The Open Science Movement aims to enhance the soundness, transparency, and accessibility of scientific research, and at the same time increase public trust in science. Currently, Open Science practices are mainly presented as solutions to the ‘reproducibility crisis’ in hypothetico-deductive quantitative research. Increasing interest has been shown towards exploring how these practices can be adopted by qualitative researchers. In reviewing this emerging body of work, we conclude that the issue of diversity within qualitative research has not been adequately addressed. Furthermore, we find that many of these endeavours start with existing solutions for which they are trying to find matching problems to be solved. We contrast this approach with a natural incorporation of Open Science practices within interaction analysis and its constituent research traditions: conversation analysis, discursive psychology, ethnomethodology, and membership categorisation analysis. Zooming in on the development of conversation analysis starting in the 1960s, we highlight how practices for opening up and sharing data and analytic thinking have been embedded into its methodology. On the basis of this presentation, we propose a series of lessons learned for adopting Open Science practices in qualitative research.

中文翻译：

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“一刀切”：从将开放科学实践定制到定性研究的交互分析中得到的经验教训

开放科学运动旨在增强科学研究的健全性、透明度和可及性，同时增加公众对科学的信任。目前，开放科学实践主要是作为假设演绎定量研究中“再现性危机”的解决方案。人们对探索定性研究人员如何采用这些实践越来越感兴趣。在回顾这一新兴工作时，我们得出的结论是，定性研究中的多样性问题尚未得到充分解决。此外，我们发现许多这些努力都是从现有的解决方案开始的，他们试图找到需要解决的匹配问题。我们将这种方法与交互分析及其组成研究传统中的开放科学实践的自然结合进行对比：对话分析、话语心理学、民族方法论和成员分类分析。着眼于 20 世纪 60 年代开始的对话分析的发展，我们重点介绍开放和共享数据以及分析思维的实践如何嵌入到其方法论中。在此演示的基础上，我们提出了在定性研究中采用开放科学实践的一系列经验教训。