通过基于社区的数据基础来加强表面测量的稳定性
Vadim Keyser1, Hannah Howland2
1Department of Philosophy, California State University, Fresno, 2380 E Keats Ave, Fresno, CA 93710, USA.
Studies in history and philosophy of science
|March 7, 2025
概括
测量稳定性确保可靠的检测,但可以掩盖社会背景中的问题. 这项研究确定了
科学领域:
- 环境科学 环境科学
- 公共卫生 公共卫生
- 方法论 方法论 方法论
背景情况:
- 稳定性分析通过不同的方法确定一致的结果,表明可靠的测量.
- 测量的稳定性对于准确检测环境现象至关重要.
- 然而,在不公平的社会环境中应用它会带来独特的挑战.
研究的目的:
- 在不公平的社会背景下识别测量强度的方法问题.
- 引入"为了普遍性而牺牲代表性充分性" (SRAG) 的概念.
- 提出基于社区的数据实践作为一种解决方案,以提高测量表示的充分性.
主要方法:
- 该研究分析了"牺牲对普遍性的表示性充分性" (SRAG) 问题.
- 介绍了两个案例研究,以说明SRAG在行动中,重点关注污染掩盖和负担.
- 研究了基于社区的强有力的数据实践的有效性.
主要成果:
- 融合测量,尽管看起来很强大,但可以隐藏重要的环境问题,如污染掩盖.
- SRAG问题突出了测量普遍性和准确地代表当地现实之间的权衡.
- 社区主导的数据实践为改善测量目标和策略提供了可行的策略.
结论:
- 由于SRAG问题,在不公平的社会环境中,单纯的测量稳定性是不够的.
- 基于社区的数据实践可以纠正测量策略,促进代表性充分性.
- 解决SRAG对于公平的环境健康研究和实践至关重要.
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