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Record W2942955366 · doi:10.15353/kinema.vi.1321

Adapting The Tempest

2015· article· en· W2942955366 on OpenAlexvenueno aff
Antonio Sanna

Bibliographic record

VenueKinema A Journal for Film and Audiovisual Media · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicShakespeare, Adaptation, and Literary Criticism
Canadian institutionsnot available
Fundersnot available
KeywordsTempestInterpretation (philosophy)LiteratureArtRevelsAestheticsHistoryLinguisticsPhilosophy

Abstract

fetched live from OpenAlex

ADAPTING THE TEMPEST: JULIE TAYMOR'S REVELS Adaptations and appropriations of Shakespeare's plays demonstrate the unending life of a series of canonical texts that still invite numerous forms of interpretation. Simultaneously, they also offer a tool for the (re)interpretation of the English playwright's works. This is definitely the case of Julie Taymor's recent film The Tempest (2010), which partially alters the structure of Shakespeare's last solo play, but also actively engages with the academic debates on the work's thematic concerns. Nevertheless, Taymor's film could be seen as faithful to the original source and as fully realizing on the screen its fantastic elements, especially through the use of the special effects. Taymor's The Tempest utilizes the original heightened language of the seventeenth century - which certainly gratifies those spectators that enjoy what Stephen Greenblatt has defined as Shakespeare's "infinite delight in language"(1) - and maintains the main dialogues of the original...

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)0.002
metaresearch head score (Gemma)0.004
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 score0.010
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0100.014
Scholarly communication0.0080.004
Open science0.0010.006
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0040.001

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 head0.119
GPT teacher head0.296
Teacher spread0.177 · 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
Published2015
Admission routes1
Has abstractyes

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