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Record W7023790929

Of Priests, Fiends, Fops, and Fools: John Bowman's Song Performances on the London Stage, 1677-1701

2006· article· en· W7023790929 on OpenAlexaboutno aff

Bibliographic record

VenueDigiNole (Florida State University) · 2006
Typearticle
Languageen
FieldArts and Humanities
TopicMusicology and Musical Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsPerformance practiceSubject (documents)Quarter (Canadian coin)Perspective (graphical)Performance artPeriod (music)Commission
DOInot available

Abstract

fetched live from OpenAlex

Referred to as Henry Purcell's "favorite baritone," the actor-singer John Bowman (ca. 1655-1739) became the leading baritone on the London stage during the last quarter of the seventeenth century. Centering on the career and song performances of Bowman, this dissertation provides a fresh perspective from which to view Restoration music theater, a reorientation that shifts the spotlight away from the works themselves—the plays and their music—and away from composers and playwrights, to one that focuses on performers and their concerns. The purpose of this work is to provide an account of the performance practice of Restoration theater song using Bowman as a case study. Bowman is an excellent subject for a case study for several reasons. He sang in Purcell's first stage commission and went on to sing many more songs by Purcell, as well as music by other significant composers of the era, including John Blow and John Eccles. As an actor, Bowman performed roles written by virtually every playwright of the late seventeenth century in England and worked with such actors as Thomas Betterton and Anne Bracegirdle. A desired outcome of this project is that singers wishing to cultivate their adeptness in historically informed performance of Restoration song will find this a helpful resource. To this end, Chapter II focuses wholly on performance practice in Restoration theater, covering both vocal production and acting, and concludes with a very detailed application of these to a song Bowman performed. This chapter also includes a guide outlining a practical approach for historically informed performance of Restoration theater song. As this guide shows, the initial step in the process, after having located the music, is to determine how each song fit into the larger dramatic context. Subsequent chapters are thus devoted principally to uncovering and reproducing all extant, unpublished songs Bowman performed, and to describing Bowman's characters and the contexts in which their song performances occurred.

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)0.003
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 score0.091
Threshold uncertainty score0.181

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0100.006
Scholarly communication0.0040.001
Open science0.0010.002
Research integrity0.0010.001
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 head0.016
GPT teacher head0.169
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 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
Published2006
Admission routes1
Has abstractyes

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