Contribution Based Author Categorization to Calculate Author Performance Index - Rahman, Mohammad Tariqur; Regenstein, Joe Mac; Abu Kassim, Noor Lide; Karim, Muhammad Manjurul (Taylor & Fracis, 2020)
Despite the widely used author contribution criteria, unethical authorship practices such as guest, ghost, and honorary authorship remains largely unsolved. We have identified six major reasons by analyzing 78 published papers addressing unethical authorship practice. Those are lack of: (i) awareness about and (ii) compliance with authorship criteria, (iii) universal definition and scope for determining authorship, (iv) common mechanisms for positioning an author in the list, (v) quantitative measures of intellectual contribution; and (vi) pressure to publish. As a possible measure to control unethical practice, we have evaluated the possibility to adopt an author categorization scheme – proposed according to the common understanding of how first-, co-, principal-, or corresponding- author is perceived. Based on an online opinion survey, the proposed scheme was supported by ~80% of the respondents (n=370). The impact of the proposed categorization was then evaluated using a novel mathematical tool to measure “Author Performance Index (API)” that can be higher for those who might have authored more papers as primary and/or principal authors than those as coauthors. Hence, if adopted, the proposed author categorization scheme together with the API would provide a better way to evaluate the credit of an individual as a primary and principal author.