Learning and open data in sustainability transitions : evolutionary implications of the theory of probabilistic functionalism
Related Research Unit(s)
|Journal / Publication||Environment Systems and Decisions|
|Online published||28 Nov 2017|
|Publication status||Published - Mar 2018|
|Link to Scopus||https://www.scopus.com/record/display.uri?eid=2-s2.0-85035100657&origin=recordpage|
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.
- Evolutionary process, Learning, Open data, Sustainability transition, Theory of probabilistic functionalism
Environment Systems and Decisions, Vol. 38, No. 1, 03.2018, p. 88-91.
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal