在COVID-19预版中预测社会和行为科学主张的可复制性
Alexandru Marcoci1,2, David P Wilkinson3,4, Ans Vercammen3,5,6
1Centre for the Study of Existential Risk, University of Cambridge, Cambridge, UK. alexandru.marcoci@gmail.com.
Nature human behaviour
|December 20, 2024
概括
引发预测提供了一个比完全复制更快,更便宜的方式来评估科学可靠性. 无论是初学者还是经验丰富的研究人员都可以预测研究的可重复性,有助于危机决策.
科学领域:
- 科学方法科学方法学
- 可复制性研究可复制性研究
- 在COVID-19研究中,研究人员进行了COVID-19的研究.
背景情况:
- 复制对于验证科学发现至关重要,但资源密集.
- 需要更快,更低成本的替代方案,如预测诱导,特别是在危机期间快速实施政策.
- 评估新兴研究的可靠性,例如COVID-19研究,至关重要.
研究的目的:
- 调查使用预测诱导作为代价昂贵复制的替代方案的可行性.
- 为了比较不同专业水平的参与者之间的预测的准确性.
- 评估预测诱导在指导复制努力和告知政策方面的潜力.
主要方法:
- 使用结构化协议,从COVID-19预印件中获得100个索赔的参与者的预测.
- 进行了29次高功率复制,以作为基础真理.
- 在同行互动后,分析了参与者估计和信心的变化.
主要成果:
- 初学者和经验丰富的参与者都在预测索赔可靠性时表现出比偶然更好的准确性 (平均准确率为0.57-0.58).
- 初学者与经验丰富的人相比,在互动后的估计和信心更新显著增加.
- 参与者的判断是相关的,这表明他们对索赔可靠性的理解是共同的.
结论:
- 结构化预测诱导显示出作为评估"快速科学"在不确定性下可靠性的工具的希望.
- 新手和专家的判断都能为复制性提供宝贵的见解.
- 需要进一步的研究,以确定最佳的诱导策略和专家预测器,以进行关键决策.
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