Artistic education from an international perspective: An inquiry into relevant topics, professional networks and research perspectives
Bibliographic record
Abstract
This article aims to approach the current state of Arts Education internationally. To this end, it presents the results of documentary research based on three axes: 1. The transition from an Art Education centred on transnational movements and perspectives (as expression, disciplinary basis, language, aesthetics and visual culture) to more local approaches. It focused on specific issues (social justice, decoloniality, digitalisation, etc.). 2. The professional networks link those involved in Art Education, where 3 cases are analysed: Art Education Australia, the Canadian Society of Art Education and the National Society for Education in Art and Design. And 3. The predominant research perspectives in this field are based on analyzing the proceedings from the annual European ECER conference published from NW29. Research on Arts Education (NW29) on in the past three editions. The vision that emerges from this overview is of a diverse movement with strengths and weaknesses, which continues to demand recognition in educational and cultural policies. The article closes with the outline of a balance and the formulation of some prospective lines to continue the conversation and the claim
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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 | 0.010 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.012 | 0.021 |
| Scholarly communication | 0.027 | 0.017 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 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".