Integrated arts textbooks in Taiwan and the USA: a single series examination
Bibliographic record
Abstract
The purpose of this article is to examine current arts and humanities elementary school textbooks in Taiwan and to make recommendations for the future. Using the paradigms of curriculum integration of Beane, Berton, Jacobs, and Snyder as a basis, the article compares selected current arts and humanities texts in both Taiwan and the USA, noting, first, the proportion of music versus other disciplines in each, and, second, the organizational method. Important findings are that the selected Taiwanese texts do not feature sufficient musical material in comparison with their US counterparts and also that the organizational method of the Taiwanese texts fosters confusion among teachers. Implications for the wider community include the facts that new textbooks should be piloted prior to receiving government approval, that the uniqueness of each art discipline should be preserved within carefully crafted thematic units, and that music can serve as an effective bridge between the various art disciplines.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".