Bibliographic record
Abstract
This book situates mindfulness and contemplative interaction at the heart of transformative learning for a more sustainable and compassionate world. Drawing on a mixed-methods study of a specific set of reflective learning activities introduced to undergraduates in Canada, the book highlights the importance of critical thinking and the necessity of the underlying affective dispositions to transformative learning. It argues that contemplative practices can play a central role in creating an unexpected sense of connectedness even among students who do not agree with each other, who may come from widely different backgrounds, and who may not speak English as a first language. These practices encourage students to improve their listening skills, suspend judgments, and explore multiple points of view without confirmation bias or rigidity. Mindfulness and contemplative interaction are further discussed in the context of the growing use of generative AI in higher education and the practical issues of student evaluation and feedback. This forward-thinking volume will appeal to contemplative practice scholars in the field of higher education, as well as educators and researchers with interests in transformative learning, critical thinking, and applied mindfulness.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.016 | 0.006 |
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".