For all of its advances (and they are many) complexity science has yet to bridge fully the rift between qualitative and quantitative method.
Before I explain myself, however, some quick definitions are in order. First, by qualitative method, I mean the non-numerical analysis of narrative and verbal data, as typically studied in historical inquiry, ethnography, qualitative interviews, and grounded theory. By quantitative method, I mean the study of numerical data, primarily through the application of statistics and top-down equation-based modeling.)
To its credit, complexity science has significantly progressed the qualitative analysis of numerical data. By "qualitative analysis" I mean the study of the complex, emergent, relational, dynamic, evolving, idiographic dimensions of numerical data. In fact, one could claim that complexity science method is really a major advance in the qualitative study of complex numerical data.
What complexity science has not advanced, however, is the non-numerical study complexity. To date, only a handful of articles have applied qualitative method to the study of complexity. And even fewer articles have examined how to advance the usage of qualitative method for studying complex systems.
The earliest examples I know of that apply qualitative method to the study of complexity were written by Crabtree and colleagues (most of whom are in medicine, nursing or health finance) and their study of medical practices:
1. Crabtree, B. F. (1997). Individual attitudes are no match for complex systems. Journal of Family Practice, 44(5), 447-448.
2. Crabtree, B. F. (2003). Primary care practices are full of surprises! Health Care Management Review, 28(3), 279-283.
3. Crabtree, B. F., Miller,W. L., Aita,V. A., Flocke, S. A.,&Stange, K. C. (1998). Primary care practice organization and preventive services delivery: Aqualitative analysis. Journal of Family Medicine, 46(5), 403-409.
4. Crabtree, B. F., Miller,W. L.,&Stange, K. C. (2001). Understanding practice from the ground up. Journal of Family Practice, 50(10), 881-887.
The earliest (and most widely popular) example of the development of qualitative method for the study of complex systems is Charles Ragin's Fuzzy Set Social Science (2000). Ragin also has a new book with David Byrne (a prominent British sociologist and leading scholar in the social science application of complexity science--I will blog more about this book later). The title of the book is The SAGE Handbook of Case-Based Methods (2009).
Despite being a small literature within complexity science, these scholars make some very compelling arguments for developing the qualitative (non-numerical) study of complexity. Perhaps the best argument is that a significant amount of data goes unexplored when qualitative method is not used.
What, for example, are the phenomenological dimensions of complex networks? What does it mean for people to be connected to one another by six or fewer links? What are the emotional dimensions of being part of a massive online social network? What role do power, conflict, hate, greed, anger, and love play in the complex global system? How does one study "confidence" in a system? What does a state of domination within a complex social system look like? Is altruism within a system more than a prisoner dilemna? I could go on and on and on.
Okay, just one more example: Think about the current global financial collapse in which most (if not all) the world is struggling? How do people make meaning of this experience? And, to consider second-order cybernetics and sociocybernetics, what consquence does the meaning people make have for the way in which our global economic system will evolve? And so on and so forth.
There is a lot qualitative method can offer complexity science. And, there is a lot complexity science can offer qualitative method. If complexity scientists turned their attention to this dimension of method, they could create some very incredible tools.