就像正义一样，科学在盲目的时候最有效

Like justice, science works best when it's blind. For the better part of two centuries, that's been the mantra for sound experimental design.

就像正义一样，科学在盲目的时候最有效。在两个世纪的大部分时间里，这一直是声音实验设计的口头禅。

Hiding observations that risk introducing bias defines a standard of reliability in research. But a group of UK scientists have put forward an argument that in many cases, it could be a waste of effort, and one that might even do more harm than good.

在研究中，隐藏可能导致偏差的观察结果定义了可靠性的标准。但一群英国科学家提出了一个观点，在很多情况下，这可能是白费力气，甚至可能弊大于利。

Together with colleagues from the University of Edinburgh and the Centre for Public Health in Belfast, clinical researcher Rohan Anand from Queen's University Belfast makes a case that scientists should think long and hard before working blinding procedures into their experiment.

来自贝尔法斯特女王大学的临床研究员Rohan Anand与来自爱丁堡大学和贝尔法斯特公共卫生中心的同事们一起提出了一个案例，即科学家们在对他们的实验进行盲法操作之前应该仔细思考。

Their argument boils down to a question of cost versus benefit. We're quick to recognise the potential rewards of a blinded trial, but some of the less convenient consequences might mean it's not worth the fuss.

他们的争论归结为成本与收益的问题。我们很快意识到盲法试验的潜在回报，但一些不太方便的结果可能意味着它不值得大惊小怪。

"Given that the number of new trials is increasing every year, with 25,000 registered since the start of 2019, we are concerned that a substantial amount of time, energy, and funding may be going into considering and implementing blinding without a sound rationale for it," Anand and his fellow researchers state in a recent Analysis article in The BMJ.

阿南德和他的研究伙伴在BMJ最近的一篇分析文章中说：“鉴于新的试验数量每年都在增加，自2019年初以来已注册了25000个，我们担心大量的时间、精力和资金可能会在没有合理理由的情况下考虑和实施盲法。”

That 'sound' rationale is all too easy to take for granted. After all, science evolved as a system of checks and balances to ensure our best ideas explaining the Universe weren't fanciful dreams born of peer pressure and wishful thinking.

这种“合理的”理由太容易被认为是理所当然的。毕竟，科学的发展是一种制衡体系，以确保我们解释宇宙的最佳想法不是来自同辈压力和一厢情愿的空想。

Along with replication in experimentation, positive and negative controls, p-values, and randomisation of test subjects, using naïve observers to report and measure variables is just one more way to ensure we don't confuse imagination for reason.

除了实验中的复制、阳性和阴性对照、p值以及受试者的随机性之外，使用天真的观察者来报告和测量变量，只是确保我们不会因为理性而混淆想象力的另一种方法。

But none of these efforts come for free. Volunteers need to be recruited and screened, for instance, which as any postgrad knows is no easy task. Even then, they don't always stick around to the end.

但这些努力都不是免费的。例如，志愿者需要被招募和筛选，任何研究生都知道这不是一件容易的事情。即使这样，他们也不总是坚持到底。