Sharing dance: a participatory action research project in online community dance education
Bibliographic record
Abstract
"As a dance and movement workshop leader for over five years I have seen the benefits that dance education offers students first hand. While on tour across Northern Ontario with the Cree language opera Pimooteewin: The Journey, I had the opportunity to share creative dance workshops with students living in remote locations. These students had limited access to dance education and most schools I visited had no integrated dance curriculum. I found this surprising since the inclusion of dance in Ontario public schools is a requirement. Dance was incorporated into the 1993 Common Curriculum and the 1998 Ontario Curriculum (Ministry of Education). Many teachers I spoke with while on tour mentioned they did not have access to high quality, free dance education materials, and did not feel comfortable teaching the subject. This experience drew me to develop an applied research project with Canada's National Ballet School's (CNBS) community outreach initiative, Sharing Dance. Unlike other online dance education organizations, such as the Council for Ontario Dance and Drama Educators (CODE) that works on a subscription model, Sharing Dance offers teachers easy access to dance education materials for free, potentially overcoming location and socioeconomic obstacles"--From introduction, page 1-2.
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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 | 0.085 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.020 | 0.014 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.004 | 0.013 |
| 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".