The First Rush of Movement: A Phenomenological Preface to Movement Education
Bibliographic record
Abstract
Children’s lived experiences of movement indicate possibilities for teaching them to be at home in increasingly challenging domains of activity. Especially significant are movements that reflect landscape connection, that carry an intention not confined to individual purpose, and that are enhanced by observational glance. The first rush of movement is described phenomenologically as an essential feature of these movements and of the vital consciousness they engender. The phenomenon of the first rush of movement attests to a mimetic impulse towards otherness that overrides personal motive and moderates an otherwise containing gaze. Its intentionality is evident in an extended, inclusive and progressive range of human movements that affirm a natural, intimate relation with others and the world at large. The embrace, caress and kiss are described as primary, elemental gestures from which movement disciplines sustaining the first rush of moment and its mimetic impulse can be cultivated. Accordingly, this study prefaces a practice of education in which children’s movements, originating in responsiveness to landscape and motivated by a mimetic impulse, can be guided towards enhanced and sustaining world relations. Vital qualities of movement can be sustained from childhood to adulthood and from the most rudimentary contacts with the world to the most refined, skill-based encounters.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.024 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.006 |
| 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".