Bibliographic record
Abstract
For 70 years, Bethune Studies in China is on the way from propaganda to academic research. Mao Zedong’s In memory of Norman Bethune and Zhou Erfu’s Dr. Bethune have played an important role in propagandizing the image of Bethune. The Scalpel, the Sword by Ted Allan and Sydney Gordon and The Politics of Passion -Norman Bethune's Writing and Art by Larry Hannant are especially the significant works to study Bethune. Since the beginning of 1980s some new features have been presented, such as new information, endless emerging of new works, enlarged number of researchers and the organizational trend of the study and so on. Of cause we have more work to do, which needs the cooperation and the communication between researchers in different areas, between different branches of learning or even between different countries. Key Words: Norman Bethune; Bethune Study; CanadaResume: Depuis 70 ans en Chine, des etudes sur Bethune se transforment de la propagande en recherche universitaire. A la memoire de Norman Bethune de Mao Zedong et Docteur Bethune de Zhou Erfu ont joue un role important dans la popularisation de l'image de Bethune. Le Scalpel et l'epee de Ted Allan et Sydney Gordon, et Politique de passion - creations et recits de Norman Bethune de Larry Hannant sont notamment des oeuvres importantes pour les etudes sur Bethune. Depuis le debut des annees 1980, de nouvelles caracteristiques ont ete presentees, tels que de nouvelles informations, de nouvelles œuvres emergentes, un nombre accru de chercheurs, la tendance organisationelle de l'etude etc. Nous avons bien sur encore du travail a faire, ce qui necessite la cooperation et la communication entre chercheurs de differents domaines, entre differentes branches de connaissances ou meme entre differents pays.Mots-cles: Norman Bethune; etudes sur Bethune; Canada
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.010 |
| Science and technology studies | 0.023 | 0.007 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.022 | 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".