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Record W1954546837 · doi:10.30535/mto.20.4.7

Treading Robert Schumann’s New Path

2014· article· en· W1954546837 on OpenAlexaff
Harald Krebs

Bibliographic record

VenueMusic Theory Online · 2014
Typearticle
Languageen
FieldArts and Humanities
TopicMusicology and Musical Analysis
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsRhythmPoetryExpression (computer science)LiteratureVariety (cybernetics)ArtDuration (music)WishSimplicityCommunicationLinguisticsPsychologyAestheticsPhilosophyComputer scienceEpistemologyArtificial intelligence

Abstract

fetched live from OpenAlex

Robert Schumann’s late songs (1849–52) are in some respects difficult to understand and to perform. Paradoxically, it is their apparent simplicity that poses a challenge for performers; harmonically, texturally, and metrically less adventurous than the songs of 1840, they may on first contact seem rather bland. Those who wish to explore Schumann’s “second practice” of song writing must grapple with the questions: 1) What is interesting and expressive about the late songs? and 2) How can their interesting and expressive elements be communicated to listeners? One striking aspect of the songs is their manner of declaiming the texts; their vocal rhythms depart more drastically from the poetic rhythm than is ever the case in Schumann’s earlier songs. Poetic feet, which would be approximately equivalent in duration in a normal recitation, are set to a wide variety of durations, producing irregular and unpredictable vocal rhythms. Schumann’s new manner of declamation is a significant locus of expression in songs where other potentially expressive features are attenuated. Analysis and recomposition highlight Schumann’s unorthodox but expressive declamation, and help performers to make decisions that enhance the song’s expressive attributes.

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)0.005
metaresearch head score (Gemma)0.010
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 score0.012
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0050.017
Scholarly communication0.0080.008
Open science0.0010.005
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0120.006

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 head0.030
GPT teacher head0.225
Teacher spread0.195 · 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

Citations28
Published2014
Admission routes1
Has abstractyes

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