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consistent with all applicable constraints (even those resulting from patterns in the state-spaces representing the system at very different levels of analysis), it’s not quite right to say that the introduction of a new constraint will always affect constraints acting on the system in all other applicable state spaces. Rather, we should just say that every constraint needs to be taken into account when we’re analyzing the behavior of a system; depending on what collection of constraints apply (and what the system is doing), some may be more relevant than others.

The fact that some systems exhibit interesting patterns at many different levels of analysis—in many different state-spaces—means that some systems operate under far more constraints than others, and that the introduction of the right kind of new constraint can have an effect on the system’s behavior on many different levels.

6.3.2 Approximation and Idealization

The worry is this: we’ve established a compelling argument for why we ought not privilege the patterns identified by physics above the patterns identified by the special sciences. On the other hand, it seems right to say that when the predictions of physics and the predictions of the special sciences come into conflict, the predictions of physics ought to be given primacy at least in some cases. However, it’s that last clause that generates all the problems: if what we’ve said about the mutual constraint (and thus general parity) of fundamental physics and the special sciences is correct, then how can it be the case that the predictions of physics ever deserve primacy? Moreover, how on earth can we decide when the predictions of physics should be able to overrule (or at least outweigh) the predictions of the special sciences? How can we reconcile these two arguments?

Here’s a possible answer: perhaps the putative patterns identified by climate science in this