Could Bibliometrics Reveal Top Science and Technology Achievements and Researchers? The Case for Evaluatology-based Science and Technology Evaluation

• URL: http://arxiv.org/abs/2408.12158v1
• Date: Thu, 22 Aug 2024 06:57:46 GMT
• Title: Could Bibliometrics Reveal Top Science and Technology Achievements and Researchers? The Case for Evaluatology-based Science and Technology Evaluation
• Authors: Guoxin Kang, Wanling Gao, Lei Wang, Chunjie Luo, Hainan Ye, Qian He, Shaopeng Dai, Jianfeng Zhan,
• Abstract summary: We present an evaluatology-based science and technology evaluation methodology. At the heart of this approach lies the concept of an extended evaluation condition, encompassing eight crucial components derived from a field. Within a specific field like chip technology or open source, we construct a perfect evaluation model that can accurately trace the evolution and development of all achievements.
• Score: 5.203905488272949
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: By utilizing statistical methods to analyze bibliographic data, bibliometrics faces inherent limitations in identifying the most significant science and technology achievements and researchers. To overcome this challenge, we present an evaluatology-based science and technology evaluation methodology. At the heart of this approach lies the concept of an extended evaluation condition, encompassing eight crucial components derived from a field. We define four relationships that illustrate the connections among various achievements based on their mapped extended EC components, as well as their temporal and citation links. Within a relationship under an extended evaluation condition, evaluators can effectively compare these achievements by carefully addressing the influence of confounding variables. We establish a real-world evaluation system encompassing an entire collection of achievements, each of which is mapped to several components of an extended EC. Within a specific field like chip technology or open source, we construct a perfect evaluation model that can accurately trace the evolution and development of all achievements in terms of four relationships based on the real-world evaluation system. Building upon the foundation of the perfect evaluation model, we put forth four-round rules to eliminate non-significant achievements by utilizing four relationships. This process allows us to establish a pragmatic evaluation model that effectively captures the essential achievements, serving as a curated collection of the top N achievements within a specific field during a specific timeframe. We present a case study on the top 100 Chip achievements which highlights its practical application and efficacy in identifying significant achievements and researchers that otherwise can not be identified by using bibliometrics.

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