Bibliographic record
Abstract
The purpose of this paper is to make a contribution to our working knowledge, practice and pedagogy of compassion through consideration of a Daoist perspective on the matter. I begin with a consideration of Daoist cosmology and a sage’s compassion drawn primarily from the Daodejing, This serves as a backdrop to consider Daoist contemplative pedagogy for the cultivation of virtue and compassion. Consistent with Daoist practices which rely on exemplars as a means of inspiring others I justify considering Nelson Mandela an exemplar of compassion. I then discuss how his life lines up with the Daoist conception of compassion. Finally I discuss the practicalities of developing compassion along with other virtues in post-secondary business ethics education classes. These classes work with the following principles: starting small, self- compassion, person to person connections and relationship. Students engage in emotional intelligence activities including: exercises to know their purpose or calling, meditative exercises that help them become aware of their emotions, and structured interpersonal interaction challenging them to develop new social skills. While this work is in its early stages it appears to assist students in developing compassion for others.
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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 | 0.008 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.052 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.006 |
| 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".