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Record W4251910415 · doi:10.1386/jafp.9.2.191_1

Practitioners’ Perspectives

2016· article· en· W4251910415 on OpenAlexaff
Tom Ue, Christopher Shinn

Bibliographic record

VenueJournal of Adaptation in Film & Performance · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicTheatre and Performance Studies
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
Fundersnot available
KeywordsConversationSociologyPsychologyGender studiesCommunication

Abstract

fetched live from OpenAlex

Abstract The following interview was completed by e-mail on 26 November 2015. It focuses on Christopher Shinn’s Teddy Ferrara (2015), a play both informed by and in response to a number of recent suicides, including that of Tyler Clementi. This conversation explores Shinn’s creative processes for the play, which began its theatrical life in the Goodman Theatre in Chicago before being brought to the Donmar Warehouse in London where it had its London premiere. It goes on to examine Shinn’s views about the adolescent experience, desire, and LGBTQ issues, and it suggests some avenues for more positive ways to engage in discussions despite our differences.

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)0.040
metaresearch head score (Gemma)0.063
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.040
Threshold uncertainty score0.210

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0400.063
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.005
Science and technology studies0.0240.015
Scholarly communication0.0180.012
Open science0.0040.016
Research integrity0.0140.019
Insufficient payload (model declined to judge)0.0400.005

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 head0.032
GPT teacher head0.239
Teacher spread0.207 · 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 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

Citations2
Published2016
Admission routes1
Has abstractyes

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