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Record W2996399531 · doi:10.7202/1065078ar

SHAKESPEREAN APPARATUS: EXPLICIT TEXTUAL STRUCTURES AND THE IMPLICIT NAVIGATION OF ACCUMULATED KNOWLEDGE

2019· article· en· W2996399531 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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueSurfaces · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicDigital Humanities and Scholarship
Canadian institutionsVancouver Island University
Fundersnot available
KeywordsComputer scienceHypertextHumanismFacilitationHypermediaSoftwareSonnetNatural language processingHuman–computer interactionInformation retrievalArtificial intelligenceWorld Wide WebLinguisticsProgramming languagePsychologyPhilosophy

Abstract

fetched live from OpenAlex

In its exploration of the potential for hypertextual navigation offered by the new humanistic understanding of text, the article analyzes a traditional humanistic activity — that of annotating a scholarly edition (in this case, one of Shakespeare’s sonnets). It asserts that the interaction allowed by advanced textual analysis software are transferable to all the material that can be linked to the text. Moreover, semantic patterns, especially those identified with machine facilitation, operate in ways akin to hypertextual links.

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)0.000
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: Empirical
Teacher disagreement score0.734
Threshold uncertainty score0.981

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.036
GPT teacher head0.264
Teacher spread0.227 · 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