Investigation of Partition Cells as a Structural Basis Suitable for Assessments of Individual Scientists
Nadine Rons

TL;DR
This study evaluates whether partition cells, formed by intersecting subject categories, better reflect individual scientists' publication records and citation impacts than broader subject categories, aiding in more accurate performance assessments.
Contribution
It demonstrates that partition cells more closely match individual scientists' publication distributions and citation patterns than traditional broad subject categories.
Findings
Partition cells align better with scientists' publication distributions.
Differences in citation metrics are smaller between adjacent partition cells.
Partition cells outperform broader categories in representing specialized publication records.
Abstract
Individual, excellent scientists have become increasingly important in the research funding landscape. Accurate bibliometric measures of an individual's performance could help identify excellent scientists, but still present a challenge. One crucial aspect in this respect is an adequate delineation of the sets of publications that determine the reference values to which a scientist's publication record and its citation impact should be compared. The structure of partition cells formed by intersecting fixed subject categories in a database has been proposed to approximate a scientist's specialty more closely than can be done with the broader subject categories. This paper investigates this cell structure's suitability as an underlying basis for methodologies to assess individual scientists, from two perspectives: (1) Proximity to the actual structure of publication records of individual…
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Taxonomy
Topicsscientometrics and bibliometrics research
