I also get annoyed at claims like “everybody does X”, when I don’t do X. However, some time after this post, I read statistical models & the irrelevance of rare exceptions, and found it an interesting counter-perspective:
Yes, the general case is drawn from instances, I’m saying that we shouldn’t get caught up in the details unless they really matter. And if there is a clear statistical generalization, the details matter very little.
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Rare exceptions are irrelevant because almost all models of the real world (not physics) are statistical claims about what’s usually true, not absolute claims about what’s always true. So a rare data point that doesn’t fit is actually *not* a contradiction! Pointing such cases out is just reiterating the tautological fact that statistical models are not absolute, which seems like a total waste of time to me. (Especially if the speaker agrees with the model!)
I’ve noticed this happens more often with careful, intellectually humble thinkers, who often include caveats of the form “But here’s an exception to this strong model I’ve just presented.” I think often they’re trying to proactively defend against others pointing out this case. But to me, this is wrongfully falling into the frame that rare exceptions are relevant criticisms or corrections of a statistical model.
So, rather than defending by acknowledging the rare case, I think it’s far better to break the false frame that rare exceptions are counter-examples and pointing them out is a relevant thing that needs to be addressed. Move into the new, correct frame that this is a statistical model—say by asking them if they actually disagree that the suggested pattern fits in the vast majority of cases and thus is statistically true.
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Finally, I do find rare exceptions relevant when there is a pattern to the exceptions… As an example for this topic, note that in extreme distributions like power law, a “rare exception” that happens at 1% frequency could have 100x intensity compared to the other 99%, and so need to be weighted equally in a model. The generalization of this exception is that the more extreme the distribution, the more rare a rare case has to be to be irrelevant. This generalized exception now improves our model of statistical models.
Though to tie this back into the original post: many of these anecdotes, like the one with the pillow, or the one about Tom Hanks, are in fact not statistical claims where “most people do X” gets rounded to “everybody does X” or “everybody who does X is Y”. The exceptions to these statements aren’t necessarily rare, or even in the minority. So these claims are far more wrong than Orson Scott Card’s “no one does that”, which does seem obviously statistically true.
I also get annoyed at claims like “everybody does X”, when I don’t do X. However, some time after this post, I read statistical models & the irrelevance of rare exceptions, and found it an interesting counter-perspective:
Though to tie this back into the original post: many of these anecdotes, like the one with the pillow, or the one about Tom Hanks, are in fact not statistical claims where “most people do X” gets rounded to “everybody does X” or “everybody who does X is Y”. The exceptions to these statements aren’t necessarily rare, or even in the minority. So these claims are far more wrong than Orson Scott Card’s “no one does that”, which does seem obviously statistically true.