Bibliographic record
Abstract
Conventional wisdom dictates that Chinese literati in the Qing dynasty (1644–1912), like their forerunners in previous dynasties, were politically active. Chinese Marxist historians tend to portray the Qing literati as politicians rather than scholars. Tang Zhiju, a China-based historian and the author of a book with an explicitly political title, Jindai Jingxue yu Zhengzhi (Modern Classical Learning and Politics), argues that the forefather of the Qing Evidential Research School, Gu Yanwu (1613–1682), used classical learning to maintain the Han people's national consciousness, and that the founders of the Gongyang New Text School, Zhuang Cunyu (1719–1788) and Liu Fenglu (1776–1829), applied the ‘sublime words with deep meaning’ in the Gongyang Chunqiu (Gongyang Commentary on Spring and Autumn Annals) to justify the Manchu's tianming (mandate of heaven). In late Qing, Tang contends, the New Text scholars Kang Youwei (1858–1927) and Liang Qichao (1873–1929) studied the classics with the intention of political reform, while the Old Text scholar Zhang Taiyan (1869–1936) developed the tradition in Confucianism of jingshi (managing the world) for anti-Manchu revolution.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.013 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.029 | 0.008 |
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".