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The impact factor fallacy

zhpd55 添加于 2017/3/23 11:26:31  336次阅读 | 0次推荐 | 0个评论

The use of the journal impact factor (JIF) as a measure for the quality of individual manuscripts and the merits of scientists has faced significant criticism in recent years. We add to the current criticism in arguing that such an application of the JIF in policy and decision making in academia is based on false beliefs and unwarranted inferences. To approach the problem, we use principles of deductive and inductive reasoning to illustrate the fallacies that are inherent to using journal based metrics for evaluating the work of scientists. In doing so, we elaborate that if we judge scientific quality based on the JIF or other journal based metrics we are either guided by invalid or weak arguments or in fact consider our uncertainty about the quality of the work and not the quality itself.

作 者:Frieder Michel Paulus, Nicole Cruz, Soeren Krach
期刊名称: BioRXiv
期卷页: Posted February 20, 2017. 第卷 第期 页
学科领域:管理综合 » 宏观管理与政策 » 科技管理与政策
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原文链接:http://biorxiv.org/content/early/2017/02/20/108027
DOI: https://doi.org/10.1101/108027
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备 注: Eugene Garfield’s pioneering work on the journal impact factor (IF) fundamentally changed how institutions evaluate scientific quality. What was initially sought to help make decisions about journal subscriptions today influences academia far beyond the stocking of libraries. Scientists may receive grants, bonuses, and tenure depending on the perceived impact of the journals in which they publish their research. This practice has been widely criticized because the IF is a poor indicator for the number of citations of a specific journal article, and motivating scientists based on citation rates and journal IFs might have unwanted side effects, potentially jeopardizing the reliability and credibility of science. Using IFs for such purposes also results in reasoning and argumentation fallacies. Policies that rely on journal-based metrics for evaluating scientific contributions are either guided by weak or invalid arguments or, in fact, consider the uncertainty about the quality of the science and not the quality itself. In a recent preprint, we have described several of these “impact factor fallacies” by applying ideas from reasoning and argumentation research.
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