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Record W4410087733 · doi:10.33137/rr.v47i4.45374

By the Shallow Rivers of Babylon: Musical Mashups and the Sound of Lost Music in The Merry Wives of Windsor

2025· article· en· W4410087733 on OpenAlexaffvenue
J. G. Wylde

Bibliographic record

VenueRenaissance and Reformation · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicTheater, Performance, and Music History
Canadian institutionsSt. Francis Xavier University
FundersUniversity of CambridgeBritish Broadcasting CorporationUniversity of OxfordJohns Hopkins University
KeywordsWindsorMusicalSound (geography)ArtAcousticsVisual artsGeologyPhysics

Abstract

fetched live from OpenAlex

InThe Merry Wives of Windsor, there is a humorous sound-based musical moment in act 3, scene 1 that no longer resonates with contemporary audiences; the sounds evoked in the text and intended for performance on the stage have become obsolete. This article begins by investigating the original sounds and meanings of the sonic moment in the play, exploring what they would have sounded like and what they meant to an Elizabethan audience. It then turns to three twentieth- and twenty-first-century productions that have contended with this outdated sonic moment in funny, memorable, and very different ways, asking how new productions can harness new sounds to capture old meanings.

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)0.002
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.007
Scholarly communication0.0040.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.014
GPT teacher head0.205
Teacher spread0.191 · 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
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 routes2
Has abstractyes

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