Questioning Traditional Teaching and Learning in Canadian Music Education
Bibliographic record
Abstract
I have no idea how the world should be educated.Each culture has its own targets for citizenship and develops a curriculum to meet those objectives.Those who disagree with the objectives will have a rough time in school.I spent years in school trying to get out.It seemed to me that so much of education was devoted to answering questions that no one had asked while the real questions slid by unanswered.Plato taught that there was an answer to every question.Socrates taught that there was a question to every answer, but that was something my teachers didn't seem to want to deal with.For that reason I never completed my education, but instead set out to travel the world and educate myself.Unfortunately, as Ivan Illich pointed out, the effect of universal education is to make the autodidact unemployable.It was only after many years of travelling -first as a sailor, then as a journalist, a broadcaster, and a composer -that I began to question seriously why my life at school had been so futile.The failure of the music program concerned me in particular because I had musical talent -I played the piano and sang in a choir -and had eventually adopted music as my vocation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.023 | 0.044 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".