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.
Measurements are used in policy-making to set targets, and to monitor progress towards targets. Think of CO2 emission targets, energy efficiency targets, waste recycling monitoring. When dealing with complex issues, the choice of metrics is not trivial! The issue of non-equivalence reveals that measurements may be precise, but they do not lead to univocal knowledge. As a consequence, policy objects are constituted also through the choice of metrics.
Why write a blog about complexity and science for policy? Because complexity matters for science advice to policy. Complex systems may lead to a situation in which science cannot provide all answers. Complexity refers to situations in which “the whole is different from the sum of its parts”, because of emerging properties at different scales of analysis. This situation is challenging for governance, because providing evidence on “the parts” will lead to different decisions than providing evidence on “the whole”.