Literature DB >> 32675837

Administrative Discretion in Scientific Funding: Evidence from a Prestigious Postdoctoral Training Program.

Donna K Ginther1, Misty L Heggeness2,3.   

Abstract

The scientific community is engaged in an active debate on the value of its peer-review system. Does peer review actually serve the role we envision for it-that of helping government agencies predict what ideas have the best chance of contributing to scientific advancement? Many federal agencies use a two-step review process that includes programmatic discretion in selecting awards. This process allows us to determine whether success in a future independent scientific-research career is more accurately predicted by peer-review recommendations or discretion by program staff and institute leaders. Using data from a prestigious training program at the National Institute of Health (NIH), the Ruth L. Kirschstein National Research Service Award (NRSA), we provide evidence on the efficacy of peer review. We find that, despite all current claims to the contrary, the existing peer-review system works as intended. It more closely predicts high-quality science and future research independence than discretion. We discover also that regression discontinuity, the econometric method typically used to examine the effect of scientific funding, does not fit many scientific-funding models and should only be used with caution when studying federal awards for science.

Entities:  

Keywords:  biomedical workforce; innovation; peer review; scientific funding

Year:  2020        PMID: 32675837      PMCID: PMC7365616          DOI: 10.1016/j.respol.2020.103953

Source DB:  PubMed          Journal:  Res Policy        ISSN: 0048-7333


  28 in total

1.  Perspective: is NIH funding the "best science by the best scientists"? A critique of the NIH R01 research grant review policies.

Authors:  Leslie C Costello
Journal:  Acad Med       Date:  2010-05       Impact factor: 6.893

2.  Opinion: Addressing systemic problems in the biomedical research enterprise.

Authors:  Bruce Alberts; Marc W Kirschner; Shirley Tilghman; Harold Varmus
Journal:  Proc Natl Acad Sci U S A       Date:  2015-02-17       Impact factor: 11.205

3.  Why the US science and engineering workforce is aging rapidly.

Authors:  David M Blau; Bruce A Weinberg
Journal:  Proc Natl Acad Sci U S A       Date:  2017-03-27       Impact factor: 11.205

4.  Ancient texts to PubMed: a brief history of the peer-review process.

Authors:  P R Farrell; L Magida Farrell; M K Farrell
Journal:  J Perinatol       Date:  2016-11-17       Impact factor: 2.521

5.  Low agreement among reviewers evaluating the same NIH grant applications.

Authors:  Elizabeth L Pier; Markus Brauer; Amarette Filut; Anna Kaatz; Joshua Raclaw; Mitchell J Nathan; Cecilia E Ford; Molly Carnes
Journal:  Proc Natl Acad Sci U S A       Date:  2018-03-05       Impact factor: 11.205

6.  Careers of an elite cohort of U.S. basic life science postdoctoral fellows and the influence of their mentor's citation record.

Authors:  David G Levitt
Journal:  BMC Med Educ       Date:  2010-11-15       Impact factor: 2.463

7.  The Influence of Peer Reviewer Expertise on the Evaluation of Research Funding Applications.

Authors:  Stephen A Gallo; Joanne H Sullivan; Scott R Glisson
Journal:  PLoS One       Date:  2016-10-21       Impact factor: 3.240

8.  NIH peer review percentile scores are poorly predictive of grant productivity.

Authors:  Ferric C Fang; Anthony Bowen; Arturo Casadevall
Journal:  Elife       Date:  2016-02-16       Impact factor: 8.140

9.  The acceptability of using a lottery to allocate research funding: a survey of applicants.

Authors:  Mengyao Liu; Vernon Choy; Philip Clarke; Adrian Barnett; Tony Blakely; Lucy Pomeroy
Journal:  Res Integr Peer Rev       Date:  2020-02-03

10.  Research Funding: the Case for a Modified Lottery.

Authors:  Ferric C Fang; Arturo Casadevall
Journal:  mBio       Date:  2016-04-12       Impact factor: 7.867

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