Ouyang Jingwu Buddhism Socialization and Sinology Education Philosophy
Bibliographic record
Abstract
The integration of Buddhism and Confucianism put forward by Ouyang Jingwu is the combination of pure Buddhism and Confucianism with original consciousnessonly theory as the focus, distinguishing itself from the traditional concept of the integration of Buddhism represented by Zen and Confucianism with the basis of Neo-Confucianism in the Song and Ming Dynasty. In the meanwhile, the integration of Confucianism and Buddhism come up with by him has a distinctive feature that Confucianism serves as the Buddhism’s knowledge of complying with the needs of society. He strictly defines the content of Confucianism and Buddhism to academically discuss the blending of inner logic of Buddhism and Confucianism. He criticizes the sinicized Buddhism which serves Tiantai Sect, Huanyan Sect and Jingtu School of Buddhism as mainstream, simply the China Buddhism classics liken Mahayana, reconstructs the inner school; he criticizes the mainstream Confucianism which is based on Neo-Confucianism in Song and Ming Dynasty, and the Confucianism which eschews quietus and ontology, he also criticized the fledgling Confucianism, and reconstructs the Confucianism. And then, he advocated to take the “Three Wisdoms and three gradual steps” as the main method to blend Confucianism and Buddhism. His fusion of Confucianism and Buddhism has brought profound influence to intellectual and elite at that time, making important significance.
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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 | 0.000 |
| 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 | 0.007 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".