Bibliographic record
Abstract
THE LONG MARCH The True History of Communist China's Founding Myth Sun Shuyun New York: Doubleday, 2006. 270pp, $34.00 cloth (ISBN 9781400134526)Getting facts straight on long march of Chinese communist forces retreating from southeast China (Jiangxi) ultimately to northwest China (Shaanxi) in 1934-35 is no easy matter. It is, as Sun Shuyun confirms in this readable account, national myth of People's Republic of China. Since march was made known to Westerners by Edgar Snow in his Red Star Over China (1937 in London; 1938 in New York), it has been presented as myth of sacrifice and redemption that vindicated Chinese Communist party and its then-emerging leader, Mao Zedong, as rightful rulers of China. These themes were amplified by party propaganda system and taught - in fashion of similar national myths in other countries - to generations of Chinese ever since, including to Sun, who learned this during last decade of Mao's rule (she was born in 1960s to a military family in China).Sun is clear from start: she wants to challenge that myth. For her, digging beyond patriotic paeans to long march involves asking: Was communism magnet that drew poor in droves to Red Army? How did it all work in detail? And what happened to four-fifths of approximately 100,000 marchers who never reached end (3)? Her answers are vivid: some people did believe, but many did not and joined by force of circumstance or at point of a rifle under forced conscription. Leaders, particularly Mao, made numerous mistakes and were often unfeeling of suffering of rank and file. The heroism of long march was mostly heroism of ordinary people, not Mao, other leaders, or idealized Red Army commanders from films Sun saw in China as a kid. Mostly, Sun's story emphasizes experience, memory, and voices of ordinary Chinese, many long forgotten and ill-served by army and party they either joined or endured. In end, Sun finds heroism, but it is not heroism of Mao and party, but heroism of these ordinary people. Their example now inspires Sun and her mission is to get their side of story out. The reason this is important, Sun says, is that dark side of long march that emerges helps to explain what went wrong later under Mao. The errors of later years and causes of sufferings of survivors she profiles can be seen in Jiangxi before long march (246). The implication is clear: it was rotten from start.Sun presents stories ofthe ordinary long marchers - and their lives since then - in style of a documentary film. This is no coincidence, as Sun is a filmmaker and television producer in England. Her scenes and images are vivid, and conversations taken from some 40 interviews are moving. She opens and closes with a few individuals, particularly tragic case of woman Wang (Wang Quanyuan), who after years of mistreatment still has faith in party. These are moving stories, well presented, based on extensive interviews, and all by a Chinese who grew up under Mao but now writes with freedom of one living in England. What's not to like?We should doubt a book that has the true history as part of its title. …
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.053 | 0.018 |
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".