Holistic Education and Embodied Learning
Bibliographic record
Abstract
Learning often begins with an experience in the body. Our body can tighten or feel expansive depending on different learning contexts. This experience of learning in the body is crucial to holistic education. This book explores embodied learning from several perspectives.This first section explores how psychology can inform us about embodied learning; for example, the work of Carl Jung and Wilhelm Reich devoted much of their thinking to how energy manifests itself in the body. Meditation and movement are also examined as ways of embodied learning; for example, Dalcroze, a form of movement education, is presented within the context of whole person education. The book also presents schools where embodied learning is nurtured. Waldorf education is discussed as well as a public school in Toronto where the body is central to holistic education. The book also presents visions of embodied learning. John Miller presents a holistic vision of teacher education and Tobin Hart, who has written extensively in this field, writes about the embodied mind.Embodied learning is an emerging area of inquiry in holistic education and this book presents a variety of perspectives and practices that should be helpful to both scholars and practitioners.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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".