Cultivating Skillful Means of Care in Schools Through Compassion Practice and Individual and Joint Inquiry
Bibliographic record
Abstract
Objectives: We examined the extent to which compassion practices helped guide skillful means of care among educators. We engaged educators in a collaborative design (co-design) process that foregrounded two components: (1) contemplative practice and (2) developing skill in how social interactions are embedded within wider systems through individual and joint inquiry. We analyzed the ways educators developed awareness of social suffering and set intentions to alleviate suffering. We examined how co-design fostered an understanding of compassion and new ideas about how to respond skillfully to suffering in schools. Methods: Using qualitative methods, we analyzed data from educators who participated in co-design, including their written reflections, field notes, semi-structured interviews, and surveys. Results: Educators identified multiple opportunities for acting with compassion, including approaching school-based interactions with compassion, cultivating compassion for themselves, and envisioning school change through a lens of compassion. Educators' experiences in co-design directly informed how they imagined compassionate action in their schools. Specific elements highlighted were contemplative practice, reflection, and individual and joint inquiry. Conclusions: The adaptation of a general program on compassion training can benefit from attending to how to show compassion in the context of concrete interactions in schools, and this can support educators in developing skillful means of care. Our analyses provide insight into the components that supported educators to offer compassion and suggest that educators' skillful means of care can be cultivated through both contemplative practice and inquiry into social suffering. We offer a conceptual model for developing skillful means of care educational settings.
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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 | 0.051 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.008 | 0.020 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".