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Record W3168650723 · doi:10.1017/9781782046097

Venanzio Rauzzini in Britain

2015· book· en· W3168650723 on OpenAlexaboutno aff
Paul F. Rice

Bibliographic record

Venuenot available
Typebook
Languageen
FieldArts and Humanities
TopicMusicology and Musical Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsMOZARTPrestigeMusicalArtArt historyPerformance artPoliticsHistoryLiteratureLawPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

Venanzio Rauzzini (1746-1810), the celebrated Italian castrato, is best known for his performance in Mozart's <I>Lucio Silla</I> in 1772, with which Mozart was so pleased that he composed for the singer the famous motet <I>Exsultate Jubilate</I>. In 1774, Rauzzini moved to London where he performed three seasons of serious operas at the King's Theatre. From 1777 until his death in 1810, he was the director of the concert series in Bath, a series that matched the prestige of any that were given in London. In addition, he composed prolifically, writing music for eleven operas.<BR><BR> This book is a study of Rauzzini's remarkable yet often overlooked career in Britain. Paul Rice chronicles Rauzzini's performances at the King's Theatre and examines his leadership of the Bath subscription concerts from 1780-1810, recovering much of the repertory. Rice shows in detail how Rauzzini responded musically to the social and political conditions of his adopted country, and analyzes the castrato's reception, as well as compositional choices, shedding new light on changing musical tastes in late eighteenth-century Britain.<BR><BR> Paul F. Rice is professor of musicology at the School of Music, Memorial University of Newfoundland.

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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.030
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0030.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0270.009

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 head0.056
GPT teacher head0.225
Teacher spread0.169 · 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

Citations3
Published2015
Admission routes1
Has abstractyes

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Same topicMusicology and Musical AnalysisFrench-language works237,207