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Record W2145889810 · doi:10.14288/1.0067362

Narrative and representation in Robert Schumann's Waldszenen, Op. 82

2009· article· en· W2145889810 on OpenAlexaff
Wing Yin Cherry Li

Bibliographic record

VenuecIRcle (University of British Columbia) · 2009
Typearticle
Languageen
FieldArts and Humanities
TopicMusicology and Musical Analysis
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsNarrativeRepresentation (politics)LinguisticsHistoryCommunicationArtPsychologyPhilosophyPolitical science

Abstract

fetched live from OpenAlex

Robert Schumann's music is replete with literary references and extramusical indications. His devotion to literature and his adaptation of the narrative strategies of the early Romantics in his compositions have prompted many investigations of literary influences on Schumann's music. Many of his early piano cycles are inspired by the literature of the Romantics, and in particular by the novels of Jean Paul Richter. However, it has sometimes been suggested that Schumann discarded the narrative strategies of Jean Paul in his late compositions, some of which were written for musical education and music-making in the home. My goal, in this dissertation, is to demonstrate that Jean Paul's narrative devices remained relevant in Schumann's late works. This study examines the aspects of narrative and representation that permeate the Waldszenen cycle. The first aspect is large-cycle coherence, an effect that is achieved through innovative associational means -- including motivic and tonal cross-references-- and through more traditional hierarchical means, such as tonal departure and return and the use of programmatic titles that suggest a complete forest journey. The second aspect is the manipulation of formal conventions, which is accomplished through problematic closure, problematic recapitulation, and ambiguous formal function. The third aspect is the use of intertextual allusions to Schumann's earlier works. The last aspect of representation in Waldszenen is the use of three musical topics - fantasy, pastoral, and hunt - in association with their corresponding Romantic literary genres - Kunstmärchen, idyll, and hunting tale and song.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.965
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.186
Teacher spread0.173 · 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 teacher head, not a consensus.

Study designObservational
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

Citations1
Published2009
Admission routes1
Has abstractyes

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