Exploring the Bases of Holistic Education
Bibliographic record
Abstract
The term ‘Holistic Education’ is quite popular in the sector of education. But it is much difficult to define it in one line. Ron Miller and John Miller, who were the main proponents of the holistic education movement, tried to classify and conceptualize this term. John Miller published ‘The Holistic Curriculum’ in 1988 in Canada, which was the first rational as well as methodical account of Holistic Education. In 1990, Ron Miller published ‘What are School for? Holistic Education in American Culture’, which may be called the pioneer book of Holistic Education. Holistic Education has focused on creating new learners’ community who will be connected mentally with this planet. It has not focused on self but nurturing the students that they can reach beyond self realization. Then they can make relationship with larger community, nation, planet and the universe (Vengopal & Kumari, 2010). In this paper, the present researcher tried to discover afresh the bases of holistic education from the existing related literature. In doing this, extensive exploration was done through content analysis method and then seven bases namely, a) Community / Global Connectedness b) Emotional Stability c) Education on Democracy d) Value based Learning e) Peace Education f) Learning of Social Responsibility g) Compassion/Empathy were identified and discussed thoroughly in this paper.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.004 | 0.016 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| 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".