Abstract
A perennial problem in bibliometrics is the appropriate distribution of authorship credit for coauthored publications. Several credit allocation methods and formulas have been introduced, but there has been little empirical validation as to which method best reflects the typical contributions of coauthors. This paper presents a validation of credit allocation methods using a new data set of author-provided percentage contribution figures obtained from the coauthored publications in cumulative PhD theses by authors from three countries that contain contribution statements. The comparison of allocation schemes shows that harmonic counting performs best and arithmetic and geometric counting also perform well, while fractional counting and first author counting perform relatively poorly.
Highlights
The social creation of knowledge and its dissemination as publications is of critical importance to the modern science system
This paper presents a validation of credit allocation methods using a new data set of author-provided percentage contribution figures obtained from the coauthored publications in cumulative PhD theses by authors from three countries that contain contribution statements
The comparison of allocation schemes shows that harmonic counting performs best and arithmetic and geometric counting perform well, while fractional counting and first author counting perform relatively poorly
Summary
The social creation of knowledge and its dissemination as publications is of critical importance to the modern science system. Coauthorship credit is a theoretical concept that refers to the idea that one may conceive of a publication as being associated with a mathematical object with unity value (1.0), on which mathematical operations can be performed. By this transformation the publication’s authors can be credited with relative shares of the whole unit. These shares can be referred to as their respective credits or partial publication equivalents. Because only a few publications state contributions explicitly and numerically, it is crucial in bibliometric practice to use a credit allocation method that is on average in close agreement with typical contributions
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