{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/research-impact-evaluation-based-on-effective","title":"Research impact evaluation based on effective authorship contribution sensitivity: h-leadership index","arxiv_id":"2503.18236","date":"2025-03-23","proceeding":null,"authors":["Hardik A. Jain","Rohitash Chandra"],"abstract":"The evaluation of a researcher's performance has traditionally relied on various bibliometric measures, with the h-index being one of the most prominent. However, the h-index only accounts for the number of citations received in a publication and does not account for other factors such as the number of authors or their specific contributions in collaborative works. Therefore, the h-index has been placed on scrutiny as it has motivated academic integrity issues where non-contributing authors get authorship merely for raising their h-index. In this study, we comprehensively evaluate existing metrics in their ability to account for authorship contribution by their position and introduce a novel variant of the h-index, known as the h-leadership index. The h-leadership index aims to advance the fair evaluation of academic contributions in multi-authored publications by giving importance to authorship position beyond the first and last authors, motivated by Stanford's ranking of the top 2 \\% of world scientists. We assign weighted citations based on a modified complementary unit Gaussian curve, ensuring that the contributions of middle authors are appropriately recognised. We apply the h-leadership index to analyse the top 50 researchers across the Group of 8 (Go8) universities in Australia, demonstrating its potential to provide a more balanced assessment of research performance. We provide open-source software for extending the work further.","url_abs":"https://arxiv.org/abs/2503.18236v5","url_pdf":"https://arxiv.org/pdf/2503.18236v5.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"research-impact-evaluation-based-on-effective","repo_url":"https://github.com/nepython/metrics","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}