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Record W4286523198 · doi:10.30535/mto.28.2.4

Cadential Melodies

2022· article· en· W4286523198 on OpenAlexaff
Kyle Hutchinson, Matthew Poon

Bibliographic record

VenueMusic Theory Online · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicMusicology and Musical Analysis
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMelodyPhraseKey (lock)ParallelsFocus (optics)MathematicsHarmonicLinguisticsPure mathematicsComputer sciencePhilosophyLiteratureArtAcousticsPhysicsMusical

Abstract

fetched live from OpenAlex

This article proposes that engaging with structural melodic content can expand how we conceive of cadential function and add nuance to the more harmonically driven approaches of Caplinian form-functional theory. Drawing on discussions by Schenker, Marx, and Schoenberg, we posit parallels between structural melodic configurations and the temporal formal functions of Caplinian theory. Through several analytic examples we suggest that certain melodic directions have default association with Caplin’s temporal functions: ascending lines are typically associated with initiating functions, while the static prolongation of structural tones typically serves as either initiating or medial functions. Conversely, descending melodic lines, especially terminating on ".fn_scaledegree(1)." (authentic cadences) or ".fn_scaledegree(2)." (half cadences) are endemic of concluding functions. We do not suggest that melodic considerations replace harmonic ones, but rather conclude that the two domains are symbiotic in the sense that melodic consideration can reinforce or undermine harmonic ones, and vice versa. Ultimately, we use this rebalancing of analytic focus as a means of reengaging with various problematic phrase types and suggest further efficacy for this approach with respect to nineteenth-century formal expansions.

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: none
Teacher disagreement score0.016
Threshold uncertainty score0.055

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 studies0.0010.007
Scholarly communication0.0040.005
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0160.002

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 head0.039
GPT teacher head0.226
Teacher spread0.186 · 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
Published2022
Admission routes1
Has abstractyes

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