Complexity Definitions Need to Best Tested as a Whole

This post extends a conversation I began on 19 May 2010, titled testing the validity of complex systems. This is the fourth post on this topic since then.

Okay, I am getting a bit closer to what I am trying to say about testing. When I say definitions needs to be empirically grounded and tested I mean that the entire definition, as a whole, needs to be empirically grounded and tested. To date, most empirical inquiry in the complexity sciences focuses on parts of the complexity science definition. Researchers study networks or they study dynamics or they study emergence, autopoiesis, self-organization (a.k.a swarm behavior) and so forth. Two things are held as true in these studies. First, that the things being studied are actually complex systems. Second, that the part of the complexity science definition the researcher is studying naturally integrates into the larger complex systems scheme of things. My questions is, how do you know both of these things are true about the topic one is studying?

One way I think researchers can be sure is to do a complete (holistic) test of their topic, (1) to make sure that the definition of a complex system they are using applies and (2) to make sure that their topic fits this definition. For example, if researchers assume that a complex system is self-organizing, emergent, comprised of a large network of interacting agents and open-ended, then these researchers should have a series of tests to validate if this definition (in its entirety) applies to the topic they are studying. Alternatively, such a complete set of tests makes sure that the topic these researchers are studying is actually a complex system, or at least the type of complex system they seek to study.

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