Applying the Metaphor of Motion to Phrase Analysis and Performance of Choral Music
Bibliographic record
Abstract
This paper addresses the role of the metaphor of motion as a conceptual aid to the analysis and performance of choral music.I discuss a few ways in which it can benefit the choral director, both in score preparation and in communicating sophisticated musical concepts with an amateur choir.In particular, I focus on the analysis of form, specifically the phrase structure of tonal music.To this end, I apply two types of analytical techniques from the tradition of energetics-tonal analysis as developed by Schenker (1979) and melodic analysis of Meyer (1956) and Narmour (1992)-and demonstrate their general application to score study.For the sake of clarity, this paper focuses on Mozart's choral-music gem, Ave verum corpus, although these ideas can be beneficially applied to more substantial works as well as those less overtly tonal.Common to all energetic theories of music, such as Schenkerian theory, are at least three features.These include an ahistorical approach to the music that de-emphasizes style in favour of perceived musical universals and a conceptual-metaphoric understanding that the tones have a will of their own.Another crucial feature is the
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.003 | 0.019 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".