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The Role of Proportion in the First-Movement Expositions of Mozart's String Quintets

2014· article· en· W2228314565 on OpenAlexaff
Eduardo Solá Chagas Lima

Bibliographic record

VenueRevista Vórtex · 2014
Typearticle
Languageen
FieldArts and Humanities
TopicMusicology and Musical Analysis
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsRepertoireMOZARTScope (computer science)Movement (music)String (physics)Balance (ability)Tonic (physiology)Performing artsComputer scienceEpistemologyTheoretical physicsPure mathematicsSociologyPsychologyLiteratureMathematicsPhysicsAestheticsPhilosophyArtNeuroscience

Abstract

fetched live from OpenAlex

This study aims at discussing the role of balance and proportion in the expositional scope within a Classical Sonata Form movement. While using the approach, model and labels proposed by James Hepokoski and Warren Darcy in Elements of Sonata Theory (2006), it also challenges the application of some of their analytical tools. Throughout this study, special attention is given to different treatments of expositional spaces, including a few significantly difficult cases for the repertoire. The intention here is to observe the interaction between these spaces in light of the dual function in the expositional trajectory: (1) to fulfill the harmonic requirement in destabilizing the tonic key; and (2) to attain a rhetorically reasonable organization of thematic material (HEPOKOSKI; DARCY, 2006, p.18). For this purpose, a careful examination of the medial caesura and the essential expositional closure is also taken into account throughout the present analysis. Finally, however limited the repertoire range used in this specific research, the present study fosters the idea of proportion and balance as feasible arguments (among many others) not only in determining the dimensions of expositional spaces, but also in the holistic process of analyzing entire Classical sonata forms as hermetic units.

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)0.002
metaresearch head score (Gemma)0.006
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 score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0030.008
Scholarly communication0.0050.005
Open science0.0010.005
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 head0.012
GPT teacher head0.209
Teacher spread0.198 · 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".

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Citations0
Published2014
Admission routes1
Has abstractyes

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