Article ; Online: Mapping scientists' career trajectories in the survey of doctorate recipients using three statistical methods.
2023 Volume 13, Issue 1, Page(s) 8119
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 ...
| 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. |
|---|---|
| Language | English |
| Publishing date | 2023-05-19 |
| Publishing country | England |
| Document type | Journal Article |
| ZDB-ID | 2615211-3 |
| ISSN | 2045-2322 ; 2045-2322 |
| ISSN (online) | 2045-2322 |
| ISSN | 2045-2322 |
| DOI | 10.1038/s41598-023-34809-1 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
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