鉴赏性调查中的反种族主义:生成紧张和集体反射性
Amanda Gebhard1, Willow Samara Allen2, Fritz Pino1
1Faculty of Social Work, University of Regina, Canada.
Action research (London)
|October 11, 2024
概括
这项研究将欣赏性调查 (AI) 适用于反种族主义研究,整合了批判性反射性,以解决权力动态和种族主义问题. 研究结果表明,人工智能可以被修改为包含边缘化的知识和经验,而不仅仅是简单的正/负二进制.
科学领域:
- 行动研究行动研究
- 反种族主义理论反种族主义理论
- 定性研究方法 定性研究方法
背景情况:
- 鉴赏性调查 (AI) 是一种行动研究方法,专注于组织的优势.
- 人工智能对积极性的强调引发了反种族主义研究范式的问题.
- 基于社区的研究原则为团队的权力共享和知识共建方法提供了信息.
研究的目的:
- 探索反种族主义理论与欣赏性调查的整合.
- 检查在COVID-19大流行期间学校的种族化定居工人的经验.
- 在加拿大定居者殖民背景下,解决AI的积极性焦点和反种族主义框架之间的紧张关系.
主要方法:
- 在反种族主义研究人员的跨种族团队中合作的反射性.
- 根据反种族主义理论,欣赏性调查的调整.
- 定性研究侧重于主要种族化定居点工人的经验.
主要成果:
- 对种族主义的批判性反思对于将反种族主义纳入欣赏性调查至关重要.
- 没有反种族主义框架的评价性调查,可能无法完全捕捉参与者的跨国知识或经验,而不是积极/消极的二进制.
- 在制度压力忽视种族主义的背景下,在AI的积极性和反种族主义框架之间谈判紧张关系至关重要.
结论:
- 通过对种族主义的批判性反思,第一人称行动研究可以扩大研究的社会正义目标.
- 整合反种族主义理论增强了欣赏性调查的能力,以解决权力动态和多样化的经验.
- 修改后的欣赏性调查可以更好地适应社会正义研究中的复杂,跨国知识和经验.
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