Understanding Complex Social Systems – The use of Multiple Methods to Provide Multiple Perspectives

This paper originates in the authors’ approach to a general problem for social research: how can we understand social systems as complex and how can we establish causality in relation to outcomes for such complex systems? The latter question has particular salience for applied evaluative research where it translates into the question: What works? More specifically, the complexity frame of reference requires us to ask, “What works where, when, and how?” In complexity terms, we have to establish context in both temporal and spatial terms and to delineate contingent and multiple causal pathways towards outcomes. The paper will draw on examples combining a variety of methods—with methods understood as a means for constructing different and complementary perspectives, which enable us to hunt causes in examining complex interventions towards social objectives. The issues covered will include inequalities in health, outcomes of urban ‘regeneration’, and programmes directed towards ‘social inclusion’. Methods reviewed include comparative case-based approaches, simulation, neural nets, longitudinal classification, network analysis, cluster analysis, quantitative and qualitative narrative, and participatory action research. The emphasis will not be on the methods as complementary rather than competitive ways of grasping both the trajectories of complex social systems and the causal factors influencing those trajectories. Our foundational argument will be that the meta-theoretical perspective of complex realism provides an overarching framework which validates this style of work. Moreover, we argue that a “complex realist” mapping of method, in combination with the “making” of the trajectories of complex social systems is what ultimately allows for causal factors to be identified. In mapping terms, such an approach requires (1) a careful account of the justification for the deployment of various methodological combinations and (2) a critical consideration of how the research products of the different approaches can be integrated into a useful overall account.