What does complexity theory have to offer to the study of the science-policy interface? (2)
Blog post II of IV: Complexity as a means to explain, name and label the policy process
Blog post II of IV: Complexity as a means to explain, name and label the policy process
Blog post I of IV: Complexity as a critical response to reductionism and the linear model
Many have flagged that the “nexus” has become a buzzword, and I have found myself working in two different projects that use the word “nexus”, but have quite different focuses, aims and scopes. The first project is a European project Read more…
How one theorizes uncertainty is central to how uncertainty is analysed. If uncertainty is conceptualised as incomplete knowledge, uncertainty analysis will focus on describing knowledge gaps. If uncertainty is conceptualised as the challenge of predicting the future, uncertainty analysis will focus on describing how present variables may change in the future. In this post, I argue that a theoretical understanding of uncertainty is necessary to guide decision-making, and that the analysis of uncertainty must be theoretically informed and not only solution-oriented.
How do representations of slums affect the governance of informality? In this post, I share with you some of the results from my latest publication “Governing informality through representation: Examples from slum policies in Brazil and South Africa” soon available in Cities!
How to provide good science advice to policymakers, under conditions of scientific complexity and uncertainty?
There are three points that I would like to make. (more…)
This is an excerpt from my latest publication: Kovacic, Z. (2018). Conceptualizing numbers at the science-policy interface. Science, Technology & Human Values.
What happens to science advice to policy when science speaks with multiple voices? How does pluralism affect the science policy interface? Is pluralism irreducible or can it be governed? In this post, I review three approaches to governance in the context of pluralism.
Building on the uncertainty literature, we* conceptualize ambiguity as the type of uncertainty that emerges from complexity.
The complexity view is that economic systems are adaptive systems, becoming systems, self-organising systems. Adaptive systems are not as susceptible to planning as machines may be. Complexity may be useful to discuss the challenges of scaling up the actions and innovations of economic agents and firms to economic growth, and the limits of trickle down logics in the context of persistent and growing inequalities in terms of non-linearities between lower level and higher level system components.