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Record W2074279928 · doi:10.4000/jtei.210

‘The Apex of Hipster XML GeekDOM’

2011· article· en· W2074279928 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of the Text Encoding Initiative · 2011
Typearticle
Languageen
FieldArts and Humanities
TopicDigital Humanities and Scholarship
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsDigital humanitiesField (mathematics)SociologyCommonsEpistemologyVirtueDigital libraryComputer scienceLibrary sciencePolitical scienceLinguisticsPhilosophyLaw

Abstract

fetched live from OpenAlex

If the notion of the methodological commons is as centrally located as we believe it to be in any visualization accurately depicting the intellectual structure of the digital humanities and digital literary studies (McCarty 2005, 119), then so, too, must be the community itself whose members provide that which populates the commons. As an interdiscipline, humanities computing has always well-understood its methodologies; indeed, the digital humanities (of which digital literary studies is a part), more generally, have made a virtue of the way in which they render explicit and tangible the theoretical models that govern the representative and analytical endeavour of their fields via computational application. So, too, have those in the field understood and documented its formal structures and institutional manifestations, a chief example being the Text Encoding Initiative itself. Less explicitly rendered and less formally documented–though intuited by its chief practitioners and builders–is the exact nature of the community itself, its depth and breadth, its own centre and, perhaps more important in a field whose embrace of interdisciplinarity is far from self-serving, its periphery and those aspects of which promise to become central. This article presents work carried out in conjunction with the Text Encoding Initiative Consortium, a foundation of many digital literary studies projects, work that seeks to document the full nature of its community, from the institutional and research project groups that comprise the formal consortium at centre to those who appear on the other side of the easily-permeable periphery that separates it from the centre, largely individual practitioners in areas hitherto not closely identified with the digital humanities but clearly sharing methods and tools, thus suggesting their place in the same communities of practice, as they are members of the same methodological commons. This methodological approach is drawn from marketing and organizational behavior, manifest in social networking, in the study of viral marketing campaigns conducted in online environments. The method for this work was centred around a viral marketing experiment designed to showcase the TEI and novel ways that it can be used to encode different kinds of text. At the heart of the experiment was a Bob Dylan song and its associated video which incorporated text; encoded text was overlaid and the video was posted to YouTube and a blog with links to the TEI website with analysis of traffic patterns carried out.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.791
Threshold uncertainty score0.958

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.155
GPT teacher head0.246
Teacher spread0.091 · 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