Remaining problems with the "New Crown Indicator" (MNCS) of the CWTS

TL;DR

This paper critiques the CWTS's

Contribution

It proposes replacing the mean with the median in the MNCS to improve robustness and aligns it with percentile-based approaches for better accuracy.

Findings

The mean is inappropriate for skewed citation distributions.

Using the median can enhance measurement precision.

Percentile-based metrics are a viable alternative.

Abstract

In their article, entitled "Towards a new crown indicator: some theoretical considerations," Waltman et al. (2010; at arXiv:1003.2167) show that the "old crown indicator" of CWTS in Leiden was mathematically inconsistent and that one should move to the normalization as applied in the "new crown indicator." Although we now agree about the statistical normalization, the "new crown indicator" inherits the scientometric problems of the "old" one in treating subject categories of journals as a standard for normalizing differences in citation behavior among fields of science. We further note that the "mean" is not a proper statistics for measuring differences among skewed distributions. Without changing the acronym of "MNCS," one could define the "Median Normalized Citation Score." This would relate the new crown indicator directly to the percentile approach that is, for example, used in the Science and Engineering Indicators of US National Science Board (2010). The median is by definition equal to the 50th percentile. The indicator can thus easily be extended with the 1% (= 99th percentile) most highly-cited papers (Bornmann et al., in press). The seeming disadvantage of having to use non-parametric statistics is more than compensated by possible gains in the precision.