Michalska-Smith Matthew J, Allesina Stefano
Department of Ecology & Evolution, University of Chicago, Chicago IL, United States of America 60637.
Computation Institute, University of Chicago, Chicago IL, United States of America 60637.
PLoS One. 2017 Jun 1;12(6):e0178074. doi: 10.1371/journal.pone.0178074. eCollection 2017.
Scientists often perceive a trade-off between quantity and quality in scientific publishing: finite amounts of time and effort can be spent to produce few high-quality papers or subdivided to produce many papers of lower quality. Despite this perception, previous studies have indicated the opposite relationship, in which productivity (publishing more papers) is associated with increased paper quality (usually measured by citation accumulation). We examine this question in a novel way, comparing members of the National Academy of Sciences with themselves across years, and using a much larger dataset than previously analyzed. We find that a member's most highly cited paper in a given year has more citations in more productive years than in in less productive years. Their lowest cited paper each year, on the other hand, has fewer citations in more productive years. To disentangle the effect of the underlying distributions of citations and productivities, we repeat the analysis for hypothetical publication records generated by scrambling each author's citation counts among their publications. Surprisingly, these artificial histories re-create the above trends almost exactly. Put another way, the observed positive relationship between quantity and quality can be interpreted as a consequence of randomly drawing citation counts for each publication: more productive years yield higher-cited papers because they have more chances to draw a large value. This suggests that citation counts, and the rewards that have come to be associated with them, may be more stochastic than previously appreciated.
有限的时间和精力可以用于产出少量高质量论文,或者细分用于产出多篇质量较低的论文。尽管有这种看法,但先前的研究表明了相反的关系,即生产力(发表更多论文)与论文质量提高(通常通过引用积累来衡量)相关。我们以一种新颖的方式研究这个问题,将美国国家科学院的成员多年来的情况进行自身对比,并使用了比之前分析的大得多的数据集。我们发现,在给定年份中,一位成员被引用次数最多的论文在生产力较高的年份比在生产力较低的年份有更多的引用。另一方面,他们每年被引用次数最少的论文在生产力较高的年份引用次数较少。为了厘清引用和生产力的潜在分布的影响,我们对通过打乱每位作者在其出版物中的引用次数生成的假设出版记录重复进行分析。令人惊讶的是,这些人为的历史记录几乎完全重现了上述趋势。换句话说,观察到的数量与质量之间的正相关关系可以解释为每个出版物随机抽取引用次数的结果:生产力较高的年份会产生被引用次数更高的论文,因为它们有更多机会抽到一个大的数值。这表明引用次数以及与之相关的奖励可能比之前所认为的更具随机性。