Measuring scholarly performance using comprehensive standardized research-teaching (RT) score

Abstract University faculty members and participants in scientific competitions are typically evaluated based on metrics derived from their published works and other relevant academic activities. However, designing a robust mathematical algorithm to process bibliometric information is challenging, and accessible computer codes are often scarce. Consequently, evaluation committees may resort to improvised, mathematically inadequate, poorly standardized, and overly simplistic evaluation methods, which can yield unfair and not-transparent outcomes. This paper introduces a novel algorithm, the “ RT-score ”, designed to assess and rank the research and teaching performance of a group of academics. The RT-score builds upon the “ C-score ”, which is currently used to generate the “ Stanford/Elsevier World Top 2% Most Influential Scientists ” list. The RT-score incorporates several complementary bibliometric indicators, including productivity (number of publications), impact (citations), and the involvement of the individual researcher in the published works. The RT-score also emphasizes the most recent and impactful publications while incorporating parameters that account for variations in the number of articles and citation density across different scientific disciplines, funding, and other pertinent aspects. Finally, it combines these metrics with a measure of teaching experience and other academic activities. The RT-score aims to address key recommendations from DORA, CoARA, and the Leiden Manifesto concerning research assessment reform. The supplement provides a MATLAB code that implements the proposed algorithm.

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Publication Details

Journal
Scientometrics
Published
2025-04-21
DOI
https://doi.org/10.1007/s11192-025-05317-y
Citations
3
Primary Topic
scientometrics and bibliometrics research
Type
article
Field-Weighted Citation Impact
4.20

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article

Measuring scholarly performance using comprehensive standardized research-teaching (RT) score

Nicola Scafetta
3 citations
Scientometrics
scientometrics and bibliometrics research
4.20
article

Measuring scholarly performance using comprehensive standardized research-teaching (RT) score

Nicola Scafetta
article en
3 citations

Abstract

Abstract University faculty members and participants in scientific competitions are typically evaluated based on metrics derived from their published works and other relevant academic activities. However, designing a robust mathematical algorithm to process bibliometric information is challenging, and accessible computer codes are often scarce. Consequently, evaluation committees may resort to improvised, mathematically inadequate, poorly standardized, and overly simplistic evaluation methods, which can yield unfair and not-transparent outcomes. This paper introduces a novel algorithm, the “ RT-score ”, designed to assess and rank the research and teaching performance of a group of academics. The RT-score builds upon the “ C-score ”, which is currently used to generate the “ Stanford/Elsevier World Top 2% Most Influential Scientists ” list. The RT-score incorporates several complementary bibliometric indicators, including productivity (number of publications), impact (citations), and the involvement of the individual researcher in the published works. The RT-score also emphasizes the most recent and impactful publications while incorporating parameters that account for variations in the number of articles and citation density across different scientific disciplines, funding, and other pertinent aspects. Finally, it combines these metrics with a measure of teaching experience and other academic activities. The RT-score aims to address key recommendations from DORA, CoARA, and the Leiden Manifesto concerning research assessment reform. The supplement provides a MATLAB code that implements the proposed algorithm.

ScientometricsVol. 130(5)
University of Naples Federico II (IT)
Università degli Studi di Napoli Federico II
Openalex Percentile: Top 6%
scientometrics and bibliometrics research
4.20
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