Mapping the complexity of capabilities: a participatory approach and methodological toolbox
Craven, Luke (2016). 'Mapping the complexity of capabilities: a participatory approach and methodological toolbox' Paper presented at the annual conference of the HDCA, Tokyo 2016.
abstract Concepts such as disadvantage and poverty are intrinsically complex, multifaceted and multidimensional. This is largely due to the fact that they involve a plurality of variables, determinants, and contexts which themselves interact with and affect one another. Indeed, as it is outlined by Sen, the capability approach is largely unable to account for the complexity and dynamism of a person’s capability set and his/her social and personal context. In practice, the approach cannot readily distinguish between an individual’s resources, conversion factors, and valuable functionings. While conceptually clear cut, the relation between resources, functionings and their conversion is empirically less clear, since some functionings might be considered resources for other functionings, some resources might be actually considered functionings and so on. This ‘circularity problem’ points to the fact that all three concepts seem to be mutually endogenous and interdependent, which presents problems for both conceptualisation and measurement. In this paper, I outline a new participatory methodology to operationalise this multidimensionality that draws fuzzy cognitive mapping and graph theory. This approach has been developed as part of my doctoral research into the determinants of food insecurity in urban migrant communities, and I demonstrate its efficacy by way of case study. Fuzzy cognitive maps are models of how a system operates based on defined variables and the causal links between these variables. These variables can be measurable physical quantities such as amount of precipitation or complex aggregate and abstract ideas such as people’s welfare. The person making the fuzzy cognitive map decides what the important variables are that affect the system and then draws causal relationships among the variables. The paper will outline how to elicit fuzzy cognitive maps from participants as well as how individual participant maps can be integrated into an aggregate model, using network mapping techniques and graph theory. I will also outline future methodological possibilities, including the development of causal maps using a combination of cognitive mapping and purposive text data. I argue that such an approach is particularly well suited to operationalize multidimensionality in the capability approach on a number of grounds. First, it takes into consideration the plurality of determinants of food insecurity and the relations between them. At the same time, it provides a set of quantitative tools to assess the intensity of particular connections and locate leverage points in the system. Second, the aggregate model accounts for, and is grounded in, the heterogeneous nature of wellbeing and the contexts in which it is experienced. This ensures that local priorities are not lost in the process of aggregation. Finally, the approach is built on insights from complexity theory, including interdependence, nonlinearity and emergence. Conceding multidimensionality requires that notions of complexity be put at the core of capability-based theories of wellbeing. Crucially, the methodology outlined here would easily resonate with such a framework, while also maintaining enough simplicity to allow ‘operational significance’.