Theory and Applications
Edited by Eve Mitleton-Kelly, Alexandros Paraskevas and Christopher Day
Chapter 2: Complex evolving social systems: unending, imperfect learning
A methodology implies a purpose which here is to reveal and understand what patterns and structures exist in social systems and how, why and when they occur. In the natural sciences, we can perform repeatable experiments that allow us to find robust general laws by induction and make predictions about specific behaviour by deduction. In social systems, however, agents inhabiting a situation are really in co-evolution with each other and their environment, hence constantly changing over time. This makes induction for general laws much harder and predictions on the basis of deduction questionable. Complexity Science provides a ‘scientific’ basis for evolutionary, qualitative changes, revealing the impossibility of guaranteed prediction. We use several examples to show how complexity and evolution involve changing systems of changing elements – both qualitative and quantitative. Our interpretive frameworks (models) do not make predictions about the world but about themselves thus making, through reflexivity, evasive action more likely.
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