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Record W4294199684 · doi:10.4000/volume.10005

Entendre le récit dans les sons

2022· article· fr· W4294199684 on OpenAlexaff
Marion Brachet

Bibliographic record

VenueVolume ! · 2022
Typearticle
Languagefr
FieldArts and Humanities
TopicNarrative Theory and Analysis
Canadian institutionsUniversité LavalMusée de la Civilisation
Fundersnot available
KeywordsArtPhilosophy

Abstract

fetched live from OpenAlex

Les apports de la narratologie cognitiviste à l’étude des musiques populaires ont récemment permis d’adopter des approches analytiques permettant de rendre compte des processus de narrativisation à l’œuvre lors de l’écoute, c’est-à-dire des modes de réception caractérisés par l’interprétation des éléments sonores et verbaux au travers d’un prisme narratif. Malgré la généralisation de ce cadre théorique, peu d’études de réception ont encore été réalisées pour renseigner ces processus de narrativisation. Cet article se propose de contribuer à leur compréhension grâce aux résultats d’un questionnaire en ligne portant sur la réception narrative des chansons rock et folk, en se concentrant ici sur les strates musicales non vocales des chansons. Les témoignages d’écoute mettent en évidence trois éléments majeurs jouant le rôle d’incitants narratifs pour la population enquêtée : la complexité de la forme, la présence de soli instrumentaux, ainsi qu’une atmosphère jugée immersive. En s’appuyant sur les descriptions de ces caractéristiques par les enquêtés, cet article tente d’affiner l’identification de ces incitants narratifs non vocaux dans un contexte musical défini génériquement.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.023
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.004
Scholarly communication0.0050.003
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0230.005

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 head0.206
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 designTheoretical or conceptual
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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