MétaCan
Menu
Back to cohort
Record W4235421417 · doi:10.1017/ccol9780521898881.011

Channelling the ghosts: the Wooster Group’s remediation of the 1964 Electronovision <i>Hamlet</i>

2008· book-chapter· en· W4235421417 on OpenAlexaboutno aff
Thomas Cartelli

Bibliographic record

VenueCambridge University Press eBooks · 2008
Typebook-chapter
Languageen
FieldEconomics, Econometrics and Finance
TopicCinema and Media Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHAMLET (protein complex)GreenwichArtInterpretation (philosophy)AdmirationPerformance artArt historyHistoryLiteraturePhilosophy

Abstract

fetched live from OpenAlex

In early February 1964 when the buzz around the scandalous affair between Richard Burton and American screen goddess Elizabeth Taylor was at a fever-pitch, a new Broadway-bound production of Hamlet began to take shape in Toronto under the direction of the already legendary John Gielgud and starring Burton in his third go-round in the title role. Rehearsals with a uniformly accomplished supporting cast of British and American actors – which included such then and later-to-become stage-luminaries as Hume Cronyn, George Rose and John Cullum – proceeded at a speedy clip, though not without distractions prompted by occasional sightings of Ms Taylor. Sources indicate that Burton accepted instruction from Gielgud in an understatedly deferential manner – amicably trading anecdotes with him about fellow stage-legends, Ralph Richardson and ‘Larry’ Olivier – but seldom followed the old master’s directives, much less seemed to work very hard at mastering his lines. Although the cast uniformly evinced respect and admiration for Gielgud – who seemed to know all their parts by heart and could rehearse them backwards and forwards – they also found themselves at sea without a rudder as opening night beckoned, lacking any determinate sense of an overarching concept or sustained interpretive focus for the production itself. Seriously professional to a fault, the cast was often bewildered by the variability of Gielgud’s daily notes and directives, which would require, for example, the actor playing Guildenstern to be meekly obsequious in one scene, aggressively inquisitorial in another, without developing a consistent through-line of interpretation that would render his changes in tone coherent.

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 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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.929
Threshold uncertainty score0.743

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 science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.025
GPT teacher head0.167
Teacher spread0.142 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations3
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueCambridge University Press eBooksSame topicCinema and Media StudiesFrench-language works237,207