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Record W4405943877 · doi:10.71156/2994-7073.1144

Some Challenges in Teaching American-Based Harmony in French

2005· article· en· W4405943877 on OpenAlexaboutno aff
Roxane Prevost

Bibliographic record

VenueJournal of Music Theory Pedagogy · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicFrench Language Learning Methods
Canadian institutionsnot available
Fundersnot available
KeywordsHarmony (color)Mathematics educationSociologyPsychologyArtVisual arts

Abstract

fetched live from OpenAlex

Music theory pedagogy at the undergraduate level imposes many challenges, such as the sequence of material, example selection, and drawing connections to performance, but the pedagogue of music theory in French at a North-American bilingual post-secondary institution faces more severe challenges. Since the University of Ottawa offers courses in both English and French, an attempt to coordinate the material between the different sections is ideal. Two main areas are problematic, however, for the French music theory class: the accessibility of recent resources in the pedagogy of music theory written or translated into French, and the discrepancy in the interpretation of certain concepts between English- and French-language texts. In recent years, French scholars have begun to translate and compile materials for a North American-rooted music theory, but few useful resources on music theory pedagogy exist. In this essay, I fi rst survey texts available for music theory pedagogy in French. I then explore some of the different interpretations for diminished, half-diminished, and augmented-sixth chords in English- and French-language sources. I conclude with a call for more resources for the French pedagogue and student of harmony.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.856
Threshold uncertainty score0.491

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.070
GPT teacher head0.392
Teacher spread0.322 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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
Published2005
Admission routes1
Has abstractyes

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