BEYOND TEXT: USING ARRAYS TO REPRESENT AND ANALYZE ETHNOGRAPHIC DATA.

IF 0.1 Q4 BUSINESS
Clio America Pub Date : 2015-08-01 Epub Date: 2015-04-17 DOI:10.1177/0081175015578740
Corey M Abramson, Daniel Dohan
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引用次数: 0

Abstract

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.

超越文本:使用阵列来表示和分析人种学数据。
最近,社会学界在方法论方面的争论主要集中在如何使数据和分析更开放、更易获取,如何使理论化和知识生产的过程更清晰,以及如何开发可视化手段来帮助解决这些问题。在民族志研究中,来自不同传统的学者并不一定与他们的定量研究同行或彼此分享关于研究事业的基本认识论假设,因此这些问题尤为复杂。然而,在社会学领域工作的民族志学者在管理、分析和展示田野工作中产生的丰富的、与语境相关的数据时,面临着一系列共同的实际挑战。受目前关于如何使社会学研究更加透明的讨论以及其他以数据为中心的领域的创新的启发,作者开发了一种交互式可视化方法,为解决这些共同的实用挑战提供了工具。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们解决广泛认同的后勤和技术复杂性,同时保持对民族志认识论多样性及其实践者对深度、语境和解释的共同承诺的敏感性。作者利用一项重病人种学研究的数据构建了一个人种阵列模型,并解释了如何将这种阵列与数据存储库连接起来,以促进学术界和非学术界进行新形式的分析、解释和分享。最后,他们讨论了民族阵列和相关方法对民族志的范围、实践和形式的一些潜在影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Clio America
Clio America BUSINESS-
自引率
33.30%
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