A new system of authorship best assessment

Bibliometric indices, such as the h-index, number of citations and the impact factor, have become popular tools for assessing the scientific impact of researchers, institutions, and journals. However, these indices have been subject to criticism for their limitations and potential biases.

One major limitation of bibliometric indices is their reliance on citation data as a measure of scientific impact. While citation counts can be a useful indicator of the influence of a publication or researcher within a given field, they do not necessarily reflect the quality or originality of the research. For example, a highly cited article may simply restate existing knowledge or confirm established findings, rather than presenting new and innovative ideas.

Another challenge of using bibliometric indices to assess individual researchers is the difficulty of attributing credit and determining the relative contributions of co-authors in multi-author publications. In many fields, collaborative research is common and papers with multiple authors are the norm. This makes it difficult to assess the true impact of an individual author's contributions to a particular publication. As a result, using bibliometric indices such as the h-index or citation counts as a proxy for individual impact may not provide an accurate or unbiased reflection of the contributions of each author.

In addition, the use of bibliometric indices as a metric for individual achievement may incentivize authors to prioritize the quantity of publications over the quality of their contributions to a specific paper. This can lead to situations in which the impact of the individual author's contributions may be diluted or overlooked, as the focus is placed on overall citation counts or h-index.

In this study carried out by Gianluca De Rubeis , Michele Porcu , Mauro Giovanni Carta , Alessandra Serra and Antonella Balestrieri, we propose a new metric model based on the authorship position of authors, which can be useful for identifying the real authorial contribution and overall bibliometric impact in a less biased manner.

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