Centre for Science and Technology Studies, Leiden University, Leiden, The Netherlands.
F1000Res. 2020 May 14;9:366. doi: 10.12688/f1000research.23418.2. eCollection 2020.
Most scientometricians reject the use of the journal impact factor for assessing individual articles and their authors. The well-known San Francisco Declaration on Research Assessment also strongly objects against this way of using the impact factor. Arguments against the use of the impact factor at the level of individual articles are often based on statistical considerations. The skewness of journal citation distributions typically plays a central role in these arguments. We present a theoretical analysis of statistical arguments against the use of the impact factor at the level of individual articles. Our analysis shows that these arguments do not support the conclusion that the impact factor should not be used for assessing individual articles. Using computer simulations, we demonstrate that under certain conditions the number of citations an article has received is a more accurate indicator of the value of the article than the impact factor. However, under other conditions, the impact factor is a more accurate indicator. It is important to critically discuss the dominant role of the impact factor in research evaluations, but the discussion should not be based on misplaced statistical arguments. Instead, the primary focus should be on the socio-technical implications of the use of the impact factor.
大多数科学计量学家反对将期刊影响因子用于评估单篇文章及其作者。著名的旧金山研究评估宣言也强烈反对这种使用影响因子的方式。反对在单篇文章层面使用影响因子的论点通常基于统计学考虑。期刊引文分布的偏态在这些论点中起着核心作用。我们对反对在单篇文章层面使用影响因子的统计学论点进行了理论分析。我们的分析表明,这些论点并不能支持不应将影响因子用于评估单篇文章的结论。通过计算机模拟,我们证明在某些条件下,文章获得的引文数量是衡量文章价值的一个比影响因子更准确的指标。然而,在其他条件下,影响因子是一个更准确的指标。重要的是要批判性地讨论影响因子在研究评估中的主导作用,但这种讨论不应基于错误的统计论点。相反,应该主要关注于使用影响因子的社会技术影响。