好科学的自然选择
The natural selection of good science
摘要：
一些领域的科学家担心，许多甚至大多数已发表的结果都是错误的。高误报率可能是偶然出现的，来自劣质的研究实践。或者，这可能是制度激励的必然结果，制度激励奖励出版物，而不管其真实性如何。最近的模型和对科学文化的讨论预测了假阳性出版物的选择，因为发表更多积极发现的研究实验室比更勤奋的实验室更有竞争力。关于如何修改科学实践以避免这种退化，存在着广泛的争论。一些分析表明，即使实验室被激励进行复制研究，并因后来未能复制的出版物而受到惩罚，“坏科学”仍将持续存在。在这里，我们开发了一个框架，用于模拟研究实践的文化演变，使实验室能够在理论上花费精力-使他们能够以一定的代价专注于更有可能在理论基础上为真的假设。理论恢复了实验室实践中高度努力的演变，即使在没有复制的情况下，它也将假阳性出版物抑制到技术最低限度。事实上，仅仅是在两组假设之间做出选择的能力--其中一组假设比另一组假设更有可能是正确的--就能促进更好的科学研究，而不是通过毫不费力地获得更好的一组假设。将理论和复制结合起来，可以在促进良好的科学方法和降低假阳性出版物的比率方面产生协同效应。根据我们的分析，我们提出了四个简单的规则，以促进良好的科学在面对出版的压力。
英文摘要：
Scientists in some fields are concerned that many, or even most, published results are false. A high rate of false positives might arise accidentally, from shoddy research practices. Or it might be the inevitable result of institutional incentives that reward publication irrespective of veracity. Recent models and discussion of scientific culture predict selection for false-positive publications, as research labs that publish more positive findings out-compete more diligent labs. There is widespread debate about how scientific practices should be modified to avoid this degeneration. Some analyses suggest that "bad science" will persist even when labs are incentivized to undertake replication studies, and penalized for publications that later fail to replicate. Here we develop a framework for modelling the cultural evolution of research practices that allows labs to expend effort on theory - enabling them, at a cost, to focus on hypotheses that are more likely to be true on theoretical grounds. Theory restores the evolution of high effort in laboratory practice, and it suppresses false-positive publications to a technical minimum, even in the absence of replication. In fact, the mere ability choose between two sets of hypotheses - one with greater chance of being correct than the other - promotes better science than can be achieved by having effortless access to the better set of hypotheses. Combining theory and replication can have a synergistic effect in promoting good scientific methodology and reducing the rate of false-positive publications. Based on our analysis we propose four simple rules to promote good science in the face of pressure to publish.
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