Ontario—By the Numbers: A Statistical Examination of Enrolment in Ontario Secondary School Music Classes
Bibliographic record
Abstract
This chapter reports on the results of a statistical analysis of secondary school Music enrolment in Ontario from 1993-2002.Data from the electronic database at the Ontario Ministry of Education were examined to determine if Music enrolment was changing, both in absolute terms, and in relationship to the overall secondary school enrolment.Results varied, with enrolment increasing at the Grade 9 level, and decreasing in the remaining grades.Change was most noticeable following the introduction of the revised secondary curriculum in 1999.Data were also examined from the Ontario Universities' Application Center and results indicate that the vast majority of students registered in a final senior secondary school Music course use the credit for university application, but not for access to university Music education.The historical account presented by Willingham and Cutler outlines numerous past problems in education in Ontario and alludes to difficulties in Music education associated with academic and financial decisions of the Mike Harris Conservative government elected in 1995.They also raise interesting questions regarding the future of
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.018 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".