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Record W2659241536 · doi:10.21992/t9n33b

Sign Language Interpreting in Theatre: Using the Human Body to Create Pictures of the Human Soul

2017· article· en· W2659241536 on OpenAlexvenueno aff
Michael Richardson

Bibliographic record

VenueTranscUlturAl A Journal of Translation and Cultural Studies · 2017
Typearticle
Languageen
FieldPsychology
TopicLanguage, Metaphor, and Cognition
Canadian institutionsnot available
Fundersnot available
KeywordsInterpreterSign languageMeaning (existential)Sign (mathematics)Spoken languageLinguisticsAmerican Sign LanguagePsychologyComputer sciencePhilosophy

Abstract

fetched live from OpenAlex

This paper explores theatrical interpreting for Deaf spectators, a specialism that both blurs the separation between translation and interpreting, and replaces these potentials with a paradigm in which the translator's body is central to the production of the target text. 
 Meaningful written translations of dramatic texts into sign language are not currently possible. For Deaf people to access Shakespeare or Moliere in their own language usually means attending a sign language interpreted performance, a typically disappointing experience that fails to provide accessibility or to fulfil the potential of a dynamically equivalent theatrical translation. I argue that when such interpreting events fail, significant contributory factors are the challenges involved in producing such a target text and the insufficient embodiment of that text. 
 The second of these factors suggests that the existing conference and community models of interpreting are insufficient in describing theatrical interpreting. I propose that a model drawn from Theatre Studies, namely psychophysical acting, might be more effective for conceptualising theatrical interpreting. I also draw on theories from neurological research into the Mirror Neuron System to suggest that a highly visual and physical approach to performance (be that by actors or interpreters) is more effective in building a strong actor-spectator interaction than a performance in which meaning is conveyed by spoken words.
 Arguably this difference in language impact between signed and spoken is irrelevant to hearing audiences attending spoken language plays, but I suggest that for all theatre translators the implications are significant: it is not enough to create a literary translation as the target text; it is also essential to produce a text that suggests physicality. The aim should be the creation of a text which demands full expression through the body, the best picture of the human soul and the fundamental medium of theatre.

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: Empirical
Teacher disagreement score0.609
Threshold uncertainty score0.559

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.078
GPT teacher head0.392
Teacher spread0.314 · 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
Published2017
Admission routes1
Has abstractyes

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