Bibliographic record
Abstract
Arts education acts as a reinforcing link between politics and economics. The state of development of education is related to the various aspects of the operation of the state and society. The concept and role of the arts were reintroduced and then added to the educational system. In preschool, fundamental education, secondary and higher education, and art education provides guidance and shape the way of thinking and acting of students. Therefore, art education has become an integral part of the education system in many countries. Arts learning is a life experience that provides creative value for the subsequent development of personal and social life, including emotional value, economic transformation value, research development value, etc. This points to the education of arts education and technological development. The article describes the concept and meaning of arts education; the investment in arts education in Canada, including funding, curriculum approaches, teaching teams, extracurricular school resources, legal policies, and other aspects of investment and outcomes. The article is provided to help inform the Canadian art education system, to fill in the discussion of information and assessment of the phenomenon in Canadian arts classrooms, and to provide statistics and results on specific legal settings and funding streams.
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 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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.024 | 0.009 |
| Scholarly communication | 0.012 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".