Unbiased evaluation of social vulnerability: A multimethod approach using machine learning and nonparametric statistics

IF 6.6 1区 经济学 Q1 URBAN STUDIES
Hiroki Yokoyama , Yoshiyasu Takefuji
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引用次数: 0

Abstract

This paper introduces a globally applicable bias-aware framework for interpreting machine-learning feature importances by benchmarking them against classical statistics. Using CDC's Social Vulnerability Index data, we compare five predictive models—both nonlinear and linear—with three ground-truth association measures. While nonlinear models deliver superior accuracy, their importance scores systematically inherit and amplify biases from feature correlations and imbalance—a universal concern for ML interpretability. We demonstrate that key vulnerability drivers are robustly detected only when statistical validation accompanies model explanations. This research contributes methodological advances to algorithmic interpretability knowledge and offers international policy recommendations: implement statistical validation protocols for high-stakes ML applications, utilize complementary approaches for robust feature assessment, and establish global standards for interpretability in vulnerable population analytics. These findings generalize across diverse contexts where transparent, bias-resilient feature ranking drives equitable decision-making.
社会脆弱性的无偏评估:使用机器学习和非参数统计的多方法方法
本文介绍了一个全球适用的偏差感知框架,通过对经典统计数据进行基准测试来解释机器学习特征的重要性。使用CDC的社会脆弱性指数数据,我们比较了五种预测模型——非线性和线性——与三种真实关联度量。虽然非线性模型提供了更高的准确性,但它们的重要性评分系统地继承并放大了特征相关性和不平衡的偏差——这是ML可解释性的普遍问题。我们证明,只有当统计验证伴随着模型解释时,才能稳健地检测到关键漏洞驱动因素。本研究为算法可解释性知识提供了方法学上的进步,并提供了国际政策建议:为高风险的机器学习应用实施统计验证协议,利用互补方法进行鲁棒性特征评估,并为弱势群体分析的可解释性建立全球标准。这些发现可以在不同的背景下推广,在这些背景下,透明的、抗偏见的特征排名可以推动公平的决策。
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来源期刊
Cities
Cities URBAN STUDIES-
CiteScore
11.20
自引率
9.00%
发文量
517
期刊介绍: Cities offers a comprehensive range of articles on all aspects of urban policy. It provides an international and interdisciplinary platform for the exchange of ideas and information between urban planners and policy makers from national and local government, non-government organizations, academia and consultancy. The primary aims of the journal are to analyse and assess past and present urban development and management as a reflection of effective, ineffective and non-existent planning policies; and the promotion of the implementation of appropriate urban policies in both the developed and the developing world.
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