… So does it make sense to compare any finite list of models when we do not literally believe any of them? The answer is: sometimes.
  First, we would hope that, while none of the models is exactly correct, at least one is approximately correct. It behooves the data analyst to do common sense exploratory analysis — checking residuals, for example — to make sure that not all of the models are heinously wrong. [---snip---]
  Second, even when all models are wrong, it is useful to consider the relative merits of two models. Newtonian physics and general relativity are both wrong. Yet it makes sense to compare the relative evidence in favor of one or the other. …

Any discussion between Newtonian physics and general relativity had been a very grief subject for physicists and philosophers. For nowadays statisticians, it’s just another example.