A Rejoinder on Energy versus Impact Indicators

TL;DR

This paper discusses the limitations of mean-based metrics for skewed citation distributions and introduces the I3 indicator, which uses non-parametric statistics for more accurate impact assessment at the article level.

Contribution

It proposes the Integrated Impact Indicator (I3), a novel non-parametric metric for evaluating scientific impact based on percentiles, addressing issues with traditional mean-based measures.

Findings

I3 allows impact qualification at the article level.

I3 can be aggregated for overall impact assessment.

The paper highlights the inadequacy of mean-based metrics for skewed data.

Abstract

Citation distributions are so skewed that using the mean or any other central tendency measure is ill-advised. Unlike G. Prathap's scalar measures (Energy, Exergy, and Entropy or EEE), the Integrated Impact Indicator (I3) is based on non-parametric statistics using the (100) percentiles of the distribution. Observed values can be tested against expected ones; impact can be qualified at the article level and then aggregated.