Bibliographic record
Abstract
China underwent its most murderous famine between 1958 and 1962. Although a demographic transition from the countryside to the cities was in its early stage and gross domestic product (GDP) per capita was among the lowest in the world, objective conditions were far less decisive than Chinese Communist Party (CCP) policies in bringing about the famine. A development strategy copied on the Soviet model favoured quick industrialization at the expense of rural dwellers. Such novelties as people’s communes, communal canteens, and backyard furnaces further aggravated the famine. Though ethnic minorities represented only 6 percent of China’s population, compared to forty-seven percent in the Soviet Union, Soviet nationality policies heavily influenced those of China. Initially mild, especially for Tibetans, Chinese nationality policies became more authoritarian with the advent of the Great Leap Forward in 1958. Qinghai Tibetans resisted the closure of many monasteries; then the same policies, and famine itself, caused a more important rebellion in 1959 in Xizang (Tibet). Repression and the flight of the Dalai Lama to northern India coincided with the end of Tibet’s special status in China. Internal colonialism did not, however, aggravate the impact of famine on national minorities in China. Their rate of population growth between the first two censuses (1953 and 1982) exceeded that of Han Chinese. Among the provinces most severely affected by famine, only Qinghai was largely inhabited by ethnic minorities. Within Qinghai the same pattern prevailed as in Han populated provinces: the highest toll in famine deaths was concentrated in easily accessible grain surplus areas. The overwhelming majority of victims of the Chinese famine were Han peasants. At most, 5 percent were members of ethnic minorities, compared to eighty percent of victims in the Soviet Union in the period between 1930 and 1933.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".