Some of The World's Most-Cited Scientists Have a Secret That's Just Been Exposed
一些世界上被引用最多的科學家,有一個秘密剛剛被揭露出來
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.
一項新的研究揭示了一個令人不安的事實,引用指標通常被用來衡量科學家在各自研究領域的影響力。
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.
引用指標表明科學家的研究成果,在他們自己論文的腳注中被同行正式引用的頻率——但是對這一聯(lián)系網(wǎng)的全面分析表明,系統(tǒng)受到了一種經(jīng)常被忽視的隱藏行為模式的影響。
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.
具體地說,在1996年至2017年間被引用最多的10萬名科學家中,有一個秘密的研究者口袋,他們代表著“極端的自我引用和‘引用農(nóng)場’(相對較小的一組作者大量引用彼此的論文),”這項新研究的作者解釋說,該研究由從斯坦福大學的內(nèi)科醫(yī)生轉為元研究員約翰·伊奧尼迪斯。
Ioannidis helps to run Stanford's meta-research innovation centre, called Metrics, which looks at identifying and solving systemic problems in scientific research.
約阿尼迪斯幫助運營斯坦福大學的元研究創(chuàng)新中心(Metrics),該中心致力于識別和解決科學研究中的系統(tǒng)性問題。
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.
伊安尼迪斯說,其中一個問題,是自我引文是如何損害引文指標的可靠性的,特別是在極端自我引文者及其相關集群的手中。
"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."
“我認為自我引用農(nóng)場比我們想象的要普遍得多,”約阿尼迪斯告訴《自然》雜志。“那些自我引證率超過25%的人不一定從事不道德的行為,但可能需要更仔細的審查。”
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).
約阿尼迪斯所指的25%的數(shù)字是指那些在引用他們的著作(或他們的合著者的著作)的引文中,有25%是自我引用的科學家。
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.
研究顯示,擁有四分之一的粉絲群似乎是一種自我引證,但這并不罕見。
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10萬名被引頻次最高的科學家中,超過1000名研究人員的自我引頻次占總引頻次的40%以上,超過8500名研究人員的自我引頻次超過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.
沒有任何跡象表明,這些自我引用行為中的任何一種是出自不道德的、無根據(jù)的或自私自利的。畢竟,在某些情況下,你自己發(fā)表的科學研究可能是最好和最相關的鏈接來源。
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).
盡管如此,這項研究背后的研究人員表示,在他們的分析中揭示的極端案例的普遍存在,降低了引文指標作為一個整體的價值——這些指標通常被用作科學家地位和產(chǎn)出質量的代表(更不用說就業(yè)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.
作者寫道:“由于自我引用的比例非常高,我們建議不要使用任何引用指標,因為極端的自我引用率可能預示著其他虛假特征。”
"These need to be examined on a case-by-case basis for each author, and simply removing the self-citations may not suffice."
“這些需要根據(jù)每個作者的具體情況進行檢查,僅僅刪除自我引用可能還不夠。”
It's far from the first time researchers have highlighted serious problems with the way we rate the products of scientific endeavour.
這已經(jīng)不是研究人員第一次強調我們對科學成果的評估方式存在嚴重問題。
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.
近年來,科學家們發(fā)現(xiàn)了引文系統(tǒng)中隱藏的技術缺陷,揭示了我們?nèi)绾螌茖W期刊進行排名的缺點,并發(fā)現(xiàn)了對引文征集的嚴重擔憂。
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應該存在的奇怪的引文錯誤,并觀察到其他令人不安的系統(tǒng)性趨勢,這些趨勢給引文的價值蒙上了陰影。
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.
在這種混亂中,伊奧尼迪斯和他的團隊希望他們的新數(shù)據(jù)“將有助于更細微地使用度量標準”,使整個社區(qū)能夠更容易地識別和減少自我引文和引文農(nóng)場的不當影響。
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.
與此同時,另一些人則建議,解決這個問題的方法是從整體上擺脫定量度量,而是專注于用定性的方法來糾正這里的錯誤。
"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.
俄勒岡大學的心理學家桑杰·斯里瓦斯塔瓦(Sanjay Srivastava)對《自然》雜志表示:“當我們把職業(yè)發(fā)展和過于關注基于引用的指標聯(lián)系起來時,我們會鼓勵自我引用。”他沒有參與這項研究。
"Ultimately, the solution needs to be to realign professional evaluation with expert peer judgement, not to double down on metrics."
“最終,解決方案需要重新調整專業(yè)評估與專家同行判斷,而不是在指標上加倍。”
The findings are reported in PLOS Biology.
研究結果發(fā)表在《公共科學圖書館·生物學》雜志上。