Thomas Basbøll [yes, I’ve learned how to smoothly do this using alt-o] gives some writing advice:
What gives a text presence is our commitment to asserting facts. We have to face the possibility that we may be wrong about them resolutely, and we do this by writing about them as though we are right.
This and an earlier remark by Basbøll are closely related in my mind to predictive model checking and to Bayesian statistics: we make strong assumptions and then engage the data and the assumptions in a dialogue: assumptions + data -> inference, and we can then compare the inference to the data which can reveal problems with our model (or problems with the data, but that’s really problems with the model too, in this case problems with the model for the data).
I like the idea that a condition for a story to be useful is that we put some belief into it. (One doesn’t put belief into a joke.) And also the converse, that thnking hard about a story and believing it can be the precondition to ultimately rejecting it because its implications don’t make sense. It’s like in chess: the way to refute a move is to consider making the move (which is as irrevocable in a chess context as believing a story is, in the context of basing a social-scientific theory on it.)
I’m also reminded of the advice from Pólya (or somebody like that) about solving math problems. If the question is, “Is statement A true?”, you can try to prove A or find a counterexample. But it’s hard to do both at the same time! Better to take a guess and go from there: if you try and try to prove it and fail, this may give insight into where to find a counterexample (in those folds of the problem that make A so hard to prove); conversely, if you can’t find a counterexample no matter how hard you look, you can try to systematize that search, thus perhaps leading to a proof that no counterexample exists.