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Title: Transformative learning networks
In this paper, we consider how learning networks build capacity for system transformation. We define learning networks as inter-organizational voluntary collaboratives that nurture professional expertise, and describe their potential to catalyze systemic change by disrupting old habits, fostering new relationships, and providing freedom to experiment. We underscore the complexity of designing, facilitating, and sustaining learning networks, noting four distinct ways learning networks can foster systemic resilience, 1) social-psychological 2) engineering 3) social-ecological, and 4) emancipatory. We then describe our research methods and introduce four learning network case study analyses, in order of their age and relative progress towards transformation: • National Alliance for Broader Impacts (NABI) • 100 Resilient Cities Network (100RC) • Fire Adapted Community Learning Network (FAC Net) • START (Global Change SysTem for Analysis, Research & Training)
Authors:
; ; ; ; ;
Award ID(s):
1524832
Publication Date:
NSF-PAR ID:
10186101
Journal Name:
Proceedings of the 60th Annual Meeting of the ISSS
Volume:
1
Issue:
1
Sponsoring Org:
National Science Foundation
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