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Record W1942770883 · doi:10.4000/lhomme.2127

Combiner les sons pour réinventer le monde

2006· article· fr· W1942770883 on OpenAlexaff
Simha Arom, Denis‐Constant Martin

Bibliographic record

VenueL Homme · 2006
Typearticle
Languagefr
FieldArts and Humanities
TopicCultural Identity and Heritage
Canadian institutionsCanadian Nautical Research Society
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

Résumé«Musiques du monde» est une étiquette commerciale inventée au cours des années 1980 pour répertorier et vendre certains types de musique. Son succès incite à se pencher sur les conditions de cette invention et de ce succès ainsi que sur la manière dont sont rassemblées ou fabriquées les musiques qui apparaissent sous cette appellation. L’analyse d’un corpus limité de pièces diffusées comme world music permet d’établir une typologie de ce que recouvre musicalement cette expression; elle démontre que les «musiques du monde» ne correspondent à aucune forme homogène et résultent exclusivement de la combinaison d’éléments préexistants. Cet art de la combinatoire est le moyen par lequel se déploient des imaginaires du monde contemporain: il permet à la fois d’explorer un univers en mutation, de se donner le sentiment de le maîtriser et de s’en échapper. Dans cette perspective, les «musiques du monde» apparaissent comme un instrument d’invention d’un nouveau monde en formation. La compréhension du fonctionnement de ces musiques et de l’imagination, à travers la musique, de ce nouveau monde requiert l’association d’une approche sociologique et d’une approche musicologique.

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)0.002
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 score0.038
Threshold uncertainty score0.127

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.003
Scholarly communication0.0050.005
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0380.007

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 head0.041
GPT teacher head0.224
Teacher spread0.183 · 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

Citations7
Published2006
Admission routes1
Has abstractyes

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