基于文献计量学的计量学：它们的定义是什么？如何研究它们？
Bibliometrics-based heuristics: What is their definition and how can they be studied?
摘要：
当科学家们研究他们感兴趣的现象时，他们会应用合理的方法，并将工作建立在理论思考的基础上。相比之下，当他们的研究成果被评估时，基本的科学标准似乎并不重要。相反，简单的文献计量指标（即，出版物和引用计数），自相矛盾的是，既被广泛使用和批评，没有任何方法和理论框架，将有助于地面使用和批评。然而，Bornmann和Marewski [1]最近提出了这样一个框架。他们开发了基于文献计量学的文献计量学（BBHs），基于快速和节俭的决策方法[2]，以概念上理解和实证研究研究的定量评估，以及有效地训练文献计量学的最终用户（例如，科学管理人员、科学家）。启发式是一种决策策略，它使用部分可用信息而忽略其余信息。通过利用任务环境的统计结构，它们可以帮助做出准确，快速，轻松和具有成本效益的决策，而不会产生权衡。由于其简单性，物流易于理解和沟通，提高了决策过程的透明度。在这篇评论中，我们解释了几个BBH，并讨论了如何在实践中使用这种方法（以资助计划申请人的评估为例）。此外，我们还概述了为什么智能化可以表现良好，以及如何他们和他们的适合任务环境可以进行研究。在指出BBH研究的潜力和风险，研究不足，盲目使用文献计量学，这篇评论有助于使研究评估更加科学。
英文摘要：
When scientists study the phenomena they are interested in, they apply sound methods and base their work on theoretical considerations. In contrast, when the fruits of their research is being evaluated, basic scientific standards do not seem to matter. Instead, simplistic bibliometric indicators (i.e., publications and citation counts) are, paradoxically, both widely used and criticized without any methodological and theoretical framework that would serve to ground both use and critique. Yet, Bornmann and Marewski [1] proposed such a framework recently. They developed bibliometrics-based heuristics (BBHs) based on the fast-and-frugal heuristics approach [2] to decision making, in order to conceptually understand and empirically investigate the quantitative evaluation of research as well as to effectively train end-users of bibliometrics (e.g., science managers, scientists). Heuristics are decision strategies that use part of the available information and ignore the rest. By exploiting the statistical structure of task environments, they can aid to make accurate, fast, effortless, and cost-efficient decisions without that trade-offs are incurred. Because of their simplicity, heuristics are easy to understand and communicate, enhancing the transparency of decision processes. In this commentary, we explain several BBHs and discuss how such heuristics can be employed in practice (using the evaluation of applicants for funding programs as one example). Furthermore, we outline why heuristics can perform well, and how they and their fit to task environments can be studied. In pointing to the potential of research on BBHs and to the risks that come with an under-researched, mindless usage of bibliometrics, this commentary contributes to make research evaluation more scientific.
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