Moving Together : Dance and Pluralism in Canada
Bibliographic record
Abstract
Moving Together: Dance and Pluralism in Canada explores how dance intersects with the shifting concerns of pluralism in a variety of racial and ethnic communities across Canada. Focusing on the twentieth and twenty-first centuries, contributors examine a broad range of dance styles used to promote diversity and intercultural collaborations. Examples include Fijian dance in Vancouver; Japanese dance in Lethbridge; Danish, Chinese, Kathak, and Flamenco dance in Toronto; African and European contemporary dance styles in Montreal; and Ukrainian dance in Cape Breton. Interviews with Indigenous and Middle Eastern dance artists along with an artist statement by a Bharata Natyam and contemporary dance choreographer provide valuable artist perspectives. Contributors offer strategies to decolonize dance education and also challenge longstanding critiques of multiculturalism. Moving Together demonstrates that dance is at the cutting edge of rethinking the contours of race and ethnicity in Canada and is necessary reading for scholars, students, dance artists and audiences, and everyone interested in thinking about the future of racial and ethnic pluralism in Canada.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.031 | 0.010 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".