# Are numerical scores important for grant proposals' evaluation? A cross sectional study

## TL;DR

This study examines if removing numerical scores in grant proposal evaluations affected the language used in reviewer comments.

## Contribution

The study investigates the impact of removing numerical scores on the linguistic characteristics of reviewer comments in grant evaluations.

## Key findings

- Reviewer comments for proposal strengths were objective and positive, while weaknesses were cold and objective.
- Linguistic variables explained only a small proportion of variance between 2019 and 2020 comments.
- Removing numerical scores did not significantly change the linguistic characteristics of the comments.

## Abstract

Background: In the evaluation of research proposals, reviewers are often required to provide their opinions using various forms of quantitative and qualitative criteria. In 2020, the European Commission removed, for the Marie Skłodowska-Curie Actions (MSCA) Innovative Training Networks (ITN) funding scheme, the numerical scores from the individual evaluations but retained them in the consensus report. This study aimed to assess whether there were any differences in reviewer comments’ linguistic characteristics after the numerical scoring was removed, compared to comments from 2019 when numerical scoring was still present.

Methods: This was an observational study and the data were collected for the Marie Skłodowska-Curie Actions (MSCA) Innovative Training Networks (ITN) evaluation reports from the calls of 2019 and 2020, for both individual and consensus comments and numerical scores about the quality of the research proposal on three evaluation criteria: Excellence, Impact and Implementation. All comments were analyzed using the Linguistic Inquiry and Word Count (LIWC) program.

Results: For both years, the comments for proposal’s strengths were written in a style that reflects objectivity, clout, and positive affect, while in weaknesses cold and objective style dominated, and that pattern remained stable across proposal status and research domains. Linguistic variables explained a very small proportion of the variance of the differences between 2019 and 2020 (McFadden R
2=0.03).

Conclusions: Removing the numerical scores was not associated with the differences in linguistic characteristics of the reviewer comments. Future studies should adopt a qualitative approach to assess whether there are conceptual changes in the content of the comments.