Point break: using machine learning to uncover a critical mass in women's representation

نویسندگان

چکیده

Abstract Decades of research has debated whether women first need to reach a “critical mass” in the legislature before they can effectively influence legislative outcomes. This study contributes debate using supervised tree-based machine learning relationship between increasing variation women's representation and allocation government expenditures three policy areas: education, healthcare, defense. We find that predicts spending all areas. also evidence critical mass effects as relationships are nonlinear. However, beyond mass, our points potential interval or limit point representation. offer guidance on how these results inform future standard parametric models.

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ژورنال

عنوان ژورنال: Political Science Research and Methods

سال: 2021

ISSN: ['2049-8489', '2049-8470']

DOI: https://doi.org/10.1017/psrm.2021.51