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Record W354693358 · doi:10.5206/notabene.v6i1.6586

Performing Ritual: Physical and Musical Gesture in Benjamin Britten’s Curlew River

2013· article· en· W354693358 on OpenAlexaffvenue
Helen Tucker

Bibliographic record

VenueNota bene · 2013
Typearticle
Languageen
FieldArts and Humanities
TopicTheater, Performance, and Music History
Canadian institutionsMount Allison University
Fundersnot available
KeywordsGestureMusicalMusical expressionArtPunctuationAestheticsVisual artsCommunicationHistoryLiteratureSociologyLinguisticsPhilosophy

Abstract

fetched live from OpenAlex

Benjamin Britten’s Curlew River (1964) defies traditional genre labels, exhibiting characteristics of opera, Japanese Noh drama, and religious ritual. Set in medieval England and given a Christian theme, Curlew River is based on the Noh play Sumidagawa and uses a unique language of physical gesture inspired by Noh traditions. The integration of these physical gestures with the music is one of the ways in which Curlew River projects an atmosphere of ritual. In this paper I examine two passages from Curlew River, each of which demonstrates a close connection between the development of individual musical gestures and the progression of physical actions performed at the same time. In the arietta “Near the Black Mountains,” sung by the character of the Madwoman, the subtle development of a single musical figure is linked to the gradual transformation of the actor’s posture. A similar relationship is present in the Ferryman’s introductory scene, in which physical movements act as punctuation for a sequence of musical statements. In both instances, musical and physical gesture are integrated into a unified form of expression, the intensity and focus of which lend Curlew River its ritual quality.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.056
Threshold uncertainty score0.112

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.013
Scholarly communication0.0040.002
Open science0.0010.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.012
GPT teacher head0.191
Teacher spread0.178 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2013
Admission routes2
Has abstractyes

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