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Record W7155059500 · doi:10.59236/ijea15n15

Where do teachers and learners stand in music education research?

2014· article· W7155059500 on OpenAlexaff
Peter Gouzouasis, Danny Bakan, Jee Yeon Ryu, Helen Ballam, David Murphy, Diana Ihnatovych, Zoltan Virag, Matthew Yanco

Bibliographic record

VenueInternational journal of education and the arts · 2014
Typearticle
Language
FieldArts and Humanities
TopicDiverse Music Education Insights
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMusic educationMusicologyContemporary classical musicAutoethnographyConversationPower (physics)Music historyMusic GeographyPopular musicQualitative research

Abstract

fetched live from OpenAlex

We offer a multi-voiced performance autoethnography where contemporary music education practices are informed and imbued with the voices of teachers and learners. By dialogically and musically engaging with the very people who live, make music, and engage with learners in music classrooms, we promote contemporary qualitative forms of research and the (re)conception of a sociology of music education as a political and an ethical construction that needs to be grounded in serving communities of music practitioners. Through a pedagogical story, told from the perspectives of music teachers using their own voices, we begin an open conversation about the nature of power structures and struggles in music education research. We invite new possibilities in developing understandings of the complex socio-cultural dynamic of music making, music learning, music teaching, and music researching in all facets of contemporary society. By embracing a broader set of traditions--Arts-Based Educational Research and Creative Analytical Practices--that enable us to go beyond socio-cultural frameworks and orthodox beliefs that currently exist in the music education profession, we seek to (re)form a culturally contextualized, ethos-rooted, sociology of music education.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.728
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.065
GPT teacher head0.344
Teacher spread0.279 · 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.

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
Published2014
Admission routes1
Has abstractyes

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