The I-TEC Design Framework for Kinesthetic Transmission in Online Spaces
Bibliographic record
Abstract
Disseminating dance in online spaces provides an opportunity for kinesthetic knowledge to reach broader audiences. However, the transmission of dance in online spaces also primarily relies on visual and aural modalities that cannot fully capture the nuanced physical sensations of a kinesthetic experience. In recent years there has been an influx of interactive online dance resources; yet there is little analysis of how these works effectively translate kinesthetic knowledge to online audiences. We bring together research in dance film and interaction design practices to explore kinesthetic transmission in online spaces and conduct analyses on interactive digital dance resources. Based on our literature review and analyses of these dance resources we propose the I-TEC design framework for kinesthetic transmission. In this framework, Instructional, Translational, Exploratory, and Contextual interactions are brought together to expose the multiple embodiments, perspectives, and translations of kinesthesia.
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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 | 0.011 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.010 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 0.004 |
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".