Moving Towards Dance and Re-Entering the Post-Pandemic Classroom
Bibliographic record
Abstract
In a pandemic and post-pandemic setting, little discussion centres the re-entering of spaces. Having moved from the private-public sphere of online, socially-distanced learning to the public sphere of being back in classrooms, students have had to make major adjustments on their own, without being supported in conversation around the body and space. The Ontario curriculum places dance in the arts curriculum, apart from health and physical education, diminishing the social and health benefits of moving together. Through a contemporary lens, we can reimagine what a movement curriculum can look like for Grades 1-8, to include movement, dance and embodied practices, acknowledging the many benefits of working from a body-first approach.
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.023 | 0.030 |
| Scholarly communication | 0.016 | 0.009 |
| Open science | 0.003 | 0.024 |
| Research integrity | 0.004 | 0.012 |
| Insufficient payload (model declined to judge) | 0.015 | 0.003 |
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".