The in-Tensions of Extensions: Compagnie Marie Chouinard's<i>bODY Remix gOLDBERG vARIATIONS</i>
Bibliographic record
Abstract
This essay explores the affective intensity of movement in a recent choreography by noted French Canadian choreographer Marie Chouinard. In bODY rEMIX/ gOLDBERG vARIATIONS, dancers perform with all manners of prosthetics and bodily extensions--crutches, ski poles, coat racks, pointe shoes worn by men and women, on one or two feet or on hands--to a score that remixes Glenn Gould's recordings of the Goldberg Variations with his recorded interviews. Drawing on Gilles Deleuze, José Gil, and André Lepecki, I argue that despite its engagement with forms of extension, the use of prosthetics in Chouinard's bODY rEMIX fundamentally explores the intensive movement of affect, particularly through its engagement with suspense (as the generation of an ambiguous image in the tension between extensive and intensive movement) and the sound image. This exploration of the in-tensions of extensions, when, rather than simply extending into the world, movement develops a centrifugal force, likewise argues that the movement of affective intensity is the way in which the body activates its inherent capacity for change. Extension is a fundamental attitude of the dancing body; dancing “projects lines into the invisible” in a movement of outward intentionality. Yet that movement is always doubled and deviated by a responsive (not simply reactive) intensity of movement, a dynamic activation of the body's potential charged by the encounter that pushes against and reworks the constitution of the very bodies that compose it, a movement of a different quality whose effects cannot simply be determined by a reverse calculation from extension.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.016 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".