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Record W804913094

Ontario—By the Numbers: A Statistical Examination of Enrolment in Ontario Secondary School Music Classes

2007· article· en· W804913094 on OpenAlexaboutno aff
Nora Vince

Bibliographic record

VenueScholarship@Western (Western University) · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicEducation Systems and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsStatistical analysisMathematics educationGeographyStatisticsMathematics
DOInot available

Abstract

fetched live from OpenAlex

This chapter reports on the results of a statistical analysis of secondary school Music enrolment in Ontario from 1993Ontario from -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 theGrade 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 Vince, N. (2007).Ontario-by the numbers: A statistical examination of enrolment in Ontario secondary school music classes.In K. Veblen & C. Beynon (Eds.with S. Horsley, U. DeAlwiss, & A

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.741
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.109
GPT teacher head0.354
Teacher spread0.245 · 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 designObservational
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

Citations2
Published2007
Admission routes1
Has abstractyes

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