Dr Wu Lien-teh: modernising post-1911 China’s public health service
Bibliographic record
Abstract
A young Chinese doctor from a small British colony gaining fame for his role in ending a pneumonic plague in faraway north-east China is indeed a remarkable story. Wu Lien-teh (1879–1960), although standing at only 5 feet 2 inches, short even by Chinese standards, towered over many of his contemporaries because of his dedicated medical work. He was also prominent in the advancement of social and cultural causes. In particular, he campaigned against the opium trade, which had caused irreparable harm to health in China and Southeast Asia. Beyond his battle against the pneumonic plague in Manchuria, Wu was also in the forefront of efforts to create a modern public health service in China. His efforts helped China regain control of quarantine centres in all major ports that had come under the supervision of foreign powers. Wu was also called to deal with the cholera epidemic in China's north-east region in 1920–21. Active in international conferences and research, Wu was the first Chinese to have his work published in the prestigious medical journal, Lancet. For his contributions, Wu was conferred honorary doctorates by Peking University, Hong Kong University and Tokyo University. In 1935, he was nominated for the Nobel prize for his fight against the 1910 Manchurian plague and for identifying the role of tarbagan marmots in the transmission of the disease.(1) The epidemic, one of the deadliest of its kind, killed an estimated 60,000 people in the affected regions of Manchuria during the seven months that it lasted.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".