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Environment Systems and Decisions

, Volume 38, Issue 1, pp 88–91 | Cite as

Learning and open data in sustainability transitions: evolutionary implications of the theory of probabilistic functionalism

  • Masaru Yarime
Perspectives

Abstract

The Theory of Probabilistic Functionalism, as a general theory of how organisms interact with complex environmental systems, provides a useful framework for describing essential processes of sustainability planning groups. Particularly, the mechanism of producing evolutionary stable representations of and judgment about the environment has important implications for sustainability transitions. In comparison with biological evolution, the environment changes much faster in social phenomena, and the selection dynamics working on heterogeneous groups for successful survival would be incomplete. That makes continuous learning by the members of planning groups as well as collective decision-making among them critically important. The policy of open data for assembling, distributing, and utilizing various kinds of data will facilitate vision creation, strategy development, and consensus building with stakeholders for sustainability transitions.

Keywords

Theory of probabilistic functionalism Sustainability transition Evolutionary process Learning Open data 

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2017

Authors and Affiliations

  1. 1.School of Energy and EnvironmentCity University of Hong KongKowloonHong Kong
  2. 2.Department of Science, Technology, Engineering and Public PolicyUniversity College LondonLondonUK
  3. 3.Graduate School of Public PolicyUniversity of TokyoTokyoJapan

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