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Record W2784603931 · doi:10.7202/1042839ar

Concours international de composition du Festival Présences à Shanghai (2008-2010) : le moment où le Québec a rayonné en Chine par sa création musicale

2018· article· fr· W2784603931 on OpenAlexaffvenueabout
Jessica Pilon Pinette, Danick Trottier

Bibliographic record

VenueCircuit Musiques contemporaines · 2018
Typearticle
Languagefr
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsMinistry of Education, Recreation and Sports
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

C’est à la suite d’une immersion en Chine en 2008 ainsi qu’après avoir franchi les nombreuses étapes préliminaires de la grande finale internationale, que Denis Gougeon est déclaré en mai 2010 grand gagnant du Concours international de composition du Festival Présences à Shanghai. Présélectionnés par la smcq, huit compositrices et compositeurs québécois ont été invités à se familiariser avec la culture et la tradition musicale shanghaiennes en vue de participer à ce concours. La finale québécoise a ainsi pris place en 2009, moment où tous devaient présenter une composition intégrant un instrument et une mélodie issus de la tradition chinoise. Les oeuvres créées à cette occasion par Simon Bertrand, José Evangelista, Denis Gougeon, Analía Llugdar, Pierre Michaud, Farangis Nurulla-Khoja, Sean Pepperall et Serge Provost, ont offert une vitrine de choix pour la diffusion de la création musicale du Québec à l’international. L’enquête donne un aperçu des différentes étapes ayant marqué ce concours par l’intermédiaire des souvenirs et des propos de Simon Bertrand, Walter Boudreau, José Evangelista, Denis Gougeon, Analía Llugdar et Pierre Michaud, passant autant par l’organisation de la participation québécoise que par la manière dont chacun a vécu cette expérience et a conçu son oeuvre.

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)0.001
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: Empirical
Teacher disagreement score0.271
Threshold uncertainty score0.545

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.002
Scholarly communication0.0030.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0240.001

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 head0.018
GPT teacher head0.243
Teacher spread0.225 · 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

Citations0
Published2018
Admission routes3
Has abstractyes

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