Dancing Teachers Into Being With a Garden, or How to Swing or Parkour the Strict Grid of Schooling
Bibliographic record
Abstract
Abstract The co-authors, collaborators in garden-based teacher education, question the hegemony of grids in Western time, space and relationship structures in education, while also delving into our own complicity and entanglement with these grids. We ask: (1) Can we reject the grid in environmental education and in garden-based learning when it is an intimate part of our way of being in the world? (2) Can we be teachers who are at once within and not-within the regime of the Western Enlightenment/Modernist grid? (3) How can we take a ludic approach to the grid? Can we ‘swing’ and ‘parkour’ the strict grid of schooling? Pleasures and failures of the grid and experiences of alternatives to the grid are documented and exemplified through stories from garden-based teacher education. Considering parallels with principles of the alter-global movement and with the performative, embodied practices of swing dance, parkour and clowning, we meditate on becoming ecological teachers together beside the grid — neither within nor without it, but with a deep awareness of its presence and structure. In uncertain, unchanging times, we want to take a playful, artistic approach to the old certainties and structures, swinging and parkouring from them rather than accepting or rejecting binary formulations.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 0.031 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".