Measuring the match between evaluators and evaluees: Cognitive distances between panel members and research groups at the journal level

TL;DR

This paper introduces two quantitative methods to measure the cognitive distance between evaluators and research groups based on their publication journals, enhancing evaluation accuracy.

Contribution

It presents two novel approaches, barycenter and SAPV, for assessing evaluator-evaluee match using journal similarity, refining previous Web of Science-based methods.

Findings

Both methods effectively measure cognitive distances.

Bootstrapping provides confidence intervals for the distances.

Application to real evaluation data demonstrates practical utility.

Abstract

When research groups are evaluated by an expert panel, it is an open question how one can determine the match between panel and research groups. In this paper, we outline two quantitative approaches that determine the cognitive distance between evaluators and evaluees, based on the journals they have published in. We use example data from four research evaluations carried out between 2009 and 2014 at the University of Antwerp. While the barycenter approach is based on a journal map, the similarity-adapted publication vector (SAPV) approach is based on the full journal similarity matrix. Both approaches determine an entity's profile based on the journals in which it has published. Subsequently, we determine the Euclidean distance between the barycenter or SAPV profiles of two entities as an indicator of the cognitive distance between them. Using a bootstrapping approach, we determine confidence intervals for these distances. As such, the present article constitutes a refinement of a previous proposal that operates on the level of Web of Science subject categories.