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Predicting research excellence at the individual level: The importance of publication rate, top journal publications, and top 10% publications in the case of early career mathematicians

机译:在个人水平上预测卓越研究:对于早期职业数学家而言,发表率,顶级期刊出版物和前10%出版物的重要性

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The purpose of this study was to examine the relationship between publication rate, top journal publications and excellence during the first eight years of the career, and how well publication rate, top journal publications and highly cited publications during the first four years of the career can predict whether an author attain excellence in the fifth to the eighth year. The dataset consisted of publication track records of 406 early career mathematicians in the sub-field of number theory collected from the MathSciNet database. Logistic regression and dominance analysis was applied to the data. The major conclusions were (1) publication rate had a positive effect on excellence during the first eighth years of the career. However, those who publish many articles in top journals, which implicitly require a high publication count, had an even higher probability of attaining excellence. These results suggest that publishing in top journals is very important in the process of attaining excellence in the early career in addition to publishing many papers; and (2) a dominance analysis indicated that the number of top journal publications and highly cited publications during the first four years of the career were the most important predictors of who will attain excellence in the later career. The results are discussed in relation to indicator development and science policy. (C) 2018 Elsevier Ltd. All rights reserved.
机译:这项研究的目的是研究职业生涯前八年的出版率,顶级期刊出版物和卓越水平之间的关系,以及职业生涯前四年的出版率,顶级期刊出版物和被高引用的出版物能达到多少水平预测作者在第五年到第八年是否达到卓越水平。该数据集由从MathSciNet数据库收集的数论子域中的406位早期职业数学家的出版记录组成。逻辑回归和优势分析应用于数据。主要结论是(1)在职业生涯的前八年中,出版率对卓越表现产生了积极影响。但是,那些在顶级期刊上发表许多文章而隐含地需要大量发表的人,获得卓越成就的可能性甚至更高。这些结果表明,除了发表大量论文外,顶尖期刊的发表对于在早期职业中获得卓越的过程非常重要。 (2)优势分析表明,在职业生涯的前四年中,顶级期刊出版物和被高度引用的出版物的数量是谁在以后的职业中将获得卓越成就的最重要的预测指标。讨论了有关指标制定和科学政策的结果。 (C)2018 Elsevier Ltd.保留所有权利。

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