On RushTok and algorithms
Thinking
It's been about a month since the conclusion of sorority rush at the University of Alabama, aka #RushTok, but I still find myself thinking about it. I'm not on TikTok, so I missed the viral sensation that was #RushTok in 2021 and 2022, but this year my Instagram scrolling brought me Anne Helen Petersen's curated reposts to her stories (they're saved in a few highlights) and accompanying commentary, and it's been truly fascinating. And a bit horrifying.
I belonged to a sorority at Northwestern University. In fact, I was the president of my sorority chapter, which many people continue to find surprising.[1] NU was (and I assume still is) a very very different greek life culture than Alabama, but some things seem to be universal: the emphasis on the aesthetics of a particular economic class of femme cis white woman, the fraught relationship of the women to the fraternity men, the performativity of rush even in the blessed days before TikTok dancing, and the very real human longing for ritual and belonging. For those first two, I recommend Tressie McMillan Cottom's RushTok column, which is insightful as always.
But one of the most central things holding together the national sorority rush culture is also one of the quietest: the matching algorithm. There's been a small but popular literature on the matching algorithm in economics and operations research, since the problem (like medical residency matching) is a variation of the theoretical Stable Marriage Problem. The most-cited paper is from 1991, and I sincerely doubt that the implementation is the same as it was, but the basic idea almost certainly still holds. The National Panhellenic Council sororities who participate in this particular formal rush process (other greek councils do their own thing) use a shared set of national guidelines for running recruitment, including a detailed algorithm for what's called the "preferential bidding system." At a school like Alabama, carefully choreographing thousands of young women is a logistically staggering undertaking, and the abstraction and impartiality promised by an algorithm provides much-needed structure. It's less necessary but still used at schools with small greek systems. If you're curious about the underlying game theory, that paper linked above gets into the details.
Petersen called attention to the cottage industry of rush consultants, where freshman (or transfer) rushees can pay large sums to women who help them optimize their chances during rush: closet curation, conversational coaching, teaching the hidden curriculum that women who are second- and third-generation sorority women would already know. And, most importantly, strategy. Here's a good sample of what this looks like.
I recall strategy as a fraught topic: to attempt to game the system or not? There were explicit rules, many of which could be broken. But what risks and consequences came along with breaking the rules was somewhere between a rumor and an open secret. There was some discussion of the preferential bidding system around #RushTok this year (as far as I could tell through Petersen's filtering), where at least one viral rushee was dropped by all of the houses--an outcome that in my day, if I recall correctly, was promised not to happen if you and the sororities followed all the rules. The 1991 paper linked above mentions some of this, and it all tracks remarkably well with what I remember from my 2007 experience, down to the lingo.
In the version of the algorithm described in the 1991 paper, bids are determined by carefully-restricted groups of people making physical piles of cards. These days, the algorithm is run on computers. This considerably lightens the lift of coordinating the lists of rushees, though there's still a good amount of manual data entry required. But the software, like the exact implementation of the rules, is decidedly not public. The year I was chapter president, I didn't even have access to it, though I did see the interface in late-night data-entry sessions with my VP recruitment. It was my understanding at the time, that the National Panhellenic Council sent one or more people to actually run the software for campus and handle any algorithmic snafus that arose.
I've been casually poking around the internet for the past couple weeks, hoping someone else has written the STS paper on how the rush algorithm has shaped sorority culture and vice versa, but I haven't found anything.
I have so many questions:
The 1991 paper includes a brief history, but there is a huge gap between 1930 and 1970. When did the current algorithm start being used? The implication is somewhere shortly after 1930, but were there predecessors first? Did anyone ever use tabulating machines to run rush, before computers? Did any of this massive national data-processing project intersect with the histories of women computers? How was this algorithm's development related to the history of game theory (which was later)?
Have the historically white fraternities ever adopted anything similar? What about any of the other greek councils? How might this explain (or be explained by) differences in council priorities?
Who makes and maintains the software? Who actually uses it? Are any of my memories about the software actually correct?
How does the emphasis on quotas (described mathematically in the 1991 paper but effectively attempts to make every sorority approximately the same size) shape the relationships between sororities and their host universities? At NU, this was big--if your sorority didn't meet quota, that became primarily a financial problem (though also a reputational one).
How does the aura of algorithmic impartiality support the gender, race, and class hierarchies that McMillan Cottom highlights as central to Panhellenic institutions? How does the secrecy surrounding the algorithm change that relationship?
I'll stop there. But I might revisit this topic later--it feels both rich and relatively unexplored. As a total newcomer to the world of sorority studies, I expect I'm missing something obvious (I haven't even watched the HBO Bama Rush documentary, for example). Please point me in the right direction, if you have thoughts!
[1] The closest I've ever come to writing personal essays has been about my year as a sorority president. Just one example: that was the year of the swine flu pandemic, and Covid has highlighted a lot of the weirdness of that year, in retrospect. We made a quarantine room! I was hounded by the campus press! Handshakes were forbidden during rush but nobody thought about masks!
Reading
I'm horribly behind on reading the newsletters I subscribe to. And books. I'm horribly behind on all reading, actually. I did manage to read Dave Karpf's latest: the first item here, on what happens when you mix strategy consultants with generative AI, made me chuckle. I spent two years fresh out of undergrad as a consultant and I'm now working in a field where I'm hyper-aware of the tech hype cycle, and he took a look at what happens when those two things come together (spoiler: it's deeply stupid).
Doing
I've been done with the PhD for a couple of months now--it's actually official! Which also means my library access has been cut off 😭. It's been a busy second half of summer, with travel and family visits and the general chaos that comes with life with two little kids (plus a third on the way). But I've managed to revise my outline and draft two sample chapters for my book proposal. Here's hoping it can go out on submission this fall, so I can hurry up and wait.
It is also currently the annual SIGCIS conference, which is online this year, so I'm busy listening to talks and frantically trying to write notes while I try to figure out what social media platform everyone is on these days. (I'm mostly on bluesky @jillianefoley).