The Costs and Benefits of a Modified Biomedical Science Workforce
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Abstract
Analyses of the biomedical research workforce, the biomedical research enterprise and its sustainability have identified a number of threats and offered many solutions to alleviate the problems. While, a number of these solutions have been implemented, one solution that has not been broadly adopted, despite being widely recommended, is to increase the number of staff scientists and reduce dependency on trainees. The perceived impediment of this is the cost. This paper explores the costs associated with laboratory personnel and the benefits, in terms of productivity, associated with different positions in the workforce. The results of this cost-benefit analysis depend upon the values assigned to different metrics of productivity by individuals and institutions. If first and senior author publications are the most important metrics of productivity, a trainee dependent workforce is much more cost effective. If total publications is the most valued metric of productivity, the cost effectiveness of trainee and staff scientists is reasonably equitable. This analysis provides data for consideration when making personnel decisions and for the continued discussion of modification of the biomedical research workforce. It also provides insight into the incentives for modification of the workforce at the grass roots, which must be considered by institutions genuinely committed to workforce modification to sustain the biomedical research enterprise.
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This Zenodo record is a permanently preserved version of a PREreview. You can view the complete PREreview at https://prereview.org/reviews/6545824.
This manuscript provides valuble data for for modification considerations of the biomedical research workforce.
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This Zenodo record is a permanently preserved version of a PREreview. You can view the complete PREreview at https://prereview.org/reviews/4047180.
In this preprint, Michael D. Schaller shares a cost-benefit analysis of shifting the balance of the research workforce to include more staff scientists. Proponents of this intervention (myself included) argue this would simultaneously address concerns about overproduction of trainees and also promote more durable institutional knowledge. However, the costs of employing staff scientists seem to present a serious barrier to implementation. As a consequence, an economic analysis of the type presented here is sorely needed. This paper thus represents a valuable contribution to the literature.
Major points
- The benefit calculated may be an underestimate since staff scientists likely affect the …
This Zenodo record is a permanently preserved version of a PREreview. You can view the complete PREreview at https://prereview.org/reviews/4047180.
In this preprint, Michael D. Schaller shares a cost-benefit analysis of shifting the balance of the research workforce to include more staff scientists. Proponents of this intervention (myself included) argue this would simultaneously address concerns about overproduction of trainees and also promote more durable institutional knowledge. However, the costs of employing staff scientists seem to present a serious barrier to implementation. As a consequence, an economic analysis of the type presented here is sorely needed. This paper thus represents a valuable contribution to the literature.
Major points
- The benefit calculated may be an underestimate since staff scientists likely affect the overall productivity of the laboratory. For example, I'd be interested to hear your thoughts on the approach taken by a group analyzing productivity at MIT, which you cite (https://www.sciencedirect.com/science/article/abs/pii/S0048733315000037). Would it be possible to implement this approach with your data?
- In table 5, could citations to all papers be included (not just those for first and senior authors?) Again, since staff scientists might be contributing to the general efficiency of the lab (or, as a manager of a core facility, as a significant fraction of R50 recipients are, they might not be leading research projects at all). It seems important to consider all outputs, not just those with first and senior authorship, and to emphasize this figure (rather than 'primary' publications) throughout the discussion.
Minor points
- It might be helpful for readers to highlight more prominently the use of K99 data to draw conclusions about R50 awardees.
- Would another label (rather than "trainees") be more appropriate for tables that include R50 awardees, as they are not trainees?
- Missing reference: "The workforce in the biological and biomedical sciences in academia in 2018 was comprised of 52,627 predoctoral trainees, 21,533 postdoctoral trainees and 8,250 nonfaculty researchers (ref)"
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