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Record W4394857455 · doi:10.33871/vortex.2024.12.8348

Conducting pedagogues: a dialogue with Maestro Jean-François Rivest, act II

2024· article· en· W4394857455 on OpenAlexaboutno aff
Erickinson Lima, André Luiz Muniz Oliveira

Bibliographic record

VenueRevista Vórtex · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicLiterature, Musicology, and Cultural Analysis
Canadian institutionsnot available
FundersFundação para a Ciência e a Tecnologia
KeywordsSymphonyMusicalPerspective (graphical)NarrativeSociologyViolinVisual artsArtArt historyLiterature

Abstract

fetched live from OpenAlex

Understanding the didactic-pedagogical structures concerning the teaching-learning process of the conducting, are not summarized to the technical-gestural aspects, it permeates administrative, logistics and psych-pedagogical elements. To visualize this perspective in the light of labor reality, the narratives of academic, artistic and professional life are resorted through a cycle of interviews with national (Brazil) and international conductors. The professional to be interviewed is the Canadian conductor and professor Jean-François Rivest. Considered one of the most prominent violinist of his generation, Rivest studied at Julliard School with Ivan Galamian, and his musical path soon led him to a fruitful international career. As a Professor at the Université de Montréal, founded the institution's Symphony Orchestra. Giving voice to conductors as Rivest allows us to visualize new practical, conceptual and pedagogical perspectives, and directs us to look at the real needs of the field of conducting: to think and act beyond the gestural technique.

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)0.011
metaresearch head score (Gemma)0.032
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: Other · Consensus signal: none
Teacher disagreement score0.074
Threshold uncertainty score0.148

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.032
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0190.017
Scholarly communication0.0110.005
Open science0.0020.003
Research integrity0.0060.013
Insufficient payload (model declined to judge)0.0020.001

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 head0.058
GPT teacher head0.323
Teacher spread0.264 · 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
GenreOther

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
Published2024
Admission routes1
Has abstractyes

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