Abstract
Literature shows that much research has been conducted on the co-production of climate knowledge, but it has neither established a standardized and replicable model for the co-production process nor the emergent learning patterns as collaborators transition from the disciplinary comfort-zone (disciplinary and practice biases) to the transdisciplinary third-space. This study combines algorithmic simulation modelling and case study lessons from Learning Labs under a 4-year (2016–2019) climate change management project called Future Resilience of African CiTies and Lands in the City of Blantyre in Malawi. The study fills the research gap outlined above by applying a systems-approach to replicate the research process, and a Markov process to simulate the learning patterns. Results of the study make a number of contributions to knowledge. First, there are four distinct evolutionally stages when transitioning from the disciplinary comfort-zone to the transdisciplinary third-space, namely: Shock and resistance to change; experimenting and exploring; acceptance; and integration into the third-space. These stages are marked by state probabilities of the subsequent stages relative to the initial (disciplinary comfort-zone) state. A complete transition to the third-space is marked by probabilities greater than one, which is a system amplification, and it signifies that there has been a significant increase in learning among collaborating partners during the learning process. Second, a four-step decision support tool has been developed to rank the plausibility of decisions, which is very hard to achieve in practice. The tool characterizes decision determinants (policy actors, evidence and knowledge, and context), expands the determinants, checks what supports the decision, and then rates decisions on an ordinal scale of ten in terms of how knowledge producers and users support them. Third, for a successful transdisciplinary knowledge co-production, researchers should elucidate three system-archetypes (leverage points), namely: Salient features for successful co-production, determinant of support from collaborators, and knowledge co-production challenges. It is envisioned that academics, researchers, and policy makers will find the results useful in modelling and replicating the co-production process in a methodical and systemic way while solving complex climate resilience development problems in dynamic, socio-technical systems, as well as in sustainably mainstreaming the knowledge co-produced in policies and plans.
Highlights
Many studies have been conducted to explore ways of improving the modes of co-production of climate science and mainstreaming of the same in the city decisionmaking process, which have ranged from engagements between decision makers and scientists [1,2], the application of empirical studies of specific actions and activities that foster trust and build lasting relationships [3], and utilization of boundary organizations to aid engagements that link knowledge producers and users [4,5]
The general systems-approach or theory, has six characteristics on which this study has leveraged, namely [6], ([7], p. 322): It is holistic—whereby, emergent issues that cannot be quantitatively resolved are explored to reveal salient linkages; systematic—employs a methodological, consistent, and repeatable approach; systemic—considers decision-making as an emergent system where small things integrate into complete wholes; risk-based—sets priorities to identify risks associated with the domain being explored; optimal—determines trade-offs between competing factors such as quality of the knowledge produced, time, and costs associated with the learning processes; and sustainable—considers specific actions which are capable of creating a lasting footprint of networks and best practices and reveals possible up-scalable activities
It was observed that the establishment of the rapport at the onset of the co-production process was as important as the knowledge generation itself
Summary
Many studies have been conducted to explore ways of improving the modes of co-production of climate science and mainstreaming of the same in the city decisionmaking process, which have ranged from engagements between decision makers and scientists [1,2], the application of empirical studies of specific actions and activities that foster trust and build lasting relationships [3], and utilization of boundary organizations to aid engagements that link knowledge producers and users [4,5] Much of these studies have managed to unpack crucial research questions in climate science knowledge production within complex city policy and governance contexts; they have been unidirectional and not driven by theory; have failed to establish a systematic, methodical, and replicable model for the co-production process; and have focused more on units of analysis and detail complexity, and less on dynamic complexity of emergent properties of complex socio-technical systems. These dynamics, coupled with a limited capacity of responsible authorities to manage water at a catchment scale, have resulted in risks associated with water security and energy for Blantyre City and its residents
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