Chapter 4 provides a definition of the visual arts through the lens of complex dynamic systems. Art is defined as (1) a temporally contingent, iterative process involving many interacting components; (2) a distributed and situated process of enactment; (3) an emergent phenomenon; (4) a unique and authentic visual embodiment of self-determined artistic meaning; (5) an embodied meaning that exploits meta-stable, critical state dynamics of values; (6) a pluriform complex dynamic; and (7) a process governed by a dynamic of presentation, re-presentation, and reference. Finally, definitions of art are presented as critical state attractors in artworld systems (all the technical concepts are explained in Chapter 3).

The small and somewhat fringe praxis of processual self-esteem research is described with respect to its enactment of a process ontology. The chapter shows that a process approach has resulted in a focus on ‘how’ questions in self-esteem research (rather than on predictive validity, for example) and a more pluralistic approach to the operationalization of self-esteem. What the various processual-studies reviewed have in common is a conceptual and methodological approach to self-esteem as a situated and action-based process, rather than a thing that individuals have to different degrees. Here, the central role of situational affordances is highlighted. This processual praxis often relies explicitly on complex dynamic systems principles, such as self-organization, emergence, variability, and attractor landscapes. With processes and actions as its focus, this praxis constructs self-esteem knowledge that emphasizes one’s agency in the world and the centrality of our actual context-bound actions and experiences as we move through it. This chapter ends with a discussion of how a process approach is beneficial for the lived reality of self-esteem, where individuals are encouraged to embrace and reflect on their situated and fluctuating experiences of self, rather than a pursuit of ‘high’ self-esteem.

With this chapter, we contrast the mainstream explanatory practices with forms of causality that are processual: complex causality. Complex dynamic systems are used as a framework, incorporating principles such as emergence, self-organization, circular causality, and perturbations. With this alternative, processes themselves are seen as causes, making causality a moving and dynamic phenomenon. We conclude with descriptions of various concrete causal models that can be used to help researchers understand causality via processes.