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Record W2604274849 · doi:10.1177/0021989417696123

Music in Michael Ondaatje’s <i>Divisadero</i>

2017· article· en· W2604274849 on OpenAlexaff
Robert Lecker

Bibliographic record

VenueThe Journal of Commonwealth Literature · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicMusic History and Culture
Canadian institutionsMcGill University
Fundersnot available
KeywordsBluesMusicalNarrativeJazzLiteratureMusical formArtImpulse (physics)HistoryAestheticsVisual artsArt history

Abstract

fetched live from OpenAlex

Michael Ondaatje’s Divisadero uses musical references to enhance our understanding of how the story’s characters inhabit time and place. The book’s three parts unfold against a varied musical backdrop that can be experienced as a kind of soundtrack. Although musical allusions appear in Ondaatje’s earlier work, Divisadero is marked by its range of musical references, which run from classical compositions to jazz, opera to rock ’n’ roll, reggae to blues and British new wave. This article examines the way music directs us to see different narrative options in each of the novel’s three parts. One impulse behind the narrative is to connect us to the immediate, to locate the story in mimetic terms that are rooted in the California and Nevada settings that form the backdrop to the first part of the book. The musical references in this part serve to reinforce this sense of presence, as if history could be located and understood in terms of the themes and issues conveyed in particular songs. But another impulse is to work against the immediate, to cast the characters and their experiences as part of an allegorical universe in which actions and choices are symbolic, metaphoric, transhistorical.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.556
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.040
GPT teacher head0.250
Teacher spread0.210 · 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 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
Published2017
Admission routes1
Has abstractyes

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