Nan Z. Da
I want to state that nothing about this forum has been unbalanced or unfair. I wrote the article. Those who may not agree with it (in part or in its entirety) have every right to critique it in an academic forum.
What my critics and neutral parties on this forum seem to want from “The Computational Case” is nothing short of: (1) an across-the-board reproducibility check (qua OSC, as Piper suggests), plus (2) careful analyses of CLS work in which even the “suppression” of tiny hedges would count as misrepresentation, plus (3) a state-of-the-field for computational literary studies and related areas of the digital humanities, past and emergent. To them, that’s the kind of intellectual labor that would make my efforts valid.
Ted Underwood’s suggestion that my article and this forum have in effect been stunts designed to attract attention does a disservice to a mode of scholarship that we may simply call critical inquiry. He is right that this might be a function of the times. The demand, across social media and elsewhere, that I must answer for myself right away for critiquing CLS in a noncelebratory manner is a symptom of the social and institutional power computational studies and the digital humanities have garnered to themselves.
Yes, “field-killing” is a term that doesn’t belong in scholarship, and one more indication that certain kinds of academic discourse should only take place in certain contexts. That said, an unrooted rhetoric of solidarity and “moreness”—we’re all in this together—is a poor way to argue. Consider what Sarah Brouillette has powerfully underscored about the institutional and financial politics of this subfield: it is time, as I’ve said, to ask some questions.
Underwood condemns social media and other public responses. He has left out the equally pernicious efforts on social media and in other circles to invalidate my article by whispering—or rather, publically publishing doubts—about Critical Inquiry’s peer review process. It has been suggested, by Underwood and many other critics of this article, that it was not properly peer-reviewed by someone out-of-field. This is untrue—my paper was reviewed by an expert in quantitative analysis and mathematical modeling—and it is damaging. It suggests that anyone who dares to check the work of leading figures in CLS will be tried by gossip.
Does my article make empirical mistakes? Yes, a few, mostly in section 3. I will list them in time, but they do not bear on the macro-claims in that section. With the exception of a misunderstanding in the discussion of Underwood’s essay none of the rebuttals presented in this forum made on empirical grounds have any substance. Piper’s evidence that I “failed at basic math” refers to a simple rhetorical example in which I rounded down to the nearest thousand for the sake of legibility.
Anyone who does serious quantitative analysis will see that I am far from being the ideal candidate for assessing this work. Still, I think the fundamental conflict of interest at issue here should be obvious to all. People who can do this work on a high level tend not to care to critique it, or else they tend not to question how quantitative methods intersect with the distinctiveness of literary criticism, in all its forms and modes of argumentation. In the interest of full disclosure: after assessing the validity of my empirical claims, my out-of-field peer reviewer did not finally agree with me that computational methods works poorly on literary objects. This is the crux of the issue. Statisticians or computer scientists can check for empirical mistakes and errors in implementation; they do not understand what would constitute a weak or conceptually-confused argument in literary scholarship. This is why the guidelines I lay out in my appendix, in which many people are brought into peer review, should be considered.
NAN Z. DA teaches literature at the University of Notre Dame.