近年来,越来越多的科学造假事件表明,科学研究已被很多人看做是一种既能养家糊口又可名利双收的职业。不严谨的学术评议机制吸引了大量缺乏真正兴趣且不具备资质的研究者,甚至少数心术不正者。这样的学术研究氛围不能不让我们反思其根源。本文就是一篇探讨学术造假现象的文章,它重申了科学的基本精神以及科学界的基本职业伦理——求真。
That people, from politicians to priests, cheat and lie is taken for granted by many. But scientists, surely, are above that sort of thing? In the past decade the cases of Hwang Woo-Suk1), who falsely reported making human embryonic stem cells2) by cloning, and Jan Schön, a physicist who claimed astonishing (and fabricated) results in the fields of semiconductors and superconductors, have shown that they certainly are not. However, on these occasions the claims made were so spectacular that they were bound to attract close scrutiny, and thus be exposed eventually. In the cases of Dr Hwang and ex-Dr Schön, the real question for science was not whether it harbours3) a few megalomaniac4) fantasists, but why the frauds were not exposed earlier when the papers that made the claims were being reviewed by peers.
在许多人眼里,政客和牧师之流耍花招、说瞎话就像家常便饭,被认为理所当然。可是,科学家呢?就一定比这些人洁身自好吗?在过去的十年中,谎报克隆出了人类胚胎干细胞的黄禹锡、宣称在半导体和超导体领域取得惊人(却是杜撰的)成果的物理学家扬·舍恩的例子表明,科学家也好不到哪里去。不过,在上述事例中,他们是因为“成果”太过引人瞩目,所以注定会招来严密的审查,并最终使真相曝光。在博士黄禹锡和前博士扬·舍恩事件中,对于科学而言,真正的问题不在于它是否藏匿了少数喜欢夸大的幻想狂,而是同行们在评审那些宣称成果的论文时,为何没能早一点揭穿其中的谎言。
Lower-level fraud, however, is much harder to detect: the data point invented or erased to make a graph look better, or to make a result that was not quite statistically significant into that scientific desideratum5), the “minimum publishable unit6)”; the results “mined” retrospectively for interesting correlations, rather than used to test pre-existing hypotheses; the photograph that has been “enhanced” to bring out what the researcher regards as the salient7) features. How often this sort of thing happens is hard to say. But Daniele Fanelli of the University of Edinburgh thought he would try to find out. His results, published in the Public Library of Science, suggest it is commoner than scientists would like the rest of the world to believe.
不过,更难被发现的是低级造假:生造或抹掉一个数据点来美化图表,或者让统计学意义并不显著的结果摇身一变成为科学上亟需的东西——“最小出版单位”;从既往研究的故纸堆里“开采”出一些结果,为的是寻找能引发人兴趣的关联,而非检验已有的假设;对图片进行“深加工”,使之呈现出研究人员心目中所期望的显著特征。此类事情到底有多普遍很难说。不过,爱丁堡大学的达尼埃莱·法内利认为,他会努力找到答案的。他在《科学公共图书馆》杂志上发表的研究成果表明,事实上这种情况非常普遍,虽然科学家们并不想让世人相信这一点。
Dr Fanelli’s own laboratory was the internet. He hunted down8) past surveys of scientific honesty and subjected them to what is known as a meta-analysis. This is a technique that allows the results of entire studies, which may not have used the same methods, to be pooled in a statistically meaningful way. Dr Fanelli found 18 surveys that met the criteria for his meta-analysis, and a few others that he also included in a general review.
法内利博士的实验室就是互联网。他从网上搜索出以往关于科学诚信的调查,然后利用一种所谓的元分析技术对其进行分析。这种技术可以用一种具有统计学意义的方式,对所有可能通过不同方法得出的研究结果加以汇总。法内利发现,有18项调查符合他的元分析标准,除此之外,在综述中,他还引用了其他一些调查结果。
Admissions of outright fraud (i.e., having fabricated, falsified9) or modified data to improve the outcome at least once during a scientific career) were low. According to the meta-analysis, 2% of researchers questioned were willing to confess to this. But lower-level fraud was rife10). About 10% confessed to questionable practices, such as “dropping data points based on a gut feeling11)” or “failing to present data that contradict one’s previous research”.
坦承存在直接欺骗行为(即为了改进研究结果,在从事科学研究期间至少有过一次杜撰、伪造或修改数据的行为)的人并不多。元分析结果显示,接受问卷调查的研究人员中,仅有2%的人肯承认这一点。不过,低级造假行为却十分普遍。大约有10%的人承认自己存在值得质疑的行为,比如“根据个人感觉忽略一些数据”,或者“隐瞒与自己此前研究成果相矛盾的数据”。
Moreover, when it came to airing12) suspicions about colleagues, the numbers went up. The meta-analysis suggested that 14% of researchers had seen their colleagues fabricate, falsify, alter or modify data. If the question was posed in more general terms, such as running experiments with deficient methods, failing to report deficiencies or misrepresenting13) data,46% of researchers had seen others get up to such shenanigans14). In only half of the cases, though, had the respondent to a survey tried to do anything about the misconduct he said he had witnessed.
此外,对自己同事表示怀疑的人数量则比较多。元分析结果显示,有14%的研究者曾见过自己的同事杜撰、伪造、改动或修改数据。假如将诸如实验方法存在缺陷、对实验缺陷隐瞒不报或者不如实报告数据之类更具一般性的问题都算在内的话,则有46%的研究人员承认曾见他人玩过这类把戏。然而,面对这种情况,在某一调查中,只有一半的被调查对象对自己声称曾亲眼目睹的不端行为采取过行动。
How much this actually matters is moot15). Fabricating data is a heinous16) scientific sin. It steers people down paths that do not lead anywhere and discourages them from following those that do. But cleaning data up has a long tradition. Robert Millikan17), the physicist who first measured the charge on the electron, discarded results that did not match his expectations, yet he won a Nobel prize—because he was right. The results of Gregor Mendel18), the father of modern genetics, are also suspiciously over-accurate by the tenets of modern statistics. When such practices shade into19) dishonesty is itself a shady area. Just as everyone thinks himself a better-than-average driver, these results (assuming that they are honest) suggest people are more willing to see sin in others than in themselves. And that, at least, proves something that is sometimes forgotten. Scientists are as human as everyone else.
现在还说不准这种不端行为到底会产生多大的影响。杜撰数据在科学上是一种十恶不赦的罪过。它不但会把人引入徒劳无果的死胡同,也会妨碍人沿着正确的科研途径走向成功。不过,在数据上“去其糟粕,取其精华”的传统由来已久。第一个测出电子电量的物理学家罗伯特·密立根就曾舍弃与之预期不符的结果,而他却赢得了诺贝尔奖——因为他的研究结果是正确的。以现代统计学的标准来看,现代遗传学之父格里哥·孟德尔的研究结果也有过于精准之嫌。科学上的弄虚作假衍生于何时本身还是一个问题。正好比人人都觉得自己的驾驶技术高于平均水平一样,这些结果(假定他们都没有撒谎)表明,人们更倾向于看到别人而不是自己身上的过错。而这至少证实了一个有时会被遗忘的问题,那就是,和其他所有人一样,科学家也是人,一样会犯错。
1. Hwang Woo-Suk:黄禹锡(1953~),曾被誉为韩国“克隆之父”,2005年被指控违背研究伦理,伪造研究成果。
2. embryonic stem cell:胚胎干细胞
3. harbour [5hB:bE] vt. 隐匿,窝藏
4. megalomaniac [7megElEu5meInjE] adj. 夸大狂的
5. desideratum [dI7zidE5reItEm] n. 所愿望之物,迫切需要之物
6. minimum publishable unit:最小出版单位,其原意是指在同行评议的期刊上能够以最小的信息量发表的文章。这个术语通常被当做玩笑或者具有讽刺意味,指那些以牺牲质量为代价,追求最大发表数量的策略。
7. salient [5seIljEnt] adj. 显著的,突出的
8. hunt down:搜寻直至发现
9. falsify [5fC:lsI7faI] vt. 伪造
10. rife [raIf] adj. 普遍的
11. gut feeling:直觉,第六感
12. air [[ZE] vt. 发表意见
13. misrepresent [5mIs7reprI5zent] vt. 不如实地叙述(或说明)
14. shenanigan [FE5nAnI^En] n. 恶作剧,诡计,胡闹
15. moot [mu:t] adj. 未决议的,无实际意义的
16. heinous [5heInEs] adj. 可憎的
17. Robert Millikan:罗伯特·密立根(1868~1953),美国物理学家,曾获1923年诺贝尔物理学奖。
18. Gregor Mendel:格里哥·孟德尔(1822~1884),奥地利遗传学家
19. shade into:逐渐变为