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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2504.20081 |
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| _version_ | 1866912369639161856 |
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| author | Vishwakarma, Rahul Banerjee, Sinchan |
| author_facet | Vishwakarma, Rahul Banerjee, Sinchan |
| contents | Citation metrics serve as the cornerstone of scholarly impact evaluation despite their well-documented vulnerability to inflation through self-citation practices. This paper introduces the Self-Citation Adjusted Index (SCAI), a sophisticated metric designed to recalibrate citation counts by accounting for discipline-specific self-citation patterns. Through comprehensive analysis of 5,000 researcher profiles across diverse disciplines, we demonstrate that excessive self-citation inflates traditional metrics by 10-20%, potentially misdirecting billions in research funding. Recent studies confirm that self-citation patterns exhibit significant gender disparities, with men self-citing up to 70% more frequently than women, exacerbating existing inequalities in academic recognition. Our open-source implementation provides comprehensive tools for calculating SCAI and related metrics, offering a more equitable assessment of research impact that reduces the gender citation gap by approximately 8.5%. This work contributes to the paradigm shift toward transparent, nuanced, and equitable research evaluation methodologies in academia, with direct implications for funding allocation decisions that collectively amount to over $100 billion annually in the United States alone. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_20081 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Billions at Stake: How Self-Citation Adjusted Metrics Can Transform Equitable Research Funding Vishwakarma, Rahul Banerjee, Sinchan Digital Libraries Citation metrics serve as the cornerstone of scholarly impact evaluation despite their well-documented vulnerability to inflation through self-citation practices. This paper introduces the Self-Citation Adjusted Index (SCAI), a sophisticated metric designed to recalibrate citation counts by accounting for discipline-specific self-citation patterns. Through comprehensive analysis of 5,000 researcher profiles across diverse disciplines, we demonstrate that excessive self-citation inflates traditional metrics by 10-20%, potentially misdirecting billions in research funding. Recent studies confirm that self-citation patterns exhibit significant gender disparities, with men self-citing up to 70% more frequently than women, exacerbating existing inequalities in academic recognition. Our open-source implementation provides comprehensive tools for calculating SCAI and related metrics, offering a more equitable assessment of research impact that reduces the gender citation gap by approximately 8.5%. This work contributes to the paradigm shift toward transparent, nuanced, and equitable research evaluation methodologies in academia, with direct implications for funding allocation decisions that collectively amount to over $100 billion annually in the United States alone. |
| title | Billions at Stake: How Self-Citation Adjusted Metrics Can Transform Equitable Research Funding |
| topic | Digital Libraries |
| url | https://arxiv.org/abs/2504.20081 |