Transforming with a Soft Touch: Comparing Four Learning Networks

Abstract

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 catalyse systemic change by disrupting old habits, fostering new relationships, and providing freedom to experiment. We conducted a parallel study of four learning networks, which vary in age since founding from 2 to 25 years, applying three exploratory questions across our cases. We conclude by considering how learning networks can foster transformative capacity within social‐ecological systems when they are designed and facilitated with a soft touch so that network members in different sites have the freedom to define their place and purpose within their system, as well as their role in bringing about a desired transformation. We suggest that system transformation is not just the sum of similar efforts at different sites and scales or a least common denominator between them but is emergent from interaction between the partially shared understandings of actors within and between sites, and across network scales. A well‐designed network is a learning system that encompasses these multiple perspectives, and good netweaving mediates different ways of system knowing without collapsing them into one perspective. Copyright © 2017 John Wiley & Sons, Ltd.

Sustainability transformations: socio-political shocks as opportunities for governance transitions

“…There is a rich literature on path dependency, traps, and early warnings in relation to thresholds, transitions, and regime shifts in the social or ecological domains ( Carpenter et al., 2011 ; Carter and Barrett, 2006 ; Gargiulo and Benassi, 2000 ; Geels, 2002 ; Goertz and Diehl, 1995 ; Gordon et al., 2008 ; Keeler, 1993 ; Pelling and Dill, 2010 ; Scheffer et al., 2012 ; Thelen, 1999 ). Building on early studies on transitions, transformations, and regime shifts of linked social-ecological systems (SES) ( Berkes and Folke, 1998 ; Danter et al., 2000 ; Gunderson and Holling, 2002 ; Olsson et al., 2004b ; Scoones, 1999 ) the number of studies on this topic has rapidly increased in the last decade ( Abson et al., 2017 ; Adger et al., 2009 ; Avelino, 2017 ; Blythe et al., 2018 ; David Tàbara et al., 2018 ; Enfors, 2013 ; Goldstein et al., 2018 ; Loorbach et al., 2017 ; Patterson et al., 2017 ; Pereira et al., 2015 ; Reyers et al., 2018 ; Westley et al., 2017 ). By transformation we refer to the capacity to create fundamentally new systems of human-environmental interactions and feedbacks when ecological, economic, or social structures make the existing system untenable ( Walker et al., 2004 ).…”

Developing the Transformative Capacity of Social Innovation through Learning: A Conceptual Framework and Research Agenda for the Roles of Network Leadership

“…A helpful perspective for conceptualizing this role of networks is the notion of "learning networks" developed by Goldstein et al [51][52][53]. They empirically analysed learning processes in networks advancing transformative change in education, urban governance, wildfire management and climate adaptation.…”

“…They defined learning networks as "inter-organizational voluntary collaboratives that nurture professional expertise and describe their potential to catalyse systemic change by disrupting old habits, fostering new relationships, and providing freedom to experiment." [51] (p. 537). Furthermore: "Effective learning networks amplify the potential for transformative change by combining community-based innovation with community-spanning interaction and exchange" [52] (p. 7).…”

“…Risien and Goldstein [53] suggest that building and navigating boundaries of communities of practice are key for developing the transformative capacity of a learning network. Boundaries developed around membership of a network can support professionalization and expertise within their domain, while crossing boundaries can enhance innovation from exchanges with actors in the wider SI action field [51,64], or landscape of practice [63], about diverse perspectives and approaches.…”

“…Integrating autonomous experimentation with network learning and cohesion across the network: SI networks tend to promote an experimental culture where local initiatives can act autonomously and try out new approaches [1,51]. This can be a vital source of innovation for the entire network to learn from if local innovations become adopted by others.…”