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Should citations be field-normalized in evaluative bibliometrics? An empirical analysis based on propensity score matching

机译:应在评价生物素质化学中进行外部归一化吗?基于倾向得分匹配的实证分析

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Field-normalization of citations is bibliometric standard. Despite the observed differences in citation counts between fields, the question remains how strong fields influence citation rates beyond the effect of attributes or factors possibly influencing citations (FICs). We considered several FICs such as number of pages and number of co-authors in this study. For example, fields differ in the mean number of co-authors (pages), and - on the paper level - the number of co-authors (pages) is related to citation counts. We wondered whether there is a separate field-effect besides other effects (e.g., from numbers of pages and coauthors). To find an answer on the question in this study, we applied inverse-probability of treatment weighting (IPW) which is a variant of the "propensity score matching" approach (an approach which has been introduced for measuring causal effects). Using Web of Science data (a sample of 308,231 articles), we investigated whether mean differences among subject categories in citation rates still remain, even if the subject categories are made comparable in the field-related attributes (e.g., comparable of co-authors, comparable number of pages) by IPW. In a diagnostic step of our statistical analyses, we considered propensity scores as covariates in regression analyses to examine whether the differences between the fields in FICs vanish. The results revealed that the differences did not completely vanish but were strongly reduced. We received similar results when we calculated mean value differences of the fields after IPW representing the causal or unconfounded field effects on citations. However, field differences in citation rates remain. The results point out that field-normalization seems to be a prerequisite for citation analysis and cannot be replaced by the consideration of any set of FICs in citation analyses. (C) 2020 Elsevier Ltd. All rights reserved.
机译:领域 - 引用的归一化是伯格计数标准。尽管在领域之间观察到引文计数的差异,但问题仍然是强大的领域影响引用率超出可能影响引文(FIC)的属性或因素的影响。我们考虑了本研究中的一些法案,如页面数量和共同作者数量。例如,字段在共同作者(页面)的平均数量中不同,以及 - 纸张级别 - 共同作者(页面)的数量与引文计数有关。我们想知道除其他效果外是否存在单独的现场效果(例如,来自页面和共同忠解者)。为了在本研究中找到问题的答案,我们应用了处理加权(IPW)的逆概率,这是“倾向得分匹配”方法的变型(已经引入测量因果效应的方法)。使用科学数据(308,231篇文章的样本),我们调查了引用率的主题类别的平均差异仍然存在,即使在与现场相关的属性中进行了可比性的主题类别(例如,与共同作者相当,可比页面数量)通过ipw。在我们的统计分析的诊断步骤中,我们认为倾向分数作为回归分析中的协变量,以检查FIC中的域之间的差异是否消失。结果表明,差异没有完全消失,但受到强烈减少。当我们计算IPW后,在IPW代表对引用的原因或无束型现场效果的情况下计算平均值差异时,我们收到了类似的结果。但是,引用率的田间差异仍然存在。结果指出,现场标准化似乎是引文分析的先决条件,并且不能通过考虑引用分析中的任何集体组织而替换。 (c)2020 elestvier有限公司保留所有权利。

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