  Computerized document classification already orders the news articles that
Apple's "News" app or Google's "personalized search" feature groups together to
match a reader's interests. The invisible and therefore illegible decisions
that go into these tailored searches have been the subject of a critique by
scholars who emphasize that our intelligence about documents is only as good as
our ability to understand the criteria of search. This article will attempt to
unpack the procedures used in computational classification of texts,
translating them into term legible to humanists, and examining opportunities to
render the computational text classification process subject to expert critique
and improvement.
