Meditation and Holistic Contemplative Pedagogy: An Exploration of the Relationship of Five Teachers' Meditation Practices to the Pedagogical Process
Bibliographic record
Abstract
This qualitative study examines how five teachers' meditation practices have an impact on their pedagogy. The teachers' spiritual practice of mindfulness meditation shapes their understanding of themselves and their students, generating a holistic contemplative pedagogy. While there has been a growing body of literature on meditation, contemplation and holistic education, this research brings these fields into a more in-depth, detailed conversation. Teachers gain knowledge from their lived experience in the profession, which works to benefit their mindfulness practice. The study reveals that the experiential practice of mindfulness meditation can help teachers access their thoughts and feelings better, and create a more benevolent engagement with students. Meditation helps the teachers transcend and recast negative emotions. Through mindfulness, they become more loving and respectful of both themselves and their students, all while providing them a safer space in which to thrive. The practice of meditation, then, mirrors the practice of teaching. Mindfulness meditation helps shape a holistic contemplative pedagogy, which enhances teachers' understandings of their profession and the lives of students in a contemporary moment of change. The dissertation, therefore, contributes to a wider field of inquiry into the benefits of mindfulness meditation, not only in education, but also in the human sciences more broadly.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.008 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| 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".