Having an unpleasant reaction to Lisa Gitelman’s bad shrimp analogy

Digesting Lisa Gitelman’s admonition about data and rawness, most of her argument went down fine: after all, disciplinary cuisines aside (171), what she most stridently calls for is the disclosure of epistemological and methodological concerns, or recipes, and for us to discard the notion of any particular palate—whether one makes purportedly subjective or objective claims for a living—being truer than another. However, the jumbo shrimp analogy (168) stuck like a bone in my throat, in spite of how cheerfully Gitelmen provides and then discards it. I found it ill-conceived, and here’s why: “raw” is an absolute term, and while it may be an inaccurate and blinkered way to refer to data, it doesn’t really bear comparison to “jumbo,” which is a relative term for shrimp. These shrimp found here are more hefty than the already-large shrimp found near, which are in turn more generously-proportioned than the pedestrian, moderately-sized shrimp found over there—thus, “jumbo” in the first case. 

Mark Twain famously attributed to Benjamin Disraeli the quip fond to many a wag: “there are three types of lies: lies, damned lies, and statistics.” To cite either as the author, while often done, seems superfluous—it is such a truism that it doesn’t matter on whose authority we have it. And Gitelman and Manovich agree; both argue that the essential problem with data analysis, no matter how clever, is that sampling facts is a ticklish business. Carelessness and perfidiousness in the case of data collection and analysis end the same, and so whether by accident or design, prejudiced samples produce less generalizable results. The operative principle, then, is nuance, and not only acknowledging that data is always “cooked” but learning how to select it, season it, how to render most effectively the particular characteristics of interest. Thus, I would argue that in his call for “wide data” and in hers for frank disclosure of disciplinary predilections, Manovich and Gitelman in fact do apply the wisdom of fishmongers and think about scales of data as useful metrics. The jumbo shrimp, after all, is only oxymoronic in one iteration—elsewhere the langoustine and the tiger prawn produce none of the consternation apparently plaguing the American shopper.

I think it bears pointing out that the issues Gitelman has with jumbo shrimp and raw data seem to come down to the notion that somehow we’re being tricked into thinking the thing at hand it something other than it is: so, the shrimp is not a shrimp, it’s a jumbo shrimp, and data isn’t contingent observation about the material world, it is unbracketed, unadulterated truth. And while conflating industrial aquaculture and the empirical or positivist bent may work on many levels—after all, industrial aquaculture and many of its devastating consequences originate in notions that the world is entirely knowable and always improvable—there are some close to the surface in which that shorthand just doesn’t.

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Having an unpleasant reaction to Lisa Gitelman’s bad shrimp analogy

Data and the Superpanopticon

Because I’m interested in working with reality television, I was most intrigued by Lisa Gitelman’s discussion on the problems of ‘dataveillance,’ or the collection and usage of data from individuals regarding their identities and personal attributes. She questions the ethics of this process in our current age, citing Rita Raley’s examination of those who try to push back with online tools that inhibit the ubiquitous data mining of our contemporary Internet. In ‘Dataveillance and Counterveillance’ (Raley’s chapter in the book for which Gitelman provides the eponymous introduction piece), Raley unpacks the typical argument in favor of allowing passive data mining: a “personalized Internet” is only possible if our individual tastes and preferences are fair game for circulation, and “voluntarily surrendering personal information becomes the means by which social relations are established and collective entities supported” (125). The necessity of trading privacy for inclusion is certainly problematic, and I see it as a specific link to my interest in reality television shows wherein contestants formally trade their privacy (as well as their very power of self-representation) for the benefit of inclusion on a television show and potential financial gain. Raley then introduces the idea of a ‘superpanopticon’ which must necessarily exist to register our interpellation by databases; while this for her is a link to a discussion of ‘corpocracy’ and ‘cybernetic capitalism,’ I identify it for my purposes as a term to describe the reality show institution which mines identity and individual action to construct the desired narrative for commercial purposes.

Aiding my consideration of a show like Survivor as one such ‘superpanopticon,’ Raley cites Kevin D. Haggerty and Richard V. Ericson who posit that surveillance “operate[s] through processes of disassembling and reassembling. People are broken down into a series of discrete informational flows which are stabilized and captured according to pre-established classificatory criteria. They are then transported to centralized locations to be reassembled and combined in ways that serve institutional agendas” (127). This is a lengthy excerpt, but I find it so startlingly appropriate to describe how contestants can be treated on reality television shows like Survivor. Contestants’ thoughts and feelings are mined on location through individual interviews known as ‘confessionals,’ which are then transported to a central editing station to be assembled together at the whim of the producers. My initial project idea to explore Survivor confessional frequencies by episode and season draws from this notion (which I could not have stated so well before) that players are mere building blocks in a larger narrative, who can be highlighted or backgrounded as the show desires. After reading Gitelman’s caution regarding the ethics of dataveillance, though, I begin to wonder: Even if I can use the confessional data to learn and expose something about the superpanopticon of Survivor, am I still inescapably guilty of drawing on the identities and representations of others for the alleged benefit of collective knowledge?

Kelly-purple-never-talks

“Purple” Kelly Shinn, infamous as one of the most under-edited contestants in  Survivor history

Data and the Superpanopticon