Scholars have long debated how rigor can be achieved in qualitative analysis. To answer this question, we need to better understand how theory is generated from data. Qualitative analysis is, at its core, a categorization process. Nevertheless, despite a surge of interest in categorization within the social sciences, insights from categorization theory have not yet been applied to our understanding of qualitative analysis. Drawing from categorization theory, we argue that the movement from data to theory is an active process in which researchers choose between multiple moves that help them to make sense of their data. In addition, we develop a framework of the main moves that people use when they categorize data and demonstrate that evidence of these moves can also be found in past qualitative scholarship. Our framework emphasizes that, if we are not sufficiently reflexive and explicit about the active analytical processes that generate theoretical insights, we cannot be transparent and, thus, rigorous about how we analyze data. We discuss the implications of our framework for increasing rigor in qualitative analysis, for actively constructing categories from data, and for spurring more methodological plurality within qualitative theory building.

中文翻译：

---

在定性分析中实现严谨：主动分类在理论构建中的作用

长期以来，学者们一直在争论如何在定性分析中实现严格。要回答这个问题，我们需要更好地理解理论是如何从数据中产生的。定性分析的核心是一个分类过程。尽管如此，尽管社会科学对分类的兴趣激增，但分类理论的见解尚未应用于我们对定性分析的理解。从分类理论出发，我们认为从数据到理论的转变是一个积极的过程，研究人员在这个过程中选择多种有助于他们理解数据的举措。此外，我们开发了人们在对数据进行分类时使用的主要动作的框架，并证明这些动作的证据也可以在过去的定性研究中找到。我们的框架强调，如果我们对产生理论见解的积极分析过程不够反思和明确，我们就无法做到透明，从而对我们如何分析数据保持严谨。我们讨论了我们的框架对提高定性分析的严谨性、从数据中积极构建类别以及在定性理论构建中激发更多方法论多元化的影响。