Researching Spontaneous Doing: Random Dance as Decolonial Praxis in Dancing Grandmothers
Bibliographic record
Abstract
How are “hunch” and “intuition” passed on, and what kinds of knowledge are they? This essay examines Dancing Grandmothers (2011), a contemporary dance piece by Eun-me Ahn Dance Company, to study the piece’s production and transmission of embodied knowledge. The work’s dramaturgy of imperfection foregrounds makchum (random dance) as an important site of knowledge. The raw aesthetic of makchum revives the connection with the physical unconscious by decolonizing cognitive and embodied knowledge. I borrow from Ben Spatz’s epistemology of embodiment to analyze the “amateur” dance portion of Dancing Grandmothers, a section of the work that goes on stage without a rehearsal, and its invitation for the audience members to respond in embodied listening. Dancing Grandmothers is a form of decolonizing from within, where knowledge shifts mainly through remapping the perceptual rhetoric. It attempts to let the bodies speak for themselves, in equal authority with the dancers who co-create the piece. On top of contributing to a cognitive turn, the joy of dancing central to the performance conveys that animation, vitality, and revival are essential parts of knowledge, generating new energies by stimulating the senses.
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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 | 0.003 | 0.007 |
| 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 | 0.019 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".