What we Have Works...or does it? Cultural Diversity in Canadian Music Curricula and Resistance to Change
Bibliographic record
Abstract
During a series of curriculum prototype sessions in Calgary, AB, between May and September of 2014, music teachers K-12 were given virtually carte blanche and encouraged to visualize a new curriculum with no boundaries. Two outcomes of the initial music educator’s meeting were a) teachers see specific areas for improvement in the existing curriculum but are generally satisfied with it, and b) the issue of cultural diversity is vital to some, moderately important to some, and to others, recognized but not important enough to change the current Western focus. This article examines the issue of declining enrolment in music courses between middle and high school and with it a case for inclusion of non-Western musics in the curriculum, reasons for continued Western music dominance, the emphasis on Western notation literacy, teacher beliefs, teacher training, and sustainability of diversity in music programs. It is meant to stimulate thought toward building more culturally diverse music programs in Canadian schools, from pre-service training to implementation.
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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 | 0.018 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.074 | 0.054 |
| Scholarly communication | 0.021 | 0.007 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
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".