issue of the AER, which you can access below.
What can our research do for your firm?
Audit internal hiring practices
IRR can help firms diagnose their hiring practices: hiring managers use the IRR tool, then results used for education
Identify areas for improvement
Can compare the preferences of firm leaders to those “on the ground” and find gaps between intention and practice
Partner with Wharton researchers
Opportunities to partner with Wharton on research to understand hiring decisions and firm preferences
Provide clean data for ML algorithms
Beware machine learning algorithms trained on historical data: IRR provides an opportunity to train on “clean data”
In The News
Research: How Companies Committed to Diverse Hiring Still Fail
“Ultimately, our research allows a peek under the hood of big prestigious firms, where we found a surprising amount of race and gender bias given that these firms claim to be seeking diversity. To answer the call of the current moment, firms need to take a hard look at their hiring processes and face up the fact that they may not be as diversity-loving in practice as they are in intention.”
Op-Ed: It will take a lot more than diversity training to end racial bias in hiring
“Bias in résumé screening is just one part of the problem. Eliminating bias in employment will require rethinking every aspect of the hiring and promotion process. Our research shows that good intentions and pro-diversity goals aren’t enough.“
Uncovering Bias: A New Way to Study Hiring Can Help
“While testing this new method – incentivized resume rating — with companies recruiting Penn students, they uncovered evidence of how bias seeps into the hiring process of some of the world’s top firms, many of which have a stated commitment to diversity.“
Penn researchers offer new way to expose hiring bias
“Wanting diversity isn’t enough… You have to build practices that help you overcome powerful biases…. The employers who said, ‘Yes, we care about diversity, want diverse candidates’ were discriminating in multiple ways”
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