Mapping scientists’ career trajectories in the survey of doctorate recipients using three statistical methods

Edwards, K.A., Acheson-Field, H., Rennane, S. et al. Mapping scientists’ career trajectories in the survey of doctorate recipients using three statistical methods. Sci Rep 13, 8119 (2023). https://doi.org/10.1038/s41598-023-34809-1

9 Pages Posted: 11 Oct 2021 Last revised: 20 May 2023

See all articles by Kathryn Anne Edwards

Kathryn Anne Edwards

RAND Corporation - Pardee RAND Graduate School

Hannah Acheson-Field

Abt Associates

Stephanie Rennane

RAND Corporation

Melanie Zaber

RAND Corporation

Date Written: May 19, 2023

Abstract

This paper investigates to what extent there is a ‘traditional’ career among individuals with a Ph.D. in a science, technology, engineering, or math (STEM) discipline. We use longitudinal data that follows the first 7–9 years of post-conferral employment among scientists who attained their degree in the U.S. between 2000 and 2008. We use three methods to identify a traditional career. The first two emphasize those most commonly observed, with two notions of commonality; the third compares the observed careers with archetypes defined by the academic pipeline. Our analysis includes the use of machine-learning methods to find patterns in careers; this paper is the first to use such methods in this setting. We find that if there is a modal, or traditional, science career, it is in non-academic employment. However, given the diversity of pathways observed, we offer the observation that traditional is a poor descriptor of science careers.

Keywords: STEM pipeline, STEM career, tenure-track

JEL Classification: J24, I23,

Suggested Citation

Edwards, Kathryn and Acheson-Field, Hannah and Rennane, Stephanie and Zaber, Melanie, Mapping scientists’ career trajectories in the survey of doctorate recipients using three statistical methods (May 19, 2023). Edwards, K.A., Acheson-Field, H., Rennane, S. et al. Mapping scientists’ career trajectories in the survey of doctorate recipients using three statistical methods. Sci Rep 13, 8119 (2023). https://doi.org/10.1038/s41598-023-34809-1, Available at SSRN: https://ssrn.com/abstract=3939090 or http://dx.doi.org/10.2139/ssrn.3939090

Kathryn Edwards (Contact Author)

RAND Corporation - Pardee RAND Graduate School ( email )

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HOME PAGE: http://www.kathrynanneedwards.com

Hannah Acheson-Field

Abt Associates ( email )

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Stephanie Rennane

RAND Corporation ( email )

1776 Main Street
P.O. Box 2138
Santa Monica, CA 90407-2138
United States

Melanie Zaber

RAND Corporation ( email )

1776 Main Street
P.O. Box 2138
Santa Monica, CA 90407-2138
United States

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