Cultural Expressions of Tokugawa Japan and ChosÅn Korea: an Analysis of the Korean Embassies in the Eighteenth Century
Bibliographic record
Abstract
This doctoral thesis presents a historical study of the diplomatic exchanges between the Japanese and the Korean embassy in the eighteenth century. Neighbourly relationships (J: kōrin, K: kyorin) were maintained between Tokugawa Japan (1603-1868) and Chosŏn Korea (1392-1910) for more than 250 years. The visitations of the Korean embassy, dispatched to congratulate a new Tokugawa shogun, were often seen as the symbol of their amicable and friendly relationship, and it is well known that the Koreans were cordially welcomed by the Tokugawa bakufu. Despite these neighbourly relations, the visitations of the embassy had a more pragmatic purpose. More complex political conditions and nature were immanent within and between the both states. In the diplomatic interaction, the officials in the two states had traditional and obstinately-held perceptions towards the counterpart hidden behind the pleasant gesture. \n\tIn this thesis, I attempt to uncover what is associated with these neighbourly relations, by revealing the cultural awareness and consciousness of these two states in East Asia through detailed examinations of the historical sources. To find the notions behind the exchange, my thesis illustrates Japanese and Korean hua-yi awareness that came to light through the interactions between the Japanese and the Koreans. The Chinese hua-yi order, the concept of looking at the Chinese dynasties as the center, was said to dominate the East Asian order. From the Chinese point of view, Tokugawa Japan and Chosŏn Korea were barbaric and on the margins, but from the perspectives of the two countries, they certainly recognized themselves as the centers.\nOn the basis of the dynamism of historical events, thoughts, and notions between Tokugawa Japan and Chosŏn Korea in the eighteenth century, this research will examine multi-layered perspectives of the individual Japanese and Koreans who played essential roles in diplomacy. How were those officials representing the two states aware of their peers, and how did these notions affect the modern history of the two countries? This question is consistently engaged in this thesis, and to answer it the research will be further explored.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".