Abstract
This study examines how race, experience, and industry shape callback rates in hiring using the ResumeNames dataset of 4,066 fictitious resumes. Logistic regression and decision tree models reveal that race is the strongest predictor of callbacks: White-sounding names received more responses than Black-sounding names, even with equal or stronger qualifications. Black applicants needed significantly more experience to match the success rates of White applicants. Transport and Communication was the only industry where Black applicants saw higher callback rates, likely due to its historical ties to back-facing labor roles. Exploratory analysis also suggested a racial double standard in how resume quality and employment gaps are evaluated. The findings show the need for further research into how bias, algorithms, quality, and experience alignment intersect in hiring.
Advisor
Long, Colby
Department
Statistical and Data Sciences
Recommended Citation
Robinson, Kayla, "Working Twice as Hard to Get Half as Much: A Critical Analysis of Callback Rates by Race, Industry, and Experience" (2025). Senior Independent Study Theses. Paper 11359.
https://openworks.wooster.edu/independentstudy/11359
Disciplines
Data Science
Keywords
Resumes, Resume names, Hiring bias, Discrimination, African-American, Black
Publication Date
2025
Degree Granted
Bachelor of Arts
Document Type
Senior Independent Study Thesis
© Copyright 2025 Kayla Robinson