This post extends a conversation I began on 19 May 2010, titled testing the validity of complex systems.
My basic argument is that we simply too often assume that any topic we are studying is a complex system simply because we say so--regardless of the definition we are using.
Now I know that the definition of a complex system is encyclopedic, such that many definitions exist. And, of course, I am not arguing for a single standard by which all topics should be judged worthy of being called a complex system.
But, I am arguing that, regardless of the definition researchers use, they should have some way of testing their topic to see if and how it acts like a complex system.
For example, pretend one assumes that complex systems have the following characteristcs: they are self-organizing, emergent, operating near chaos, and agent-based. Definition in hand, one then goes out to study a local community, a formal organization or some social network. Before one begins, however, shouldn't there be some set of preliminary tests done; some sort of way to determine if what one is studying is actually self-organizing, emergent, etc? Related, what would one look for to determine if such characteristics exist? What tests would one use? What methods would be relevant to conduct these tests? And, what if one finds that one or more of these characteristics is lacking, or only exists in a modified form? What then?
Again, I am not saying that one test or definition fits all. But, I am saying that the definitions complexity scientst use to identify, model and study various topics as complex systems should have a bit more empirical rior. These definitions should be tested and held up to empirical validity and reliability. One should be able to talk intelligently about what one means when one is calling something a complex system.