Autor: |
Kathryn Anne Edwards, Hannah Acheson-Field, Stephanie Rennane, Melanie A. Zaber |
Jazyk: |
angličtina |
Rok vydání: |
2023 |
Předmět: |
|
Zdroj: |
Scientific Reports, Vol 13, Iss 1, Pp 1-9 (2023) |
Druh dokumentu: |
article |
ISSN: |
2045-2322 |
DOI: |
10.1038/s41598-023-34809-1 |
Popis: |
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. |
Databáze: |
Directory of Open Access Journals |
Externí odkaz: |
|
Nepřihlášeným uživatelům se plný text nezobrazuje |
K zobrazení výsledku je třeba se přihlásit.
|