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Record W7029388543

Innovations in Entertainment: Non-Traditional Content in Brass Chamber Ensemble Performances

2017· other· en· W7029388543 on OpenAlexaboutno aff

Bibliographic record

VenueArizona State University Library Digital Repository (Arizona State University) · 2017
Typeother
Languageen
FieldSocial Sciences
TopicImpact of Technology on Adolescents
Canadian institutionsnot available
FundersGrand Valley State University
KeywordsBrassEntertainmentComponent (thermodynamics)Inclusion (mineral)State (computer science)
DOInot available

Abstract

fetched live from OpenAlex

abstract: Performances of three prominent, full-time brass chamber ensembles (the Canadian Brass, Mnozil Brass, and Trompettes de Lyon), are studied for their inclusion of entertainment outside the bounds of traditional music performance. The various additions include acting, choreography, novel changes in instrumentation, props, technical exhibitions, audience interaction, and inherently humorous arrangements. These are identified, categorized, and analyzed for frequency of use. Representative scenes from each ensemble are compared for similarities with the intent of establishing general rules for the usage of each non-traditional element. Differences in overall show structure, compared to that of traditional chamber ensembles, are also discussed. \n\nIn a separate component of this project, the author wrote an original show based on the above research, and performed it with the Grand Valley State University Faculty Brass Quintet. The process of creation and observations of rehearsal and performance settings are included in this document to guide the efforts of other prospective show-writers.

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: Other · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.019
GPT teacher head0.206
Teacher spread0.187 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

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