Symptoms versus Root Causes: A Needed Structural Shift in Academia to Help Early Careers
Name
GhaffXuLarsonHawley2018-Note.pdf
Description
Accepted version
Size
61.84 KB
Format
Adobe PDF
Checksum (MD5)
31c646c9e09d48c1f77be5e2fa8c49ea
Author(s)
Ghaffarzadegan, Navid
Xu, Ran
Larson, Richard Charles
Hawley, Joshua D
Date Issued
August 27, 2018
Journal
BioScience
Publisher
Oxford University Press
Citation
Ghaffarzadegan, Navid et al. "Symptoms versus Root Causes: A Needed Structural Shift in Academia to Help Early Careers." BioScience, 68, 10 (October 2018): 744–745 © The Authors 2018
Version
Author's final manuscript
Abstract
Early career scientists in most fields—especially in biomedical sciences—are facing major challenges: The average age of first time NIH grant recipients is rising; many early career scientists spend 3 or more years in low-paid and overworked temporary postdoc positions; thousands interested in academia may never land academic positions; and serious mental health issues challenge many graduate students (Alberts et al. 2014, Levecque et al. 2017, Andalib et al. 2018). Various ameliorative policies have been suggested. In a recent article in BioScience, Beans (2018) emphasized the importance of broadening PhD education and discussing career options outside of academia in order to train and attract students for nonacademic jobs—points that many other scholars in biomedical and life sciences have made (e.g., Fenster and Dudash 2018). In a recent NASEM report (2018), seven corrective policy initiatives were offered, including capping postdoctoral positions at 3 years, supporting permanent research positions with higher pay in academia, requiring projects to support career development of postdocs through allocating specific funding (referred as the postdoc tax), and—increasing federal funding. There are some valuable arguments in this report, but none appears to address academic-system structural change. Rather, the main focus is on tinkering with policies related to the population of newly minted PhDs.
MIT Department
Massachusetts Institute of Technology. Institute for Data, Systems, and Society
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1093/biosci/biy092
