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Record W2278175612 · doi:10.1017/s0266464x15000469

‘Distilling the Essence’: Working with Shared Experience

2015· article· en· W2278175612 on OpenAlexaboutno aff
Polly Teale

Bibliographic record

VenueNew Theatre Quarterly · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicShakespeare, Adaptation, and Literary Criticism
Canadian institutionsnot available
Fundersnot available
KeywordsThe artsArtVisual artsPerformance artArt historyMedia studiesLiteratureSociology

Abstract

fetched live from OpenAlex

In this wide-ranging interview of 25 November 2014, Polly Teale, writer, director, and Artistic Director of UK-based Shared Experience theatre company, reflects on her stage adaptations of literary works, the lives of their authors, and the processes of adapting texts between genres. Founded in 1975 by Mike Alfreds, Shared Experience has toured internationally from Sydney to Beijing with highly physical stage adaptations of literary texts and biographies that express the inner lives of complex and fascinating characters. Teale discusses the adaptation of her play Brontë to a screenplay, Shared Experience’s upcoming production of Mermaid , and rehearsal strategies she uses to encourage actors to explore the subjective truths that lie beneath the surface of their characters. Besides Brontë , past productions have included Jane Eyre, The Mill on the Floss , and After Mrs Rochester . Shared Experience was recently awarded a £105,000 grant by the Andrew Lloyd Webber Foundation and has won several theatre awards including Time Out ’s Live Award for Best Play in the West End (2004) and an Edinburgh Fringe First Award (2010). Rebecca Waese is a lecturer and researcher in Creative Arts and English at La Trobe University, Melbourne. She is co-writing a book on Polly Teale and has previously written on interdisciplinary adaptations and dramatic modes in Australian and Canadian literature.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.674
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 communication0.0010.000
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 head0.080
GPT teacher head0.243
Teacher spread0.163 · 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 designQualitative
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

Citations1
Published2015
Admission routes1
Has abstractyes

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