Bibliographic record
Abstract
In the past decade, Vancouver dance has received tremendous acclaim nationally and internationally, as witnessed by the success of choreographer Crystal Pite and a rejuvenated Ballet BC. But this is only part of a vibrant and diverse story of contemporary movement practices in the city. In My Vancouver Dance History Peter Dickinson crafts an embodied narrative that focuses on his critical and creative collaborations with nine Vancouver-based dance artists and companies. Mixing interview excerpts with fieldwork descriptions of studio research and performance analysis, Dickinson draws on ten years of close observation to delve into the individual histories of select members of this community, while also relating the cumulative story of Vancouver dance production and performance as it has unfolded in the past decade. The voices of other invested participants interpolate this rich history, and chapters are interspersed with a series of "movement intervals" that reflect key moments in Dickinson's history as a spectator, scholar, and collaborator. In innovative ways, Dickinson suggests that when we pay attention to the larger social topography of dance practice - the sites that give rise to it, the labour that goes into it, and the professional friendships it engenders - we can properly understand dance's contributions to civic life.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.017 | 0.003 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.082 | 0.014 |
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".