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Record W2912061164 · doi:10.3917/nect.008.0126

Les défis des musiques des peuples pour la biodiversité

2018· article· fr· W2912061164 on OpenAlexaff
Frank Tenaille

Bibliographic record

VenueNectart · 2018
Typearticle
Languagefr
FieldSocial Sciences
TopicFrench Urban and Social Studies
Canadian institutionsMusée de la Civilisation
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

L’humanité a davantage modifié les écosystèmes depuis ces cinquante dernières années qu’au cours de toute son histoire. Notre société destructrice serait bien inspirée de tirer parti des riches enseignements des peuples premiers, qui entretiennent avec la nature des rapports responsables et n’ont pas rompu le lien entre nature et culture. Leurs musiques, en particulier, restent à l’écoute des pulsations de la planète. Il est peut-être utile, dans un monde qui produit des individus hors sol, de reconnaître les vertus de ces musiques du monde d’essence patrimoniale, pures ou métissées, rurales ou urbaines, rituelles ou festives. La préservation de la diversité des cultures humaines est en effet indissociable de la préservation de la biodiversité.

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)0.004
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.039
Threshold uncertainty score0.078

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0060.017
Scholarly communication0.0060.003
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.079
GPT teacher head0.286
Teacher spread0.206 · 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 designQualitative
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
Published2018
Admission routes1
Has abstractyes

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