Grant Peer Review Scoring Data with Criteria Scores
Open accessAbstract
The available data come from a scientific peer review of biomedical applications from a collaborative biomedical research funding program (2014-2017). Three assigned individual reviewers were asked to provide scores and commentary for the following application criteria: Innovation, Approach/Feasibility, Investigator, and Significance (Impact added as scored criteria in 2014). Each of these criteria is scored on a scale from 1.0 (best) to 5.0 (worst) with a 0.1 gradation, as well as an Overall Score (1-5). Asynchronous discussion was allowed, although few changed scores post-discussion. The data includes reviewers’ self-reported expertise scores (1 is high expertise) relative to each proposal reviewed, and reviewer/PI demographics. A total of 72 applications (“Standard” or “Pilot”) were reviewed in 3 review cycles. The success rate was 34-38%. Standard projects received a maximum of $450k over 3 years, Pilot projects received $200k max direct costs over 2 years. Application scores indicate where each application falls among all practically possible applications in comparison with the ideal standard of quality from a perfect application. No live panel discussion takes place in this review mechanism; the final proposal score is the average of the three reviewers’ scientific merit scores and is the primary factor in deter-mining AIBS funding decisions.
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The AIBS grant review data contains a complete set of applications from three rounds of an ongoing intramural collaborative biomedical research program for 2014-2017.
“Our AIBS grant review data (Gallo, 2021) contains a complete set of applications from three rounds of an ongoing intramural collaborative biomedical research program for 2014-2017.”
From When Zero May Not Be Zero: A Cautionary Note on the Use of Inter-Rater Reliability in Evaluating Grant Peer Review (2021) · cites this paper as Gallo, 2021
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Erosheva, E. A., Martinková, P., & Lee, C. J. (2021) · Journal of the Royal Statistical Society Series A: Statistics in Society · doi:10.1111/rssa.12681 · Cited by 28 · see citing works
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Martinková, P., Hladká, A., & Netík, J. (2016) · doi:10.32614/cran.package.shinyitemanalysis · Cited by 5 · see citing works
Refinement: Measuring informativeness of ratings in the absence of a gold standard
Grant, S., Meilă, M., Erosheva, E. A., & Lee, C. J. (2022) · British Journal of Mathematical and Statistical Psychology · doi:10.1111/bmsp.12268 · Cited by 2 · see citing works
- Authors
- Gallo, S.
- Corresponding author
- Gallo, Stephen
- ORCID
- Gallo, Stephen
- Venue
- figshare
- Publisher
- figshare
- Published
- 2021
- OpenAlex
- W4394153829
- Cited by
- 2
- References
- 0
- Citations by year
- 2022: 1 · 2021: 1
- Type
- dataset
- Language
- en
- Open access
- green
- figshare.com
- Licence
- Locations
- Figshare (submittedVersion, cc-by)
- Figshare (cc-by)
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Research, Science, and Academia
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › scientometrics and bibliometrics research
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Psychology Research and Bibliometrics
- Keywords
- peer review, research funding, biomedical research, innovation, feasibility, significance, reviewer expertise, pilot project, scientific merit
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