I think this is effectively provable from extraordinarily plausible premises.
1. We want to infer A from Q.
2. Most A we dont know, or have no data for, or the data is *in the future*.
3. Most Q we cannot conceptualise accurately
since we have no explanatory theory in which to phrase it or to provide measures of it.
4. All statistical approaches require knowing frequencies of (Q, A) pairs (by def.)
5. In the cases where there is a unique objective frequency of (Q,A) we often cannot know it (2, 3)
6. In most cases there is no unique objective frequency
(eg., there is no single animal any given photograph corresponds to,
nor any objective frequency of such association).
So, conclusion:
In most cases the statistical approach either necessarily fails (its about future data; its about non-objective associations; it's impossible to measure or obtain objective frequences); OR if it doesnt necessarily fail, fails in practice (it is to expensive, or otherwise impossible, to obtain the authoritative QA-frequency).
Now, of course, if your grift is generating nice cartoons or stealing cheap copy from ebooks you can convince the audience in the magical power of associating text tokens. This, of course, should be ignored when addressing the bigger methodological questions.
In most cases the statistical approach either necessarily fails (its about future data; its about non-objective associations; it's impossible to measure or obtain objective frequences); OR if it doesnt necessarily fail, fails in practice (it is to expensive, or otherwise impossible, to obtain the authoritative QA-frequency).
Now, of course, if your grift is generating nice cartoons or stealing cheap copy from ebooks you can convince the audience in the magical power of associating text tokens. This, of course, should be ignored when addressing the bigger methodological questions.