Fragmenting cripistemology: Gap movement and choreographic practice
Bibliographic record
Abstract
This article attends to the creative process of our choreographic video essay, Mourning Movements (2023). Between the distances of Tkaranto (Toronto) and Lenapehoking (New York City), we explore approaches and methods for choreographic practice through gaps of space, time and differing corporealities. Theorizing our creative collaboration within these gaps, the methodological framework of fragmentation emerges as a network for disjointed choreographic sense-making. Refiguring our ‘gap’ movement as crip choreographic practice, we consider fragmentation as a basis for a choreography that embraces disability, distance, pauses and non-cohesion. We reflect on our practices of score-work, dance improvisation, audio-description, poetry, storytelling, theoretical provocation, text messaging, Zoom meetings and Google Doc harbouring to reveal our collaborative and care-full labour of creation. We offer a proposal of ‘fragmenting cripistemologies’ which considers fragmentation as reciprocal with disabled knowing and questioning or cripistemology. Our proposal imagines disability as a source for fugitive choreographic practice through which we can potentialize, refuse and reinterpret movement.
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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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.010 | 0.060 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".