Embodying Kinaesthetic Stimulants in a Technological World, A Kinaesthetic Exploration of Western Technology's Affect on the Body
Bibliographic record
Abstract
This thesis addresses the potential kinaesthetic influences technology has on the body and how these influences can be used to extract original choreography. Based on Gretchen Schiller’s assertions that the body’s interactions with technology “contribute to the range of one’s movement repertoire and kinaesthetic condition” (Schiller 109), this research purports that the body’s interactions with transportation technology (specifically trains, subways, and automobiles), hand-held technology (cell phones, video games, and electronic children’s toys), online networking, and the television, affect its kinaesthetic condition. This is achieved through the body’s experience of new shapes, tensions, and weight-holding patterns. The individual experiences of urban Western bodies are specifically researched, particularly those in Toronto, Canada. Through site-specific movement explorations, this thesis argues that a heightened kinaesthetic awareness allows a choreographer to extract technological qualities and create original choreography. This process will, in turn, widen the choreographer’s awareness to other kinaesthetic movement inspirations.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.011 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".