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开放科学、复制危机与环境公共卫生。

Open science, the replication crisis, and environmental public health.

作者信息

Hicks Daniel J

机构信息

University Of California, Merced, CA, USA.

出版信息

Account Res. 2023 Jan;30(1):34-62. doi: 10.1080/08989621.2021.1962713. Epub 2021 Aug 17.

Abstract

Concerns about a crisis of mass irreplicability across scientific fields ("the replication crisis") have stimulated a movement for open science, encouraging or even requiring researchers to publish their raw data and analysis code. Recently, a rule at the US Environmental Protection Agency (US EPA) would have imposed a strong open data requirement. The rule prompted significant public discussion about whether open science practices are appropriate for fields of environmental public health. The aims of this paper are to assess (1) whether the replication crisis extends to fields of environmental public health; and (2) in general whether open science requirements can address the replication crisis. There is little empirical evidence for or against mass irreplicability in environmental public health specifically. Without such evidence, strong claims about whether the replication crisis extends to environmental public health - or not - seem premature. By distinguishing three concepts - reproducibility, replicability, and robustness - it is clear that open data initiatives can promote reproducibility and robustness but do little to promote replicability. I conclude by reviewing some of the other benefits of open science, and offer some suggestions for funding streams to mitigate the costs of adoption of open science practices in environmental public health.

摘要

对各科学领域大规模不可重复性危机(“复制危机”)的担忧引发了一场开放科学运动,鼓励甚至要求研究人员公布其原始数据和分析代码。最近,美国环境保护局(US EPA)的一项规定本会强制实施一项严格的开放数据要求。该规定引发了关于开放科学实践是否适用于环境公共卫生领域的大量公众讨论。本文的目的是评估:(1)复制危机是否延伸至环境公共卫生领域;以及(2)一般而言,开放科学要求能否解决复制危机。具体针对环境公共卫生领域中支持或反对大规模不可重复性的实证证据很少。没有这样的证据,关于复制危机是否延伸至环境公共卫生领域的强烈主张——无论支持还是反对——似乎都为时过早。通过区分三个概念——可重复性、可复制性和稳健性——可以清楚地看出,开放数据倡议可以促进可重复性和稳健性,但对促进可复制性作用不大。我通过回顾开放科学的一些其他益处来得出结论,并为资金流提供一些建议,以减轻在环境公共卫生领域采用开放科学实践的成本。

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