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Record W2894427911 · doi:10.1353/aq.2018.0048

Run with Whatever You Can Carry": Cross-Platform Materials and Methods in Performance Studies–Meets–Digital Humanities

2018· article· en· W2894427911 on OpenAlexaboutno aff
T. L. Cowan

Bibliographic record

VenueAmerican Quarterly · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicTheatre and Performance Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAbsurdityPerforming artsContext (archaeology)Digital humanitiesLaptopArtPerformance artHumanitiesArt historyHistoryVisual artsAestheticsMedia studiesLiteratureSociologyComputer science

Abstract

fetched live from OpenAlex

Run with Whatever You Can Carry":Cross-Platform Materials and Methods in Performance Studies–Meets–Digital Humanities T. L. Cowan (bio) Remember to Surface This essay is structured by my remix of "Instructions," a 1996 song by Veda Hille, a Vancouver-based songwriter, musician, and performer.1 Each heading is an instruction from her song, which I returned to recently as I moved back to Canada after several years of living and working in the United States. It always struck me as a survival guide for the absurdity and brink-of-apocalypse quality of contemporary life. The absurdity (understatement) continues; today's apocalypse, as always, targets some more than others. And many people have already experienced the/an apocalypse many times over. The song was a favorite of mine when I was an undergraduate dropout and emerging performer in Vancouver in the late 1990s. This was, significantly, also around the time that I got my first laptop computer and my first email account, so it also marks my belated entry into a digital existence. The perspective I bring to this AQ forum on methods is shaped by my cross-border, decentered understanding of performance studies and digital humanities, in the context of American/Americas studies more broadly. It is also shaped by what I see as the co-emergence and co-divergence of performance studies and digital humanities as newly articulated scholarly activities. Endeavour to Dive This essay reflects the thinking that I am doing as a scholar and practitioner who moves between performance studies and digital humanities, and digital media studies, all refracted through a kaleidoscopic critical lens that focuses and multiplies my understandings, priorities, and accountabilities toward work that is anti-colonial, trans- feminist and queer'ing, crip'ing, and anti-racist. [End Page 649] Indeed, like the people with whom I am in conversation, we do this work across these and other disciplines, using whatever field, space, or platform we can get our hands on within and beyond the academy. That's the first method. Don't Let Them Shrivel on the Vine The question of what methods the intradiscipline of performance studies brings to the intradiscipline of digital humanities bears considerable attention if we accept that these are two intradisciplines with distinct genealogies, protocols, methods, approaches, critical orientations, and commitments. But first let's trouble that a bit. Don't Think of It as Reasonable, Think of It as Terrifying I am reminded of Linda Tuhiwai Smith's clarification in Decolonizing Methodologies that "academic knowledges are organized around the idea of disciplines and fields of knowledge. These are deeply implicated in each other and share genealogical foundations in various classical and Enlightenment philosophies."2 She notes that disciplines are "also isolated from each other through the maintenance of … disciplinary boundaries," and that they are "not simply … a way of organizing systems of knowledge, but also … a way of organizing people or bodies."3 Performance studies: you go in this building and study these things in these ways. Digital humanities: you go in this building and study these things in these ways. Both of you: demonstrate unique observations of new objects of study and analysis that dutifully learn from—but correct, expose, and reveal—the research and analysis of earlier scholars, and provide compelling evidence of your claims. Collect things and keep them (encrypted). Best if you discover something. Best if you are a pioneer on—or, better yet, break through—the frontier, wherever that is. When You Hear a Mechanical Instrument, Think of a Child Shrieking So, in any case, let's agree that we're talking about performance studies and digital humanities in the context of the in-bed-edness of university financial, social, and intellectual power with imperialism, genocide, mass enslavement, and settler colonialism in the United States and Canada and—in various manifestations—across the Americas. And in the context of the exploitation of workers within—and the poisoning of the land, water, and atmosphere that absorb the excesses of—the industries that fuel our scholarly disciplines and [End Page 650] the technological mobilities that we must keep up in order to keep going in them. As Safiya Noble writes, these are "hidden...

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.126
metaresearch head score (Gemma)0.090
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.126
Threshold uncertainty score0.668

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1260.090
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0110.027
Scholarly communication0.0150.012
Open science0.0040.023
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0220.005

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.033
GPT teacher head0.313
Teacher spread0.280 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations2
Published2018
Admission routes1
Has abstractyes

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