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Record W2167605541 · doi:10.1177/025576140203900103

Fantasies and Other Romanticized Concepts of Music Teaching: A Cross-Cultural Study of Chinese and North American Music Education Students’ Images of Music Teaching

2002· article· en· W2167605541 on OpenAlexaff
Manny Brand, LORI ANNE DOLLOFF

Bibliographic record

VenueInternational Journal of Music Education · 2002
Typearticle
Languageen
FieldArts and Humanities
TopicDiverse Music Education Insights
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMusic educationContext (archaeology)Cross-culturalTeaching methodVisual artsPsychologyPedagogyMathematics educationSociologyArtHistoryAnthropology

Abstract

fetched live from OpenAlex

Within an international context, this article reports on the use of drawings by Chinese and North American music education majors as a means of examining these students’ images, expectations, and emerging concepts of music teaching. By studying and discussing these drawings within the methods class, it is hoped that these music education majors could project their present orientation toward music teaching. Several common themes were seen in both the Chinese and North American drawings. Individual drawings are analyzed and included as evidence of archetypal images and signifiers. It is proposed that these students’ drawings might serve as a means of uncovering, analyzing, and challenging music education students as they begin the career-long task of reconciling romanticized notions with more realistic experiences in teaching music.

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)0.003
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0050.006
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.050
GPT teacher head0.353
Teacher spread0.303 · 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

Citations18
Published2002
Admission routes1
Has abstractyes

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