论文引用的秘密，被揭露了

A new study has revealed an unsettling truth about the citation metrics that are commonly used to gauge scientists' level of impact and influence in their respective fields of research.

一项新的研究揭示了一个令人不安的事实，引用指标通常被用来衡量科学家在各自研究领域的影响力。

Citation metrics indicate how often a scientist's research output is formally referenced by colleagues in the footnotes of their own papers – but a comprehensive analysis of this web of linkage shows the system is compromised by a hidden pattern of behaviour that often goes unnoticed.

引用指标表明科学家的研究成果，在他们自己论文的脚注中被同行正式引用的频率——但是对这一联系网的全面分析表明，系统受到了一种经常被忽视的隐藏行为模式的影响。

Specifically, among the 100,000 most cited scientists between 1996 to 2017, there's a stealthy pocket of researchers who represent "extreme self-citations and 'citation farms' (relatively small clusters of authors massively citing each other's papers)," explain the authors of the new study, led by physician turned meta-researcher John Ioannidis from Stanford University.

具体地说，在1996年至2017年间被引用最多的10万名科学家中，有一个秘密的研究者口袋，他们代表着“极端的自我引用和‘引用农场’(相对较小的一组作者大量引用彼此的论文)，”这项新研究的作者解释说，该研究由从斯坦福大学的内科医生转为元研究员约翰·伊奥尼迪斯。

Ioannidis helps to run Stanford's meta-research innovation centre, called Metrics, which looks at identifying and solving systemic problems in scientific research.

约阿尼迪斯帮助运营斯坦福大学的元研究创新中心(Metrics)，该中心致力于识别和解决科学研究中的系统性问题。

One of those problems, Ioannidis says, is how self-citations compromise the reliability of citation metrics as a whole, especially at the hands of extreme self-citers and their associated clusters.

伊安尼迪斯说，其中一个问题，是自我引文是如何损害引文指标的可靠性的，特别是在极端自我引文者及其相关集群的手中。

"I think that self-citation farms are far more common than we believe," Ioannidis told Nature. "Those with greater than 25 percent self-citation are not necessarily engaging in unethical behaviour, but closer scrutiny may be needed."

“我认为自我引用农场比我们想象的要普遍得多，”约阿尼迪斯告诉《自然》杂志。“那些自我引证率超过25%的人不一定从事不道德的行为，但可能需要更仔细的审查。”
The 25 percent figure that Ioannidis is referring to are those scientists who self-refer 25 percent of the citations that reference their work (or that of their co-authors).

约阿尼迪斯所指的25%的数字是指那些在引用他们的著作(或他们的合著者的著作)的引文中，有25%是自我引用的科学家。

Being one-quarter of your own fan base might seem like a lot of self-citing, but it's not even that uncommon, the study reveals.

研究显示，拥有四分之一的粉丝群似乎是一种自我引证，但这并不罕见。

Among the 100,000 most highly cited scientists for the period of 1996 to 2017, over 1,000 researchers self-cited more than 40 percent of their total citations – and over 8,500 researchers had greater than 25 percent self-citations.

在1996年至2017年10万名被引频次最高的科学家中，超过1000名研究人员的自我引频次占总引频次的40%以上，超过8500名研究人员的自我引频次超过25%。

There's no suggestion that any of these self-citations are necessarily or automatically unethical or unwarranted or self-serving in themselves. After all, in some cases, your own published scientific research may be the best and most relevant source to link to.

没有任何迹象表明，这些自我引用行为中的任何一种是出自不道德的、无根据的或自私自利的。毕竟，在某些情况下，你自己发表的科学研究可能是最好和最相关的链接来源。

But the researchers behind the study nonetheless suggest that the prevalence of extreme cases revealed in their analysis debases the value of citation metrics as a whole – which are often used as a proxy of a scientist's standing and output quality (not to mention employability).

尽管如此，这项研究背后的研究人员表示，在他们的分析中揭示的极端案例的普遍存在，降低了引文指标作为一个整体的价值——这些指标通常被用作科学家地位和产出质量的代表(更不用说就业能力了)。

"With very high proportions of self-citations, we would advise against using any citation metrics since extreme rates of self-citation may herald also other spurious features," the authors write.

作者写道：“由于自我引用的比例非常高，我们建议不要使用任何引用指标，因为极端的自我引用率可能预示着其他虚假特征。”

"These need to be examined on a case-by-case basis for each author, and simply removing the self-citations may not suffice."

“这些需要根据每个作者的具体情况进行检查，仅仅删除自我引用可能还不够。”

It's far from the first time researchers have highlighted serious problems with the way we rate the products of scientific endeavour.

这已经不是研究人员第一次强调我们对科学成果的评估方式存在严重问题。

In recent years, scientists have identified technical flaws hidden within citation systems, revealed shortcomings in how we rank science journals, and uncovered serious concerns about citation solicitations.

近年来，科学家们发现了引文系统中隐藏的技术缺陷，揭示了我们如何对科学期刊进行排名的缺点，并发现了对引文征集的严重担忧。

Others have noticed bizarre citation glitches that shouldn't exist at all, and observed other unsettling systemic trends that cast a shadow over a citation's worth.

其他人注意到一些本不应该存在的奇怪的引文错误，并观察到其他令人不安的系统性趋势，这些趋势给引文的价值蒙上了阴影。
Amidst this mess, Ioannidis and his team hope their new data "will help achieve a more nuanced use of metrics" that enables the community as a whole to more easily identify and curtail the improper impact of self-citations and citation farms.

在这种混乱中，伊奥尼迪斯和他的团队希望他们的新数据“将有助于更细微地使用度量标准”，使整个社区能够更容易地识别和减少自我引文和引文农场的不当影响。

Others, meanwhile, suggest the way to fix this is to get away from quantitative metrics as a whole, and focus instead on a qualitative approach to righting what's wrong here.

与此同时，另一些人则建议，解决这个问题的方法是从整体上摆脱定量度量，而是专注于用定性的方法来纠正这里的错误。

"When we link professional advancement and pay attention too strongly to citation-based metrics, we incentivise self-citation," psychologist Sanjay Srivastava from the University of Oregon, who wasn't involved in the study, told Nature.

俄勒冈大学的心理学家桑杰·斯里瓦斯塔瓦(Sanjay Srivastava)对《自然》杂志表示:“当我们把职业发展和过于关注基于引用的指标联系起来时，我们会鼓励自我引用。”他没有参与这项研究。

"Ultimately, the solution needs to be to realign professional evaluation with expert peer judgement, not to double down on metrics."

“最终，解决方案需要重新调整专业评估与专家同行判断，而不是在指标上加倍。”

The findings are reported in PLOS Biology.

研究结果发表在《公共科学图书馆·生物学》杂志上。