Bibliographic record
Abstract
Choreographing the North examines 11 contemporary dance pieces that perform northern culture, landscape, folklore, and ideas of "North." The choreographers, from Canada, the United States, the United Kingdom, Belgium, Luxembourg, Australia, and Argentina, translate their real or imagined journeys to the North for stage and/or screen. This book examines the ways Indigenous subjects and subjectivities have been diminished and/or distorted and considers how that diminishment has fuelled misrepresentation both inside and outside the field of contemporary dance. Where Indigenous presence is represented in dances about the North, it is as discarnate storytellers or “everyman” pastoral figures against backdrops of ice and snow. Indigenous presence is there but it is romanticized, caricatured, flattened. Using these works as moving texts Cauthery argues that, in many regards, these dances are colonizing acts that either ignore or erase the land and people upon which they are based. In analyzing and deconstructing these dances, this book acknowledges the land- and culture-based inheritances embedded in and performed through the works themselves. This study will be of great interest to students and scholars in dance studies, theatre and performance studies, and cultural studies, as well as those interested in environmental psychology, human geography, and the expanding field of Arctic humanities.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.046 | 0.009 |
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".