Dance Education, Decolonization, and the Climate Crisis: Developing Ethical Pedagogies
Bibliographic record
Abstract
To date, there has been minimal analysis of the intersections between dance pedagogy and the climate crisis. Arguing that it is essential to approach the climate crisis via the lens of decolonization and underscoring the indivisible links between modernity, coloniality, and the climate emergency, the author considers what it might mean to develop an ethical dance pedagogy for a student population facing the grim consequences of climate change. After highlighting the academy’s decolonizing failures, the author applies principles from Indigenous scholars Andreotti, Hunt, and others to offer a pedagogical case study of her own deep dive into her position on stolen land. Arguing that it is critical to model such digging to demonstrate our collective complicity in the hegemonic systems of modernity/coloniality, the author concludes by bringing together emerging methods developing both inside and outside of dance education to propose a scaffolding for an ethical dance pedagogy for the twenty-first century.
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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 | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.029 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".