来源：《自然》
刊登日期：2021年5月3日
Research institutions are under increasing pressure to make decisions faster, with fewer resources. The science of science can provide information on how to organize research effectively to meet societal needs.
研究机构面临越来越大的压力，需要用更少的资源更快地做出决定。科学的科学可以提供关于如何有效地组织研究以满足社会需要的信息。
The field uses quantitative tools to understand the discovery system. It complements disciplines such as the history, philosophy and sociology of science, and relies on century-old bibliometric techniques that exploit the traces left by publications, grants and patents. Findings can illuminate trends, and inform policies for hiring, funding, training and more.
该领域使用量化工具来理解科学发现机制。它补充了历史、哲学和科学社会学等学科，并依赖于具有百年历史的，且利用出版物、拨款和专利留下的痕迹的文献计量技术。研究结果可以阐明趋势、并影响招聘、资助、培训等方面的政策。
In book The Science of Science, two scientists present an introduction to a new part of this activity. They frame it as a big-data approach, but it is perhaps better understood as applying the tools of network science to study science. Their book is full of interesting anecdotes, and an accessible style. But its narrow view leads to worrying interpretations.
在《科学的科学》一书中，两位科学家介绍了这一学科的一个新兴部分。他们将其表达为一种大数据方法，但或许更好的理解是将网络科学的工具应用于研究科学。他们的书充满了有趣的轶事，以及通俗易懂的风格。但其狭隘的观点导致了令人担忧的解读。
They describe the science of science as emerging, without engaging with its historical or interdisciplinary foundations. In fact, the term was used in the 1963 book Little Science, Big Science, in which science historian Derek de Solla Price advocated that the community “turn the tools of science on science itself” — and has been used in major scientometric publications since the 1970s.
他们将科学的科学描述为新兴的学科，没有涉及其历史或跨学科的基础。事实上，这个术语曾在1963年出版的《小科学，大科学》一书中使用过，在这本书中，科学历史学家德里克·德·索拉·普莱斯主张科学界“将科学工具应用于科学本身”——自20世纪70年代以来，这个术语一直被用于主要的科学计量学出版物中。
In the style of a management handbook, they promise to help scientists to navigate their careers, arguing that the science of science aims to maximize individuals’ odds of success. They suggest that their insights will help administrators to spot the people who will bring the greatest benefit to a department, and they encourage funding agencies to identify those most likely to be high performing.
他们以一本管理手册的风格，承诺帮助科学家规划自己的学术生涯，声称科学的科学旨在最大限度地提高个人成功的几率。他们表示，他们的见解将帮助管理者发现谁将为院系带来最大的利益，他们怂恿资助机构找出最可能表现出色的人。
But the research community has moved from promoting indicators such as the journal impact factor and h-index to criticizing them. These measures often do more harm than good, creating what economists Margit Osterloh and Bruno Frey call a “taste for rankings”, rather than a “taste for science”. They lead scholars to sausage-slice — publish data in increments to gather as many papers as possible — or worse, to compete.
但学术界已经从推崇期刊影响因子和h指数等指标转向批评它们。这些指标往往弊大于利，催生了经济学家玛吉特•奥斯特洛和布鲁诺•弗雷所说的“对排名的偏好”，而不是“对科学的偏好”。这些指标引导学者们“以切香肠的方式”——以增量的方式发表数据，以发表尽可能多的论文——或者变得更糟，学术研究变成了竞争。
These concerns have been promoted through consensus statements such as the Leiden Manifesto and the Declaration on Research Assessment, which has been signed by thousands of institutions and more than 17,000 individuals. The documents call on the community to end reliance on poorly constructed indicators that can lead to structural biases such as racism, sexism and classism. Policymakers are implored to remember Goodhart’s law: when a measure becomes a target, it ceases to be a good measure.