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If you had a million labelled postmodern and non-postmodern papers, you could decently identify them.
You could categorise most papers with fewer labels using citation graphs.
You can recommend papers, as you would Amazon books with a recommender system (using ratings).
There are hundreds of ways to apply machine learning to academic articles; it's a matter of deciding what you want the machine learning to do.
Sure, I guess my question was whether you'd think that it'd be possible to do this in a way that would resonate with readers. Would they find the estimates of quality, or level of postmodernism, intuitively plausible?
My hunch was that the classification would primarily be based on patterns of word use, but you're right that it would probably be fruitful to use at patterns of citations.