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Record W2026695340 · doi:10.3138/md.54.4.409

Auden and Britten's <i>Paul Bunyan</i> and the Frontiers of Opera

2011· article· en· W2026695340 on OpenAlexvenueno aff
Matthew Paul Carlson

Bibliographic record

VenueModern Drama · 2011
Typearticle
Languageen
FieldArts and Humanities
TopicPoetry Analysis and Criticism
Canadian institutionsnot available
Fundersnot available
KeywordsOperaDramaLiteraturePoetryMythologyArtMusicalPerformance artHistoryArt history

Abstract

fetched live from OpenAlex

Although W.H. Auden abandoned playwriting when he left England in 1939, he did not, as some have claimed, stop seeking a theatrically viable role for his verse. Ultimately, he would find a satisfying outlet for his unique poetic talents as well as lasting solutions to his dramaturgical problems by writing opera librettos. But even before he began to espouse opera proper, his dramatic writings, which increasingly relied on the musical contributions of Benjamin Britten, inclined toward the operatic. Shortly after arriving in America, he began writing his first libretto for Britten's operetta Paul Bunyan, a work that marks both the culmination of Auden's earlier dramatic efforts and a pivotal transition in his career from verse drama to opera. The Paul Bunyan libretto, one of the few dramatic texts Auden wrote without a collaborator, characteristically combines popular forms with quasi-religious ritual in its attempt to fashion a distinctively American myth. The final scene, in particular, achieves Auden's goal of representing a collective ritual action on the stage; however, the operetta's eclectic mix of musical theatrical genres led to a poorly received premiere in 1941. The initial failure of Paul Bunyan was partly responsible for the dissolution of the Auden-Britten collaboration, but librettist and composer would soon separately find, in the paradoxically liberating constraints of the operatic tradition, an ideal medium for their respective dramatic projects.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.274
Threshold uncertainty score0.234

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 studies0.0000.001
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 head0.020
GPT teacher head0.193
Teacher spread0.172 · 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 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

Citations1
Published2011
Admission routes1
Has abstractyes

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