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Record W2479301419 · doi:10.1017/ccol0521868386.002

Crisis in Editing?

2006· book-chapter· en· W2479301419 on OpenAlexaboutno aff
Edward Pechter

Bibliographic record

VenueCambridge University Press eBooks · 2006
Typebook-chapter
Languageen
FieldArts and Humanities
TopicTranslation Studies and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsChoseTheme (computing)CurrencyKingdomHistoryLiteratureMedia studiesArtComputer sciencePolitical scienceSociologyWorld Wide WebLawPhilosophyLinguistics

Abstract

fetched live from OpenAlex

For the first time in fifty-four years, the editors of Shakespeare Survey have devoted an issue to ‘Editing Shakespeare’. Perhaps they are motivated by a concern that has been gaining in currency since at least as early as 1988, when Randall McLeod chose ‘Crisis in Editing’ as the theme for the annual Conference on Editorial Problems at the University of Toronto. The Division of the Kingdoms had appeared five years earlier and McLeod’s own ‘UN Editing Shak-speare’ a year before that; but ‘Crisis in Editing’ extended its claims beyond the special problems of the Lear text or any particular quarrel with received opinion to suggest that editing itself was in a critical condition. This idea, in one form or another, has been in regular circulation ever since. In 1993, Margreta de Grazia and Peter Stallybrass, reflecting on the proliferation of Lear versions, foresaw ‘a radical change indeed’ not just in textual criticism but in all forms of Shakespearian practice. ‘As a result of this multiplication, Shakespeare studies will never be the same.’ The editors of two recent collections on editorial matters claim we are in the midst of a transformation analogous to the sweeping institutional and conceptual revolutions – the new maps, the Reformation, print dissemination – of the Renaissance itself. Implicit in these momentous re-enactments is the notion of a paradigm shift and, in the most recent Cambridge Companion , Barbara Mowat adopts this idea as the organizing principle for her analysis, concluding with a catalogue of the recently produced ‘paradigm-threatening’ critiques as a result of which ‘hardly a “fact” supporting New Bibliographical assumptions remains standing’.

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)0.007
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.021
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.025
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0090.021
Scholarly communication0.0210.021
Open science0.0020.006
Research integrity0.0030.008
Insufficient payload (model declined to judge)0.0130.003

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 head0.038
GPT teacher head0.206
Teacher spread0.168 · 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 designNot applicable
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".

Quick stats

Citations5
Published2006
Admission routes1
Has abstractyes

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