Willard McCarty is “a scholar-provocateur,” in the words of David Gants, who is introducing him at the moment. The full title of his keynote is “Beyond the word: Modeling literary context.”
WM is “the heavy metal version of an intellectual butterfly.” That’s in his words. Same disclaimer as with Shillingsburg: dense, dense. Choppy synopsis.
The humanist perspective on tools problematizes them, which is the point of tool development in the humanities. Our job is not to solve or to fix, but to question. Context explains nothing: it is merely more text. And yet, it remains: how else does the textual environment select for meaning, beyond contiguity and syntax?
Modeling defines an intellectual space within which we can apply styles of scientific reasoning without compromising the humanities.
Main kinds of text analysis, and their origins in prior habits of mind:
– Corpus linguistics (main foci: corpus, concordance, collocation; “words are known by the company they keep” [quote from Firth?])
– concordance is more than “known by the company it keeps”. its 17th-century practitioners were thinking typologically.
– Statistics: searching for hidden patterns of meaning
– some working patterns are inherently stochastic, essentially guesswork. (Humanities are intimately tied to stochastic ways of working, which isn’t to imply that sort of work is easy.)
– Metatextual [semantic] encoding: nontextual entity X exists in textual location Y. Gain control of the world by categorizing its parts.
– Relational database design. Resolves an artifact of study into one or more entities sharing an identical set of attributes. Strict logical principles apply, but there’s a trade-off between these principles’ limiting nature and the manipulability they allow for over significant amounts of data.
What does this analysis seek to do? [Here follows a complex argument which, when the webcast of the keynote goes up, I hope to fill in.]
Not building digital replicas of books (a literary jukebox), but modeling (purposeful gerund: the process of modeling!) of cultural artifacts is the point of humanities computing. Computers change the speed at which modeling can happen, and the amount of data that can be modeled. We think differently when more comes more quickly into view. A gap separates, and will always separate, modeling from the model.
The assumption that individual agents of a model are independent variables that don’t affect each other but act separately upon a given entity is erroneous and damaging to research.
Modeling makes our readings more informed.
…As usual when listening to Willard speak, I’m too overwhelmed by all the information flying at me. Consider this a placeholder.
