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Record W4237668652 · doi:10.33137/rr.v38i4.26381

The Quest for <i>Cardenio</i>: Shakespeare, Fletcher, Cervantes, and the Lost Play

2016· article· en· W4237668652 on OpenAlexvenueno aff
David Carnegie, G. Taylor, Ernst Gerhardt

Bibliographic record

VenueRenaissance and Reformation · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicShakespeare, Adaptation, and Literary Criticism
Canadian institutionsnot available
Fundersnot available
KeywordsArtLiteratureHistoryPhilosophy

Abstract

fetched live from OpenAlex

Documentary evidence of the lost play Cardenio, now thought to have been written collaboratively by Shakespeare and John Fletcher, is relatively slight.The Cardenio-plot derives from episodes in Cervantes's 1605 Don Quixote, translated into English in 1612 by Thomas Shelton.The adaptation of these episodes into a play may be witnessed by two payments to the King's Men for performances in 1613.On May 20, the King's Treasurer paid the King's Men for their performance of six plays, among which was "Cardenno." Another payment was made some weeks later on July 9 for performance of a single play, this time identified as "Cardenna." Forty years later "The History of Cardenio, M r Fletcher.& Shakespeare" (12) was entered, along with forty-two other titles, into the Stationers' Register by Humphrey Moseley.After Moseley's death, his copyrights were sold in 1718, and as "The History of Cardenio" was among these, a manuscript of the play may also have been part of the exchange.In December 1727, Lewis Theobald staged Double Falsehood; or, The Distrest Lovers, a play whose action is similar to the Quixote episodes.Theobald

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)0.001
metaresearch head score (Gemma)0.002
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.103
Threshold uncertainty score0.205

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0070.018
Scholarly communication0.0140.014
Open science0.0010.002
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0190.002

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 head0.017
GPT teacher head0.222
Teacher spread0.205 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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