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Record W7133031979

Regionalism in the Operas of John Beckwith and James Reaney

2022· dissertation· W7133031979 on OpenAlexaboutno aff
Katy Aileen Clark

Bibliographic record

VenueTSpace · 2022
Typedissertation
Language
FieldArts and Humanities
TopicMusicology and Musical Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsRegionalism (politics)MusicalOperaContext (archaeology)Italian opera
DOInot available

Abstract

fetched live from OpenAlex

Regionalism is the cultural trend in which the idiosyncrasies of a given region, and their influence on human lives, social structures, and cultural development, are explored and expressed through an artistic medium. This trend emerged in Canadian literature in the 1920’s and 30’s, and experienced a resurgence in prominence in the 1970’s. However, the significance of regionalism in Canadian art music remains virtually unexplored. The purpose of this study is to explore the concept of regionalism in the four Beckwith/Reaney operas: Night Blooming Cereus (1959), The Shivaree (1982), Crazy to Kill (1989), and Taptoo! (2003). The author extrapolates from a literary understanding of regionalism to create a framework of analysis for these four musical works. Beckwith and Reaney employed regionalism as a vehicle for innovation within the operatic form, and exploited the tension between European operatic norms and authentic portrayals of life in rural Ontario with these works. The concluding chapter situates these operas within the context of the twentieth-century Canadian opera marketplace through an examination of composition and performance history, and examines the influence of regionalism on their critical and popular reception.

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)0.000
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.400
Threshold uncertainty score0.795

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.007
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.035
GPT teacher head0.315
Teacher spread0.279 · 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 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

Citations0
Published2022
Admission routes1
Has abstractyes

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