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Record W2735908785

What Really Matters in Music Class?

2010· article· en· W2735908785 on OpenAlexafffund
Lee Bartel, Linda M. Cameron

Bibliographic record

VenueTSpace (University of Toronto) · 2010
Typearticle
Languageen
FieldArts and Humanities
TopicHermeneutics and Narrative Identity
Canadian institutionsUniversity of Toronto
FundersUniversity of Toronto
KeywordsClass (philosophy)Computer scienceArtificial intelligence
DOInot available

Abstract

fetched live from OpenAlex

We were at a dinner party recently and the person across the table discovered our connection to education and music.The next bit of conversation was predictable (as is the opening of most music education articles these days)!"Have you seen Mr. Holland's Opus?" "Yes," we answered, "on opening night!" "So, what did you think of it?"What we think is that it raises some important questions such as what is important in music class, who controls the content of instruction, what makes music instruction worthwhile, and how can we contribute to the survival of music in the schools.We will try to explore here what we think is at least one of the central questions: what is the role, importance, and quality of the relationship that engages the learner with music.Consider the following reflections on music learning experiences.Are there aspects of these experiences that resonate with yours?Do you contribute to these sorts of experiences with your students?...the people that turned me off to music because of the subtle personal abuse and the relentless focus on performance and not play!If only I could have had the opportunity to explore what music could do for me instead of always having to play someone else's music someone else's way --I had no ownership.I was immersed in music but not with the variety that would have captured me.I did not have good demonstrations of music-making that inspired or encouraged --not even enchanted me --and never that instructed me --just words and criticisms that were punctuated by impatience.No one worked within my zone of proximal development.No one worked with any understanding of who I am.Engagement was not there, nor "use" in Cambourne's sense as practice ("learners need time and opportunity to use, employ, and practise their developing control in functional, realistic, nonartificial ways" Cambourne 1988, p.33) Oh, but there was practice!.... terrible experiences of practice --at home on the piano or my singing --but school!! Terrible instruments that tasted like rusty spit and smelled...and would not stop squeaking and squawking because they were in such bad shape and no one was there beside me to care appropriately.The music that emerged both individually and collectively was nasty and provoked my sensitively tuned ears.I knew it was terrible and felt hopeless to do anything about it.And, I couldn't have the instrument I wanted --none of them.I had to play the E flat alto sax...I wanted the drums or the flute or, best of all, the vibes or a harp!...but a sax....If I had been able to be in a situation that met the conditions that Cambourne and Max van Manen suggest, I might be a satisfied `functional' musician or at least an informed audience participant.It is one of the most disappointing aspects of my education.One of my ways of knowing was squelched by miseducative experiences.

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)0.006
metaresearch head score (Gemma)0.030
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.028
Threshold uncertainty score0.092

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.030
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0100.010
Scholarly communication0.0140.008
Open science0.0020.004
Research integrity0.0050.007
Insufficient payload (model declined to judge)0.0280.004

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 head0.021
GPT teacher head0.219
Teacher spread0.199 · 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

Citations0
Published2010
Admission routes2
Has abstractyes

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