I am an Associate Professor in the Department of English at Rutgers University, New Brunswick. I study and teach twentieth-century literature in English. My research interests include genre fiction, the sociology of literature, modernism, South Asian literature in English, and the digital humanities. I am the author of Fictions of Autonomy: Modernism from Wilde to de Man (Oxford University Press, 2013).
It’s been a while since I checked in on the statistics for what is laughingly called “the job market” in English for PhDs. But after a few demoralizing conversations with people looking at the thing from various angles (I was the one doing the demoralizing), I realized I wanted an updated version of a chart I last made in 2017, comparing new English PhDs and new faculty job openings.
I have a review essay out in the new issue of American Literary History, under the title “Genre Fiction without Shame.” It’s a longish discussion of Mark McGurl’s Everything and Less and Kim Wilkins, Beth Driscoll, and Lisa Fletcher’s Genre Worlds, ornamented with my Strong Opinions™ about the study of popular genre. The journal permits authors to share an initially submitted version. Bonus features of the latter include a few embarrassing imprecisions in quotation and a far superior choice of typeface; for more precision and worse typography, refer to the published version.
From the essay:
Is literary studies on the verge of a genre turn of its own? When so eminent a literary historian as Mark McGurl argues that “genre fiction is the heart of the matter of literature” (xviii) in the present era, it might seem so. McGurl’s Everything and Less: The Novel in the Age of Amazon (2021) maps out a wide range of fiction subgenres, placing them at the center of contemporary fiction. Working in a different vein, Kim Wilkins, Beth Driscoll, and Lisa Fletcher illuminate the social dynamics of genre-fiction production in their collective monograph Genre Worlds: Popular Fiction and Twenty-First-Century Book Culture (2022). Yet, like the genre turn in literary fiction, this recent genre-fiction scholarship evinces a reified understanding of its subject. McGurl relies on high-literary assumptions about genre, even as he deflates the pretensions of literary fiction; Wilkins et al., writing as insiders, take the cohesiveness and autonomy of their “genre worlds” for granted. These contrasting limitations are both, it seems to me, responses to genre fiction’s status in the literary field. Without a fuller analysis of how that status is produced, work on genre fiction misses major aspects of the phenomenon, especially the contingency of genre categories and the variability of reader response.
Despite the Strong Opinions™, mainly I pay tribute to the new ground opened up by these two books for systematic studies of genre fiction in the full complexity of its social existence. Now if only I can get my own contribution done before the study of literary institutions becomes purely archaeological.
This past Tuesday, at the kind invitation of Wen Xin, I gave a talk at the University of Kansas, under the title “Data Is a Sandwich: Lessons from the Computational Literary Field.” My slides (PDF) might only be of use for pictures of the titular sandwich, but they do also contain R code for reproducing my figures demonstrating some of the lessons I taught out of my dataculture package of cultural data in last year’s Data and Culture course. The talk itself was a bit of a retrospective on different things I’ve tried to do in literary data analysis since I first started dabbling some 14 years ago (!?!), with gestures towards what I think are the lessons I learned about how useful data gets made and turned into evidence for meaningful scholarly arguments.
I honor Labor Day the way Karl Marx intended, by finishing up my syllabuses. Since it’s September, it must be Early Twentieth-Century Fiction time. I am also teaching Introduction to Science Fiction for the first time. Will there be Star Trek? Of course there will be Star Trek. The links go to pages with abbreviated schedules, but the full syllabuses are available in PDF: Early 20th-c. and SF. The two syllabus formats are not automatically generated from the same source, because getting that right (for my definition of “right”) remains much harder than it should be, and I am trying to spend less time fiddling with computer-y stuff and more time peering into the unhallowed depths of genre-fiction history.
I made an R package with some “cultural” datasets of various kinds that might be of pedagogical use. It is available on github as
agoldst/dataculture. See the repository page for a summary of the datasets, which I used to teach introductory analyses of:
- cultural tastes over time and social space (names, music genres, recipes)
- textual/paratextual signs of fictional genre (text-mining science fiction and crime)
- historical and fictional social networks (Hamlet characters and eighteenth-century Bostonian troublemakers)
If that sounds interesting, take a look at the package and the lecture slides and lab exercises from the course I created it for, “Data and Culture” (Fall 2022). I’m hoping to save someone somewhere a few steps of wheel-reinventing.