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定量研究评估:使用指标对抗被操纵的指标。

Quantitative research assessment: using metrics against gamed metrics.

机构信息

Departments of Medicine, of Epidemiology and Population Health, of Biomedical Data Science, and of Statistics, and Meta-Research Innovation Center at Stanford (METRICS), Stanford University, SPRC, MSOB X306, 1265 Welch Rd, Stanford, CA, 94305, USA.

SInnoPSis (Science and Innovation Policy and Studies) Unit, Department of Economics, University of Cyprus, Nicosia, Cyprus.

出版信息

Intern Emerg Med. 2024 Jan;19(1):39-47. doi: 10.1007/s11739-023-03447-w. Epub 2023 Nov 3.

Abstract

Quantitative bibliometric indicators are widely used and widely misused for research assessments. Some metrics have acquired major importance in shaping and rewarding the careers of millions of scientists. Given their perceived prestige, they may be widely gamed in the current "publish or perish" or "get cited or perish" environment. This review examines several gaming practices, including authorship-based, citation-based, editorial-based, and journal-based gaming as well as gaming with outright fabrication. Different patterns are discussed, including massive authorship of papers without meriting credit (gift authorship), team work with over-attribution of authorship to too many people (salami slicing of credit), massive self-citations, citation farms, H-index gaming, journalistic (editorial) nepotism, journal impact factor gaming, paper mills and spurious content papers, and spurious massive publications for studies with demanding designs. For all of those gaming practices, quantitative metrics and analyses may be able to help in their detection and in placing them into perspective. A portfolio of quantitative metrics may also include indicators of best research practices (e.g., data sharing, code sharing, protocol registration, and replications) and poor research practices (e.g., signs of image manipulation). Rigorous, reproducible, transparent quantitative metrics that also inform about gaming may strengthen the legacy and practices of quantitative appraisals of scientific work.

摘要

定量文献计量指标被广泛用于和滥用在研究评估中。一些指标在塑造和奖励数百万科学家的职业生涯方面具有重要意义。鉴于它们的声望,在当前的“发表或灭亡”或“获得引用或灭亡”的环境中,它们可能被广泛操纵。本综述考察了几种操纵行为,包括基于作者、基于引用、基于编辑和基于期刊的操纵以及完全伪造的操纵。讨论了不同的模式,包括没有值得称赞的功劳而大量署名的论文(赠品署名)、将过多的人归因于过多的作者的团队工作(信用的意大利香肠切片)、大量的自我引用、引文农场、H 指数操纵、新闻(编辑)裙带关系、期刊影响因子操纵、论文工厂和虚假内容论文,以及对于需要严格设计的研究的虚假大规模发表。对于所有这些操纵行为,定量指标和分析可能有助于检测和正确看待它们。定量指标的投资组合也可以包括最佳研究实践的指标(例如,数据共享、代码共享、方案注册和复制)和较差的研究实践的指标(例如,图像操纵的迹象)。严格、可重复、透明的定量指标,也可以告知操纵行为,从而加强对科学工作的定量评估的传统和实践。

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