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).
The other day I was talking with an innocent bystander about some of my past work in the digital humanities. It occurred to me to wonder what a person who went looking for that work would find. The abyss also looks into you. Anyhoo, once upon a time I spent a lot of time working with data from JSTOR’s Data for Research service, a thing that no longer exists, and I produced two fairly elaborate programming projects related to topic models of text: my dfrtopics R package and my dfr-browser topic-model visualization. I am writing this post to announce that those things are still available and continue to shamble on, zombie-like, into the coming apocalypse. But I don’t plan to develop them further.
In my last post on casualization at Rutgers, written November 2021, I discussed statistics on the rise of full-time, non-tenure-track faculty, arguing that this was an increasingly significant yet under-discussed aspect of the broader erosion of the tenure track. I promised then that I’d follow up on some of the details about different categories of faculty and of institutions. Would my dire picture of “twilight for tenure” change if I separated non-medical from medical faculty, or if I paid attention to faculty with non-instructional roles? Well, I’m pleased to report the picture is dire no matter how you paint it. I’ve been looking at the more granular information on higher-education staffing found in the Human Resources data from the Department of Education (specifically, the “Employees by Assigned Position” or EAP data files from IPEDS). Here are some tentative explorations, vacillating between being tediously technical and speculatively broad-brush. Skip to the end for my regular “workers of the world” conclusion followed by faculty-casualization league tables for research universities.
The basic question is, what are the terms of employment for people doing academic work in higher education? The EAP data answer that question by classifying workers at each institution as tenured, tenure-track, non-tenure-track, or “without faculty status,” dividing each category into full-time and part-time categories and according to whether they are in medical schools or not. The EAP survey also subdivides academic workers’ duties into instruction, research, and public service—as well as further categories like librarianship, archiving, and “Student and Academic Affairs.” Graduate workers (“graduate assistants”) are treated as another employee category, assigned either to teaching or research (and medical or non-). That leaves us with many possible ways of cross-cutting or subsetting the data about tenured and contingent academic work. (Obviously such categories do not exhaust the interesting variables; for example, the EAP data does not include any demographic information about each category. These are found in other IPEDS components, which however do not subdivide job categories with the same granularity.) What I want to do here is explore—without being exhaustive about it—whether the divisions matter to our understanding of contingency in the academy. I’m hoping that even if my analysis is wanting, the annotated R code on github, as “tidy” as I can make it, might help others get a leg up on working with this data.
Yesterday I had the privilege of responding to a wonderful talk by Matt Rubery at the Rutgers Initiative for the Book on “Podcasts, Audiobooks, and Podiobooks.” Feeling out of my depth as a non-podcast-listener, I went to my happy place instead, using my response as an occasion for digging around in a period and a medium I know better. Thinking about entanglements of print and audio fiction, I was moved to learn a little bit more about…
(Image from Galactic Central.) I’m not sure bringing this up was particularly illuminating on the subject of podcasts and books, but it was fun for me and I thought I’d set down a couple of things it made me think about.
I caught wind of some of the examples of GPT-3 answering PhD-exam-style questions plausibly. It seems to me an elegant if indirect proof that Wikipedia entries on many topics are written by current or former graduate students, or people with an excellent ability to imitate them. But it also called to mind the famous arithmetic scene in Eugène Ionesco’s La leçon, which I am sure I am not the first to think of in connection with today’s debates over “stochastic parrots.”
Violating my resolution to never click through to NYT higher education coverage, I went and read a report on the scandal over Columbia’s US News rankings. That rankings are “reactive” is not exactly breaking news (see Espeland and Sauder and Fourcade), but the article is worth it for two reasons. The first is the line in my title, which describes Michael Thaddeus, the Columbia math professor whose analysis is the basis for the story. The second reason is the link to the analysis itself, a highly entertaining exercise in checking Columbia management’s dodgy data. I recommend the analysis as an education in the value of looking things up in IPEDS, the Common Data Set, audited financial statements, and other public data sources. And as a reminder that there are many paths to radicalism, including those that go via algebraic geometry.