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Record W2894745744 · doi:10.7202/1051074ar

Comic Sounds in Contemporary Theatre Performances: Marthaler, Pollesch, Fritsch and Gotscheff

2018· article· en· W2894745744 on OpenAlexvenueno aff
Katharina Rost

Bibliographic record

VenueRecherches sémiotiques · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicTheatre and Performance Studies
Canadian institutionsnot available
Fundersnot available
KeywordsExaggerationAbsurdityComicsIronySarcasmContext (archaeology)AestheticsArtSound (geography)LiteratureHistoryPsychologyAcousticsPsychoanalysis

Abstract

fetched live from OpenAlex

At the Volksbühne am Rosa-Luxemburg-Platz in central Berlin, directors René Pollesch, Christoph Marthaler, Herbert Fritsch, and Dimiter Gotscheff employ comical elements of slapstick, irony, black humour, exaggeration, bluntness, vulgarity, and absurdity. Sound often proves to be significant to the comical effect of the performances as the use of music, sound effects and a specific way of speaking are characteristic for each of their individual directing styles. Even though their styles are comparable in that they all use of a vast array of acoustic elements, they nevertheless differ greatly from each other. The aim of my article is to categorize their use of comical sounds by considering how and to what effect they are employed. The comical aspect of sounds, situations or actions is not necessarily universal or trans-historical, but rather always depends on the specific cultural and historical context that also coins the specific contemporary theatre practice. The article focusses on these connections and on the shifts of attention that are mainly caused by the comical effects of sound and can cause further comical effects.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.848
Threshold uncertainty score0.844

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.169
GPT teacher head0.321
Teacher spread0.153 · 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 designNot applicable
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
Published2018
Admission routes1
Has abstractyes

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