Quantitative methods for exploring, understanding, and possibly predicting complex social systems and their intersection with natural systems

This chapter applies the complexity frame of reference to modes of quantitative investigation in general and then presents accounts of methods which specifically work in a complexity consistent fashion. We begin with a complexity take on measurement identifying quantitative measures not as properties of variables which have causal powers external to complex systems but as attributes describing systems but not properly abstractable from them. Measures of attributes can be used both to trace status of systems through time and to classify systems into kinds. Next, we turn to a discussion of how we can try to establish causality through systematic comparison across cases through time. Here we review the potential of Qualitative Comparative Analysis (QCA) and combinations of it with classification as methods with a particular value in policy and practice application. We then turn to Social Network Analysis approaches. These have real value in that they enable us to describe not just systems themselves but the patterns of their interconnections/relations although in our view, they do not take us beyond description. In contrast, modelling approaches, including all varieties of simulation, seem to offer a capacity for prediction. We note that now far more simulation models are not only calibrated on real data but have been developed in co-production with managers and professionals in practice. COVID brought modelling into the core not only of policy and practice but also of public discussion. We conclude the chapter with a discussion of COVID modelling and especially an innovative participatory approach developed by our colleagues at Durham.

Archaeology · Cartography · Geography · Intersection (aeronautics) · Natural (archaeology) · Social system · Artificial Intelligence · Complex Network Analysis Techniques · Complex Systems and Decision Making · Computer Science · Opinion Dynamics and Social Influence