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Record W2887139587 · doi:10.7202/1048919ar

La chanson française de tradition orale en Ontario : données, tendances, état du répertoire

2018· article· fr· W2887139587 on OpenAlexaffvenueabout
Marcel Bénéteau

Bibliographic record

VenueCahiers Charlevoix Études franco-ontariennes · 2018
Typearticle
Languagefr
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsUniversity of Sudbury
Fundersnot available
KeywordsHumanitiesArtPolitical science

Abstract

fetched live from OpenAlex

L’étude de Marcel Bénéteau fait le bilan de la chanson traditionnelle française en Ontario et trace son évolution dans le temps et l’espace. L’auteur décrit le travail qu’il a entrepris pour déterminer en premier lieu en quoi consiste le répertoire de l’Ontario français ; à cette fin, il précise quelles sont ses balises historiques et géographiques (où et quand le répertoire s’est-il implanté sur le territoire ?) et ce qu’il comprend au juste (combien de chansons ? quelles chansons ? quelles catégories de chansons ?). Pour ce faire, il a dû s’astreindre à dépouiller les divers fonds d’archives disponibles afin de repérer, identifier et cataloguer plus de 12 000 versions de chansons recueillies en Ontario depuis la fin du xixe siècle, un travail de longue haleine qui a occupé l’auteur au cours des dix dernières années. Le résultat – premiers jalons d’un catalogue de la chanson traditionnelle française en Ontario – permet de décrire avec précision la richesse et la diversité du répertoire tout en tenant compte de ses particularités régionales et de ses apports au fonds commun que partagent les francophones des deux côtés de l’Atlantique.

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)0.008
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.041
Threshold uncertainty score0.299

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.010
Science and technology studies0.0090.005
Scholarly communication0.0040.003
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0130.001

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 head0.012
GPT teacher head0.207
Teacher spread0.195 · 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 routes3
Has abstractyes

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