Gender and Racial Disparities in Postdoctoral Hiring

How can data science reveal racial & gender discrimination in hiring for postdoctoral fellowships?

ABSTRACT

As the market for postdoctoral positions has become a filter for faculty hiring, so too has its potential to generate disparities by race and gender. Yet little is known about postdoctoral hiring processes, and the extent to which they are influenced by race and gender biases. This project will use detailed data on postdoctoral recruitments in STEM fields at 10 research-intensive universities to test for disparities by gender and race in the evaluation of job applicants’ qualifications and their outcomes in the hiring processes.

Project Lead

Kimberlee Shauman

University of California-Davis

GOALS & RESEARCH QUESTIONS

The goal of this study is a systematic analysis of the postdoctoral hiring process that addresses the research question: Are women and underrepresented minority (URM) scholars disadvantaged in attaining STEM postdoctoral positions because they are less likely to apply for those positions or because their qualifications are evaluated less positively than equally qualified male and non-URM scholars?

METHODS

Quantitative analysis of structured and text-based data

CONTRIBUTION TO PROJECT GOALS

By identifying gender and racial disparities in the evaluation of STEM scholars and in their outcomes in postdoctoral recruitments, this project will raise awareness of the presence and impact of such biases, and identify targets for interventions aimed at increasing equity, inclusion and diversity in STEM education and employment.

FOCUS AREA WITHIN GRADUATE EDUCATION

Transition from graduate education to postdoctoral positions

INVESTIGATORS

Kimberlee Shauman, Department of Sociology, University of California, Davis

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