数学家、经济学家和生物医学科学家是否比物理学家更能追踪大的主题？
Do Mathematicians, Economists and Biomedical Scientists Trace Large Topics More Strongly Than Physicists?
摘要：
在这项工作中，我们扩展了我们以前的工作在物理学家的大跟踪到其他领域，即数学，经济学和生物医学科学。总的来说，这些结果证实了我们之前的发现，表明所有这些领域的科学家都在追踪大主题。然而，令人惊讶的是，数学领域的研究人员似乎比其他领域的研究人员更有可能追踪大型主题。我们还发现，平均而言，顶级期刊上的论文不太受规模驱动。我们比较了来自美国、德国、日本和中国的研究人员，发现中国研究人员的指数一直较大，这表明在所有这些领域，中国研究人员比其他人更强烈地追踪大主题。进一步的相关性分析显示，每篇论文的作者数量、隶属关系和参考文献数量与论文规模之间存在正相关性--拥有更多作者、隶属关系或参考文献的论文可能更受规模驱动，但有几个有趣且值得注意的例外：在经济学中，参考文献多的论文不一定是大型驱动的，在生物医学科学中，作者多的论文也是如此。我们相信，这些经验发现可能对科学政策制定者有价值。
英文摘要：
In this work, we extend our previous work on largeness tracing among physicists to other fields, namely mathematics, economics and biomedical science. Overall, the results confirm our previous discovery, indicating that scientists in all these fields trace large topics. Surprisingly, however, it seems that researchers in mathematics tend to be more likely to trace large topics than those in the other fields. We also find that on average, papers in top journals are less largeness-driven. We compare researchers from the USA, Germany, Japan and China and find that Chinese researchers exhibit consistently larger exponents, indicating that in all these fields, Chinese researchers trace large topics more strongly than others. Further correlation analyses between the degree of largeness tracing and the numbers of authors, affiliations and references per paper reveal positive correlations -- papers with more authors, affiliations or references are likely to be more largeness-driven, with several interesting and noteworthy exceptions: in economics, papers with more references are not necessary more largeness-driven, and the same is true for papers with more authors in biomedical science. We believe that these empirical discoveries may be valuable to science policy-makers.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
