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Becoming a Music Learner: Toward a Theory of Transformative Music Engagement

2012· book· en· W2625811068 on OpenAlexaff
Susan O’Neill

Bibliographic record

VenueOxford University Press eBooks · 2012
Typebook
Languageen
FieldArts and Humanities
TopicDiverse Music Education Insights
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsTransformative learningMusicalPsychologyMusic educationMusic and emotionCitizen journalismPedagogySociologyAestheticsMusic historyVisual artsArtPolitical science

Abstract

fetched live from OpenAlex

This article argues for shifts in our thinking about music learners to emphasize the dynamic potential of each individual and the social affiliations that promote music learning, as well as the need for music learning to be conceptualized as positive and purposeful transformative music engagement. It suggests that we might begin with a conscious effort to scrutinize the origins of our expectations of music learners, how music learners make sense of their own experiences, and our understanding of those experiences. The article also discusses the need to expand our awareness of the multifaceted ways that music learning is taking place in today's digital age, and to examine more deeply what it means to prepare and engage music learners in multimodal and participatory forms of music-making. The transition to a new paradigm for music learning will be complete when transformations have occurred in how we view music learners in relation to their own musical worlds; the methods we use to study them so that they take into account particular contexts and cultural ecologies; and the goals we pursue to empower learners as active agents in their own musical development.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.935
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.141
GPT teacher head0.225
Teacher spread0.084 · 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
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

Citations32
Published2012
Admission routes1
Has abstractyes

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