Jeong Hagok on Emotions and the Korean Four-Seven Debate: A Confucian, Comparative, and Contemporary Interpretation
Bibliographic record
Abstract
This article presents Jeong Jedu (Hagok; 1649–1736) on the topic of emotions and its comparative and contemporary relevance. It discusses this leading neo-Confucian thinker’s thought-provoking Four-Seven thesis and its vital implication for self-cultivation and ethics. This important topic has not been discussed in current scholarship on Korean Confucianism. The article begins with the Confucian notion of emotions (jeong/qing, 情), according to its textual and philosophical background in the Chinese tradition, and then covers key issues regarding the “Four Beginnings” of virtue, the “Seven Emotions”, and leading neo-Confucian perspectives by Zhu Xi (1130–1200) and Wang Yangming (1472–1529). The article also provides a brief comparative analysis of Toegye’s and Yulgok’s leading Korean opinions on the nature, role, and problem of emotions. The third section focuses on Hagok’s interpretation in the same context. The fourth section discusses Hagok’s ethics and spirituality of emotions in terms of the mind’s original essence (bonche/benti) and innate knowledge (of good) (yangji/liangzhi) in connection to Wang Yangming’s doctrines. The final section concludes by considering the originality and distinctiveness of Hagok’s holistic interpretation. It also presents my contemporary reflections to articulate how Hagok’s groundbreaking insights compare with certain Western theories of emotions and why they offer a worthwhile resource for comparative philosophy, religion, and ethics.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.013 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".