'Author Contribution Details' and not 'Authorship Sequence' as a merit to determine credit: A need to relook at the current Indian practice

A systematic scoping review of the ethics of Contributor Role Ontologies and Taxonomies

Contributor Role Ontologies and Taxonomies (CROTs) provide a standard list of roles to specify individual contributions to research. CROTs most common application has been their inclusion alongside author bylines in scholarly publications. With the recent uptake of CROTs among publishers -particularly the Contributor Role Taxonomy (CRediT)- some have anticipated a positive impact on ethical issues regarding the attribution of credit and responsibilities, but others have voiced concerns about CROTs shortcomings and ways they could be misunderstood or have unintended consequences. Since these discussions have never been consolidated, this review collated and explored published viewpoints about the ethics of CROTs. After searching Ovid Medline, Scopus, Web of Science, and Google Scholar, 30 papers met the inclusion criteria and were analyzed. We identified eight themes and 20 specific issues related to the ethics of CROTs and provided four recommendations for CROT developers, custodians, or others seeking to use CROTs in their workflows, policy and practice: 1) Compile comprehensive instructions that explain how CROTs should be used; 2) Improve the coherence of used terms, 3) Translate roles in languages other than English, 4) Communicate a clear vision about future development plans and be transparent about CROTs' strengths and weaknesses. We conclude that CROTs are not the panacea for unethical attributions and should be complemented with initiatives that support social and infrastructural transformation of scholarly publications.

Passive Contribution of ChatGPT to Scientific Papers

Arguably ChatGPT jeopardizes the integrity and validity of the academic publications instead of ethically facilitating them. ChatGPT can apparently fulfill a portion of one of the four authorship criteria set by the International Committee of Medical Journal Editors (ICMJE), i.e., "drafting." However, the authorship criteria by ICMJE must all be collectively met, not singly or partially. Many published manuscripts or preprints have credited ChatGPT by including it in the author byline, and the academic publishing enterprise seems to be unguided on how to handle such manuscripts. Interestingly, PLoS Digital Health removed ChatGPT off a paper which had ChatGPT listed initially in the author byline of the preprint version. Revised publishing policies are, thus, promptly required to guide a consistent stance regarding ChatGPT or similar artificial content generators. Publishing policies must accord among publishers, preprint servers ( https://asapbio.org/preprint-servers ), universities, and research institutions worldwide and across different disciplines. Ideally, considering any declaration of the contribution of ChatGPT to writing any scientific article should be recognized as publishing misconduct immediately and be retracted. Meanwhile, all parties involved in the scientific reporting and publishing must be educated about how ChatGPT fails to meet the essential authorship criteria, so that no author must submit a manuscript with ChatGPT contributing as a "co-author." Meanwhile, using ChatGPT for writing laboratory reports or short summaries of experiments may be acceptable, but not for academic publishing or formal scientific reporting.

Rating a Researcher’s Cumulative Scholarly Output Based on Their Sequence Numbers in Multi-Authored Publications

As the academic world yields an ever-increasing research output in terms of journal papers, conference proceedings, and books, the rating of published works and authors becomes imperative. All the big citation databases and search engines are currently using cumulative output indices, such as h-index, i10-index, and g-index, which do not consider the number of co-authors or the researcher’s sequence number in the authors list of a publication. In this context, the article presents a novel computational approach for evaluating a researcher’s scholarly output by taking into account the total number of co-authors, the sequence number of the researcher in the authors list, and the number of citations received per year by an article. Arithmetic progression is applied to quantify the credit for each co-author of a publication. The respective credits of a researcher are then accumulated for all their publications to obtain the rating. The method yields a truer value of the researcher’s impact in terms of their scholarly activities. A global implementation of the metric presented in this work will curb the unethical practice of including the names of non-contributing researchers in the authors list and expecting reciprocity in return.