From inclusion to integration: intercultural dialogue and contemporary university dance education
Bibliographic record
Abstract
It was not until the 1980s, more than half a century after modern dance became the centre of university dance programmes, that dance educators began writing about diversity issues. While some authors have addressed the importance of diversifying curricula and others have written specifically about classes they re‐visioned in a more multicultural way, few have written about how we might go about updating university dance departments in a practical way at the level of curriculum. In this article, two dance professors, one in Canada and the other in Brazil, discuss the ideological foundations of existing university dance programmes to imagine a more inclusive vision for dance education in increasingly globalized local contexts. They then share the model that they have developed for contemporary, intercultural dance curricula at the university level, which is rooted in the principles of dialogue and integration.
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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 | 0.014 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.023 | 0.089 |
| Scholarly communication | 0.025 | 0.017 |
| Open science | 0.002 | 0.026 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 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".