The Early Qing Compilation of the Ming History in Manchu: The Contexts, Contents, and Significance of the Ming gurun i suduri
Bibliographic record
Abstract
Abstract The Qing court produced an extensive history of the Ming empire in the Manchu language, which has survived in manuscript form in the Palace Museum under the title Ming gurun i suduri (History of the Ming State). Based on a close reading of this manuscript and scrutiny of related archival documents, this article elaborates on three observations. First, the Ming gurun i suduri resulted from the earliest stage (1645–1669) of the Qing compilation of the Ming history. With a primary focus on producing a chronicle in Manchu, it exemplifies the mid-seventeenth-century development of Inner Asian historiography. Second, it recounts Ming history by juxtaposing and connecting translated extracts from the Ming shilu 明實錄 (Ming Veritable Records) whenever it exists. This approach that combines compiling and translating, in effect, offers a reassessment of key political events and figures. Third, in light of the Ming gurun i suduri thus contextualized, the 1739 Ming shi 明史 (Ming History) is best seen as a product of a century-long history of negotiation (1645–1739) during which the ideological agenda and intellectual achievements of the early Qing court gradually sank into oblivion.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".