Rethinking Environmental Justice in Sustainable Cities - Insights from Agent-Based Modeling (Hardcover)

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As the study of environmental policy and justice becomes increasingly significant in today's global climate, standard statistical approaches to gathering data have become less helpful at generating new insights and possibilities. None of the conventional frameworks easily allow for the empirical modeling of the interactions of all the actors involved, or for the emergence of outcomes unintended by the actors. The existing frameworks account for the "what," but not for the "why." Heather E. Campbell, Yushim Kim, and Adam Eckerd bring an innovative perspective to environmental justice research. Their approach adjusts the narrower questions often asked in the study of environmental justice, expanding to broader investigations of how and why environmental inequities occur. Using agent-based modeling (ABM), they study the interactions and interdependencies among different agents such as firms, residents, and government institutions. Through simulation, the authors test underlying assumptions in environmental justice and discover ways to modify existing theories to better explain why environmental injustice occurs. Furthermore, they use ABM to generate empirically testable hypotheses, which they employ to check if their simulated findings are supported in the real world using real data. The pioneering research on environmental justice in this text will have effects on the field of environmental policy as a whole. For social science and policy researchers, this book explores how to employ new and experimental methods of inquiry on challenging social problems, and for the field of environmental justice, the authors demonstrate how ABM helps illuminate the complex social and policy interactions that lead to both environmental justice and injustice.

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Product Description

As the study of environmental policy and justice becomes increasingly significant in today's global climate, standard statistical approaches to gathering data have become less helpful at generating new insights and possibilities. None of the conventional frameworks easily allow for the empirical modeling of the interactions of all the actors involved, or for the emergence of outcomes unintended by the actors. The existing frameworks account for the "what," but not for the "why." Heather E. Campbell, Yushim Kim, and Adam Eckerd bring an innovative perspective to environmental justice research. Their approach adjusts the narrower questions often asked in the study of environmental justice, expanding to broader investigations of how and why environmental inequities occur. Using agent-based modeling (ABM), they study the interactions and interdependencies among different agents such as firms, residents, and government institutions. Through simulation, the authors test underlying assumptions in environmental justice and discover ways to modify existing theories to better explain why environmental injustice occurs. Furthermore, they use ABM to generate empirically testable hypotheses, which they employ to check if their simulated findings are supported in the real world using real data. The pioneering research on environmental justice in this text will have effects on the field of environmental policy as a whole. For social science and policy researchers, this book explores how to employ new and experimental methods of inquiry on challenging social problems, and for the field of environmental justice, the authors demonstrate how ABM helps illuminate the complex social and policy interactions that lead to both environmental justice and injustice.

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Product Details

General

Imprint

Routledge

Country of origin

United Kingdom

Series

Routledge Studies in Public Administration and Environmental Sustainability

Release date

June 2015

Availability

Expected to ship within 12 - 17 working days

First published

2015

Authors

, ,

Dimensions

229 x 152 x 19mm (L x W x T)

Format

Hardcover

Pages

250

ISBN-13

978-0-415-65744-0

Barcode

9780415657440

Categories

LSN

0-415-65744-X



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