Science Workforce Analysis: A Review and a Reflection on Structural Barriers to Improve Research Workforce Career, Performance, and Diversity

10 Pages Posted: 12 Feb 2022

See all articles by Navid Ghaffarzadegan

Navid Ghaffarzadegan

Virginia Tech - Grado Department of Industrial and Systems Engineering (ISE)

Date Written: December 5, 2021

Abstract

Science workforce is the population that directly deals with the advancement of science or engineering fields through basic or applied research. It includes different groups of scientists such as university professors, researchers in the public or private sectors, university students and postdoctoral fellows. It also includes people who design research projects or oversee research activities in administrative positions of science teams such as research team managers or principal investigators of research grants. Analyzing the current and future state of science workforce is strategically important for the economic growth of any country. This has been a common theme of nine years of my collaboration with Drs. Richard Larson of MIT and Joshua Hawley of the Ohio State University. Our efforts benefited from contributions of several excellent students and postdocs in our institutions. Here, I review the basic concepts related to science workforce and science workforce analysis, provide a background about our projects, and list the main findings. The review points to structural barriers for improving the career of researchers, their performance, and diversity as well as fostering the performance of the entire system as affected by governmental, institutional, and individual policies.

Keywords: Science workforce, science workforce analysis, higher education, science policy, diversity, labor policy, science team, team science, complex systems, systems thinking

JEL Classification: J08

Suggested Citation

Ghaffarzadegan, Navid, Science Workforce Analysis: A Review and a Reflection on Structural Barriers to Improve Research Workforce Career, Performance, and Diversity (December 5, 2021). Available at SSRN: https://ssrn.com/abstract=3978147 or http://dx.doi.org/10.2139/ssrn.3978147

Navid Ghaffarzadegan (Contact Author)

Virginia Tech - Grado Department of Industrial and Systems Engineering (ISE) ( email )

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