The Problem of Institutional Fit: Uncovering Patterns with Boosted Decision Trees

Complex social-ecological contexts play an important role in shaping the types of institutions that groups use to manage resources, and the effectiveness of those institutions in achieving social and environmental objectives. However, despite widespread acknowledgment that “context matters”, progress in generalising how complex contexts shape institutions and outcomes has been slow. This is partly because large numbers of potentially influential variables and non-linearities confound traditional statistical methods. Here we use boosted decision trees – one of a growing portfolio of machine learning tools – to examine relationships between contexts, institutions, and their performance. More specifically we draw upon data from the International Forest Resources and Institutions (IFRI) program to analyze (i) the contexts in which groups successfully self-organize to develop rules for the use of forest resources (local rulemaking), and (ii) the contexts in which local rulemaking is associated with successful ecological outcomes. The results reveal an unfortunate divergence between the contexts in which local rulemaking tends to be found and the contexts in which it contributes to successful outcomes. These findings and our overall approach present a potentially fruitful opportunity to further advance theories of institutional fit and inform the development of policies and practices tailored to different contexts and desired outcomes

Leverage points for sustainability transformation: a review on interventions in food and energy systems

© 2019 Elsevier B.V. There is increasing recognition that sustainability science should be solutions orientated and that such solutions will often require transformative change. However, the concrete sustainability interventions are often not clearly communicated, especially when it comes to the transformative change being created. Using food and energy systems as illustrative examples we performed a quantitative systematic review of empirical research addressing sustainability interventions. We use a modified version of Donella Meadows' notion of ‘leverage points’ – places in complex systems where relatively small changes can lead to potentially transformative systemic changes – to classify different interventions according to their potential for system wide change and sustainability transformation. Our results indicate that the type of interventions studied in the literature are partially driven by research methods and problem framings and that ‘deep leverage points’ related to changing the system's rules, values and paradigms are rarely addressed. We propose that for initiating system wide transformative change, deep leverage points – the goals of a system, its intent, and rules – need to be addressed more directly. This, in turn, requires an explicit consideration of how scientific approaches shape and constrain our understanding of where we can intervene in complex systems