Calibrating the Scientific Ecosystem Through Meta-Research
Calibrating the Scientific Ecosystem Through Meta-Research
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DOI：
10.1146/annurev-statistics-031219-041104
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发表时间：
2020-01-01
期刊：
影响因子：
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通讯作者：
Ioannidis, John P. A.
中科院分区：
文献类型：
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作者：
Hardwicke, Tom E.;Serghiou, Stylianos;Ioannidis, John P. A.
当一些科学家研究昆虫、分子、大脑或云时，其他科学家研究科学本身。元研究，或研究中的研究，是一门新兴的学科，研究科学生态系统中的效率，质量和偏见，这些主题在对科学文献可信度的广泛关注中变得特别相关。元研究可以通过提供经验证据，为改革举措的迭代生成和改进提供信息，从而帮助校准科学生态系统，使其达到更高的标准。我们介绍了一个翻译框架，涉及（a）识别问题，（B）调查问题，（c）开发解决方案，（d）评估解决方案。在每个领域，我们回顾了关键的元研究工作，并讨论了一些先前和正在进行的工作的例子。科学生态系统是不断发展的;元研究的学科提供了一个机会，利用经验证据来指导其发展并最大限度地发挥其潜力。
While some scientists study insects, molecules, brains, or clouds, other scientists study science itself. Meta-research, or research-on-research, is a burgeoning discipline that investigates efficiency, quality, and bias in the scientific ecosystem, topics that have become especially relevant amid widespread concerns about the credibility of the scientific literature. Meta-research may help calibrate the scientific ecosystem toward higher standards by providing empirical evidence that informs the iterative generation and refinement of reform initiatives. We introduce a translational framework that involves (a) identifying problems, (b) investigating problems, (c) developing solutions, and (d) evaluating solutions. In each of these areas, we review key meta-research endeavors and discuss several examples of prior and ongoing work. The scientific ecosystem is perpetually evolving; the discipline of meta-research presents an opportunity to use empirical evidence to guide its development and maximize its potential.