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Record W2089950025 · doi:10.1093/jrma/126.2.193

Music and Narrative Revisited: Degrees of Narrativity in Beethoven and Mahler

2001· article· en· W2089950025 on OpenAlexaff
Vera Micznik

Bibliographic record

VenueJournal of the Royal Musical Association · 2001
Typearticle
Languageen
FieldPsychology
TopicLanguage, Metaphor, and Cognition
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsNarrativityNarrativeSymphonyLiteratureLinguisticsSyntaxMusicalMeaning (existential)ArtSonata formPhilosophyEpistemology

Abstract

fetched live from OpenAlex

This study presents an attempt to pin down the potential narrative qualities of instrumental, wordless music. Comparing as case-studies two pieces in sonata form–the first movements of Beethoven's ‘Pastoral’ Symphony (as representative of Classical narrative possibilities) and of Mahler's Ninth Symphony (as representative of its composer's idiosyncratic treatment of those in the late nineteenth century) –I propose a ‘narrative’ analysis of their musical features, applying the notions of ‘story’, ‘discourse’ and other concepts from the literary theory of, for example, Genette, Prince and Barthes. An analysis at three semiotic levels (morphological, syntactic and semantic), corresponding to denotative/connotative levels of meaning, shows that Mahler's materials qualify better as narrative ‘events’ on account of their greater number, their individuality and their rich semantic connotations. Through analysis of the ‘discursive techniques’ of the two pieces I show that a weaker degree of narrativity corresponds to music in which the developmental procedures are mostly based on tonal musical syntax (as in the Classical style), whereas a higher degree of narrativity corresponds to music in which, in addition to semantic transformations of the materials, discourse itself relies more on gestural semantic connotations (as in Mahler).

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)0.005
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 score0.008
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0030.013
Scholarly communication0.0080.005
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.020
GPT teacher head0.279
Teacher spread0.259 · 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

Citations104
Published2001
Admission routes1
Has abstractyes

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