ORIGINAL ARTICLE
Politics of problem definition: Comparing public support of climate change mitigation policies using machine learning
Junghwa Choi,
Wesley Wehde,
Romit Maulik,
Corresponding Author
Junghwa Choi
School of Public Administration, University of Nebraska Omaha, Nebraska, Omaha, USA
Correspondence
Junghwa Choi, School of Public Administration, University of Nebraska Omaha, 6320 Maverick Plaza, Omaha, NE 68182, USA.
Email: [email protected]
Search for more papers by this authorWesley Wehde
Department of Political Science, Texas Tech University, Texas, Lubbock, USA
Search for more papers by this authorRomit Maulik
Mathematics and Computer Science Division, Argonne National Laboratory, Illinois, Lemont, USA
Search for more papers by this authorJunghwa Choi,
Wesley Wehde,
Romit Maulik,
Corresponding Author
Junghwa Choi
School of Public Administration, University of Nebraska Omaha, Nebraska, Omaha, USA
Correspondence
Junghwa Choi, School of Public Administration, University of Nebraska Omaha, 6320 Maverick Plaza, Omaha, NE 68182, USA.
Email: [email protected]
Search for more papers by this authorWesley Wehde
Department of Political Science, Texas Tech University, Texas, Lubbock, USA
Search for more papers by this authorRomit Maulik
Mathematics and Computer Science Division, Argonne National Laboratory, Illinois, Lemont, USA
Search for more papers by this authorAbstract
enPublic support is a key contributor to successful policy adoption and implementation. Given the urgency of climate change mitigation, scholars have explored various determinants that affect public support for climate change mitigation policy. However, the relative decisiveness of these factors in shaping public support is insufficiently examined. Therefore, we deploy interpretable machine learning to understand which factors, among many previously investigated, are most decisive for structuring public support for various climate change mitigation policies. In this paper, we particularly look at the decisiveness of problem definition for shaping public support among various factors. Using U.S national survey data, we find that how individuals define the issue of climate change is more decisive for structuring public support for promoting renewable energy and regulating pollutants to mitigate the risks associated with climate change. However, the results also indicate that the most decisive factors associated with public support vary depending on the types of mitigation policy. We conclude that different strategies should be utilized to increase public support for various climate change mitigation policy options. Our findings contribute to a scholarly understanding of the specific politics of problem definition in the context of environmental and climate change policy.
Resumen
esEl apoyo público es un contribuyente clave para la adopción e implementación exitosa de políticas. Dada la urgencia de la mitigación del cambio climático, los académicos han explorado varios determinantes que afectan el apoyo público a la política de mitigación del cambio climático. Sin embargo, la decisión relativa de estos factores en la configuración del apoyo público no se examina suficientemente. Por lo tanto, implementamos aprendizaje automático interpretable para comprender qué factores, entre muchos investigados previamente, son más decisivos para estructurar el apoyo público a diversas políticas de mitigación del cambio climático. En este documento, analizamos en particular la decisión de la definición del problema para dar forma al apoyo público entre varios factores. Usando datos de encuestas nacionales de EE. UU., encontramos que la forma en que las personas definen el problema del cambio climático es más decisiva para estructurar el apoyo público para promover las energías renovables y regular los contaminantes para mitigar los riesgos asociados con el cambio climático. Sin embargo, los resultados también indican que los factores más determinantes asociados al apoyo público varían según los tipos de política de mitigación. Concluimos que se deben utilizar diferentes estrategias para aumentar el apoyo público a varias opciones de políticas de mitigación del cambio climático. Nuestros hallazgos contribuyen a una comprensión académica de la política específica de definición de problemas en el contexto de la política ambiental y de cambio climático.
摘要
zh公众支持是成功的政策采纳和实施的关键因素。鉴于气候变化缓解的紧迫性，学者已探究了影响公众支持气候变化缓解政策的一系列决定因素。不过，这些因素在影响公众支持方面的相对决定性并未得到充分检验。因此，我们使用了可诠释的机器学习以理解在以往研究的许多因素中，哪些因素对于“构建公众对不同气候变化缓解政策的支持”而言最具决定性。本文中，我们特别研究了问题定义在影响公众支持一事上的决定性。通过使用美国国家调查数据，我们发现，个人如何定义气候变化问题一事对于“构建公众支持以促进可再生能源以及调节污染物以缓解与气候变化相关的风险”而言更具决定性。不过，结果还表明，与公众支持相关的、最具决定性的因素会因不同的缓解政策类型而存在差异。我们的结论认为，应该使用不同的策略来增加公众对不同气候变化缓解政策选项的支持。我们的研究结果有助于从学术上理解环境和气候变化政策情境下问题定义的具体政治。
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