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Record W2760459599 · doi:10.1177/1470357217727678

Who’s devising your theatre experience? A director’s approach to inclusive theatre for blind and low vision theatregoers

2017· article· en· W2760459599 on OpenAlexaffabout
Mala D. Naraine, Margot Whitfield, Deborah I. Fels

Bibliographic record

VenueVisual Communication · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicSubtitles and Audiovisual Media
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsAmateurFilm directorEntertainmentArtTheatre directorProgram directorTransformative learningSociologyPerspective (graphical)Visual artsAestheticsManagementPolitical scienceMovie theaterMedicinePedagogy

Abstract

fetched live from OpenAlex

In this article, the authors present the first documented implementation of a director-produced and delivered audio description (AD) for devising theatre. In a single live, audio-described performance of Highway 63: The Fort Mac Show at Theatre Passe Muraille in Toronto, Canada, the director/describer’s artistically informed approach focuses on entertainment value for blind and low vision (B/LV) theatregoers. In-depth, semi-structured interviews with the director/screenwriter/describer garnered insight into a director’s unique perspective on the development process for the integrated approach to AD, including her artistic choices, expectations and delivery style as a first-time amateur director/describer. The process of developing and delivering integrated AD had a transformative effect on her as a director.

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)0.006
metaresearch head score (Gemma)0.008
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: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0120.009
Scholarly communication0.0110.004
Open science0.0010.011
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0070.001

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 head0.069
GPT teacher head0.366
Teacher spread0.297 · 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

Citations8
Published2017
Admission routes2
Has abstractyes

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