The point on complexity sort of brings up something I was hoping somebody would. Both the fact that they represented these dimensions with binary state and that there are only two distinct dimensions (when there are almost certainly more) are examples of creating a model that is “good enough.”

I haven’t seen anything in model theory that talks about this, maybe because I’m looking in the wrong place or not hard enough. It’s more in the practice of applying and building models, but models that are “good enough” are ones that most effectively explain phenomena or are most useful, while maintaining boundaries and a level of abstraction that keep the model simple enough to be used and understood easily.

But yes, the main point you’re making is that the type of complexity I’m talking about here will increase exponentially as dimensions are added and as dimensions are chunked into more states. All the more reason to keep models just simple enough to be effective.