Towards a Nanjing narrative of the Second World War in China: Navigating the stigma of an unspeakable past
Bibliographic record
Abstract
In China, the political act of collaboration with Japan during the Second World War has been cast as a moral flaw, with those who collaborated condemned as hanjian – traitors to the Han Chinese. This paper examines the fate of Hong Fanyu, a Chinese dentist in occupied Nanjing whose post-war career was ruined for treating a wartime collaborator (or hanjian). It maps the full extent of the stigma that still adheres to hanjian and those who associated with them, and examines some of the strategies used by those so tarred to handle the burdens of wartime history. For Hong, a poetic tribute written in 1947 in gratitude by Zhou Fohai, his jailed hanjian patient, that resurfaced in the 1970s during the Cultural Revolution, was enough to seal his fate; he was subjected to struggle sessions and died in 1979. His descendants’ invocation of professional obligation and service to the state, as well as the silences that persist around his ties with convicted hanjian Zhou Fohai, reflect both the persistence of stigma surrounding hanjian as well as the strategies used to negotiate the burdens of wartime history.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.034 | 0.035 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".