Part 2: Moral motivation and moral cultivation in <i>Mencius</i> —When one burst of anger brings peace to the world
Bibliographic record
Abstract
Abstract As a 4th century BCE Confucian text, Mencius provides a rich reflection on moral emotions, such as empathy and compassion, and moral cultivation, which has drawn attention from scholars around the world. This two‐part discussion dwells on the idea of natural moral motivation expressed through the analogy of the four sprouts—particularly the sprout of ceyin zhixin (the heart of feelings others' distress)—as the starting point, the focus, and the drive of moral cultivation. In Part 1, I presented an integrated view of the sprouts as including cognitive, affective, and motivational aspects. In Part 2, I discuss the cultivation and application of natural moral motivation. I illustrate how the sprouts inform moral deliberation and drive moral cultivation, while also being its subject. I also demonstrate how emotional responses are managed and regulated according to the sprouts and discuss why moral cultivation is sometimes unsuccessful.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.009 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".