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Record W7114792108 · doi:10.57088/978-3-7329-9027-6_5

Translationstheoretische und -praktische Aspekte der intralingualen Theaterübertitelung

2025· book-chapter· de· W7114792108 on OpenAlexaff

Bibliographic record

VenueAudiovisual translation studies · 2025
Typebook-chapter
Languagede
FieldArts and Humanities
TopicSubtitles and Audiovisual Media
Canadian institutionsPancreas Centre (Canada)
Fundersnot available
KeywordsImprovisationSemioticsIdentification (biology)Translation studies

Abstract

fetched live from OpenAlex

The present chapter focuses on theatre surtitling for an audience who are d/Deaf or hard of hearing (TSDH) in a German-speaking context. This form of translation can be defined as an intralingual, intersemiotic, partial, additive, two-phased translation. Based on two examples from practice, specific translational challenges will be described in detail. Challenges such as improvisation and speaker identification are discussed by drawing on approaches from studies on SDH and interlingual theatre surtitling. Other aspects, such as the translation of music/sound into surtitles, albeit related to SDH as well, hold challenges that are specific to the semiotics of theatre and, therefore, to TSDH. With TSDH being a new research area and practice in the German-speaking context, many research questions remain to be answered. There is a need for appropriate TSDH standards, which can only be developed by involving the main target group, not only in practice but also in further research.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.008
Scholarly communication0.0080.007
Open science0.0010.004
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0160.004

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 head0.132
GPT teacher head0.364
Teacher spread0.233 · 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 designTheoretical or conceptual
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
Published2025
Admission routes1
Has abstractyes

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