Profile of a Chinese Nationalist: the Life and Death of Dīng Zéliáng (1915–1957)
Bibliographic record
Abstract
Abstract When the Chinese historian Dīng Zéliáng denounced Timothy Richard (1845–1919) of the English Baptist Mission to be an agent of British imperialism, he voiced an opinion seldom found in Western literature on late Qīng China. Dīng discovered “evidence” in newly released Foreign Office files at the Public Record Office in London, England, pertaining to Richard’s attempt during the first Sino-Japanese War (1894–1895) to coax two powerful Qīng officials, Zhāng Zhīdòng in Nánjīng and Lǐ Hóngzhāng in Tiānjīn, into seeking Britain’s tutelage in post-war reconstruction. Unlike Richard, Dīng Zéliáng is not a familiar name in the annals of modern China. This article seeks to fill the biographical gap with a brief outline of his life, both as a backdrop to his condemnation of Richard and as an illustration of the kinds of intellectual and political turmoil that beleaguered educated Chinese in the post-Qīng decades. While surviving the manifold crisis of Republican politics, warlordism, and Japan’s invasions, Dīng proclaimed himself a “liberal,” embraced Marxism, and became a nationalist. Of this ideological mix, nationalism is arguably the most powerful component that explains not only Dīng’s vision for China’s future but also – across the wide divide of vastly different circumstances more than a half century later – China’s basic posture on the world stage.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.019 | 0.007 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".