Consuming Fragments of Mao Zedong: The Chairman's Final Two Decades at the Helm
Bibliographic record
Abstract
Every people puts its own scent on its food, and it accepts change only if it can conceal the change from itself, by smothering each novelty in its scent. Optimism about change, whether in politics, economics or culture, is only possible if this premise is accepted. Theodore Zeldin, An Intimate History of Humanity , 1994 Nikita Khrushchev was not to Mao's taste. The Chairman of the Chinese Communist Party (CCP) showed no craving for gulyáskommunizmus . He hungered for something … er … different. In the remarkable art film The Ming Tombs Reservoir Fantasy from 1958 (in which Mao appears briefly in person), we are served a sampling of what it may have been. Set in 1978, ten years after the liberation of Taiwan, with New China well into the “higher phase of communist society [when] … all the springs of co-operative wealth flow more abundantly,” the film has young revolutionaries gathering in the shade of a tree from the branches of which grow bananas, apples, pears, loquats, lizhi … and living among farmers who each rear an average of 365 pigs a day to meet some of the dietary needs of a population that has found a cure for cancer (massive quantities of Turfan grapes) and whose members live to the ripe old age of well past a hundred. It is a unique record of the utopia of Mao's Great Leap Forward, a sweet Chinese dream of plenty.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 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".