Abramson Corey M, Dohan Daniel
University of Arizona, Tucson, AZ, USA.
University of California, San Francisco, San Francisco, CA, USA.
Sociol Methodol. 2015 Aug 1;45(1):272-319. doi: 10.1177/0081175015578740. Epub 2015 Apr 17.
Recent methodological debates in sociology have focused on how data and analyses might be made more open and accessible, how the process of theorizing and knowledge production might be made more explicit, and how developing means of visualization can help address these issues. In ethnography, where scholars from various traditions do not necessarily share basic epistemological assumptions about the research enterprise with either their quantitative colleagues or one another, these issues are particularly complex. Nevertheless, ethnographers working within the field of sociology face a set of common pragmatic challenges related to managing, analyzing, and presenting the rich context-dependent data generated during fieldwork. Inspired by both ongoing discussions about how sociological research might be made more transparent, as well as innovations in other data-centered fields, the authors developed an interactive visual approach that provides tools for addressing these shared pragmatic challenges. They label the approach "ethnoarray" analysis. This article introduces this approach and explains how it can help scholars address widely shared logistical and technical complexities, while remaining sensitive to both ethnography's epistemic diversity and its practitioners shared commitment to depth, context, and interpretation. The authors use data from an ethnographic study of serious illness to construct a model of an ethnoarray and explain how such an array might be linked to data repositories to facilitate new forms of analysis, interpretation, and sharing within scholarly and lay communities. They conclude by discussing some potential implications of the ethnoarray and related approaches for the scope, practice, and forms of ethnography.
社会学领域近期的方法论争论聚焦于如何使数据与分析更具开放性和可获取性,如何使理论化与知识生产过程更明晰,以及可视化手段的发展如何有助于解决这些问题。在人种志研究中,来自不同传统的学者未必与他们的定量研究同行或彼此共享关于研究事业的基本认识论假设,这些问题尤其复杂。然而,从事社会学领域研究的人种志学者面临一系列与管理、分析和呈现田野调查期间生成的丰富的情境依赖数据相关的共同实际挑战。受关于如何使社会学研究更具透明度的持续讨论以及其他以数据为中心的领域的创新的启发,作者们开发了一种交互式可视化方法,该方法提供了解决这些共同实际挑战的工具。他们将这种方法称为“民族阵列”分析。本文介绍了这种方法,并解释了它如何帮助学者应对广泛存在的后勤和技术复杂性,同时对人种志的认知多样性以及其实践者对深度、情境和解释的共同承诺保持敏感。作者们利用一项关于重病的人种志研究数据构建了一个民族阵列模型,并解释了这样一个阵列如何与数据存储库相链接,以促进学术和非专业社区内新的分析、解释和共享形式。他们通过讨论民族阵列及相关方法对人种志的范围、实践和形式的一些潜在影响来得出结论。