Could bibliometrics reveal top science and technology achievements and researchers? The case for evaluatology-based science and technology evaluation

Guoxin Kang , Wanling Gao , Lei Wang , Chunjie Luo , Hainan Ye , Qian He , Shaopeng Dai , Jianfeng Zhan
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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 (EC), encompassing nine 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 EC, 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 to demonstrate the effectiveness of our science and technology evaluatology. The case study highlights its practical application and efficacy in identifying significant achievements and researchers that otherwise cannot be identified by using bibliometrics.
文献计量学能否揭示顶尖科技成果和研究人员?基于评价学的科技评价案例
通过利用统计方法分析书目数据,文献计量学在确定最重要的科技成果和研究人员方面面临固有的局限性。为了克服这一挑战,我们提出了一种基于评价学的科技评价方法。这种方法的核心是扩展评价条件(EC)的概念,包括从一个领域衍生出来的九个关键要素。我们定义了四种关系,根据其映射的扩展 EC 要素及其时间和引文联系来说明各种成果之间的联系。在扩展 EC 下的关系中,评估人员可以通过仔细处理混杂变量的影响,有效地比较这些成就。我们建立了一个真实世界的评估系统,其中包含一整套成就,每项成就都映射到扩展 EC 的若干组成部分。在芯片技术或开源技术等特定领域内,我们构建了一个完美的评价模型,该模型可以在真实世界评价体系的基础上,根据四种关系准确追踪所有成果的演变和发展。在完美评价模型的基础上,我们提出了四轮规则,利用四种关系剔除不重要的成果。通过这一过程,我们建立了一个务实的评价模型,有效地捕捉到了基本成就,成为特定时间段内特定领域内 N 项顶级成就的精选集。我们介绍了一个关于前 100 项芯片成就的案例研究,以展示我们的科技评估方法的有效性。该案例研究强调了其在识别重要成果和研究人员方面的实际应用和功效,而这些成果和研究人员是无法通过文献计量学识别的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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