发布公开可用的访谈数据:发布访谈数据的经验的一个实证例子
1Department of Sociology, Princeton University, Princeton, NJ, United States.
Frontiers in sociology
|June 21, 2024
概括
这项研究共享了来自亚马逊Flex,Uber和Lyft的演出工人的39份采访成绩单,详细介绍了自动化工作. 该研究强调道德考虑和公布定性数据的透明流程.
科学领域:
- 科学与技术研究 研究科学与技术研究
- 定性研究方法 定性研究方法
- 数据归档数据归档
背景情况:
- 像亚马逊Flex,Uber和Lyft这样的巨头经济平台越来越多地被研究其运营和自动化策略.
- 定性数据,特别是面试成绩单,为这些平台上的工人体验提供了丰富的见解.
- 公共可访问的数据集对于可重复的研究和推进协作科学努力至关重要.
研究的目的:
- 记录设计,收集,掩盖和发布特约工人的定性访谈数据的过程.
- 为了说明在公开提供敏感的定性数据时所涉及的决策过程.
- 在数据发布中,为受访者隐私提供透明的伦理考虑和风险评估.
主要方法:
- 在2019年对来自亚马逊Flex,Uber和Lyft的临时工进行了39次半结构面试.
- 采用系统的数据掩盖方法来保护参与者的匿名性.
- 在公开档案 (普林斯顿数据空间) 中发布了匿名的采访成绩单和详细的数据管理流程,在创意共享许可证下.
主要成果:
- 一个公开可访问的数据集,包括39个采访成绩单,现已可用.
- 这篇文章详细介绍了一种透明的,逐步的方法论,用于道德性的定性数据发布.
- 该研究强调了风险评估对整个研究生命周期的受访者隐私的重要性.
结论:
- 发布定性数据需要仔细规划,道德考虑和透明的文档.
- 描述的方法作为一个实用指南,研究人员导航数据共享的复杂性.
- 使定性数据可访问可以促进合作,促进科学和技术研究的研究.
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