Observations re the Modeling Relation
Rosen’s modeling relation presumes some kind of objectivist stance. Nowhere on this chart does one see a “perceiver” or “self.” Thus, Rosen’s modeling relation assumes a realist world — the same world as traditional management teachings. Rosen’s modeling relation assumes that we can do one-to-one mapping, world to model and model to world. This same one-to-one mapping exists in how managers are taught to rely on the Gaussian distribution. As long as Gaussian predictions hold up, it is fine to use Gauss as a model. As a manager I can make predictions. Those predictions have implications for the world. Most of the time those implications are validated. Sometimes as a manager I need to tweak my encoding and decoding schemes, but in general the schemas are okay. Once we accept, however, that the Gaussian description of the world isn’t the real world because it ignores partial dependence and partial correlation, how do we fix this?
Rosen assumes that one validates models via prediction. In general, when one is dealing with physical aspects of physical things, Rosen’s conception works pretty well. However, when one gets into things that are more abstract, semiotic or conceptual, Rosen’s modeling relation has some problems. Rosen’s modeling relation assumes that that mapping’s existence is the definition of a model. No self; no perceiver; no observer. The absence of self is a big deal, not a little deal. One of the things we do in this book is to rebuild the modeling relation from a constructivist point of view. Complexity theory tells us that a model only works if there is a self included.
