Bibliographic record
Abstract
Since October 1, 2003, grain prices have dramatically risen in China for the first time since 1997. Driven up by the grain price increase, the prices for meat, edible oil, eggs and fodder have all seen a rise. The grain price hikes result from many reasons. China has been using its grain reserves to keep a balance between supply and demand for the last four years; since 1999, China has suffered continuously smaller yields; last year the grain output in United States, Canada and Australia, having sharply drops and in Europe this year, has significantly driven up grain prices on the world market. The current situation alert on food security in China. The issue of food security closely related with land issue. On the recent Third Plenary Session of the 16th Central Committee of the CPC, land issue and issues on agriculture, rural areas and farmers have become a focus of our party and the nation. According to Chinese Constitution, all urban land is owned by the State, any land sales are absolutely forbidden and only governments and land management departments have the right to uncompensatedly transfer land use right, which the article Leads to a series of corruption related to real estate development and residents relocation. Especially in recent years the swift expansion of towns and cities, many local governments have constructed much more Development Zones , which occupied a large amount of shrinking cultivated land. As cities expanding, large quantities of agriculture land have been requisitioned. On the other hand, the compensation standards applied are very low and farmers are not properly compensated. The interests of farmers, who have lost their land, have not been fully protected in some requisition programs. To protect and improve the country grain production capabilities, land annexation, which have proven successful in United States, can push the pace of agriculture modernization and industrialization. But under the current land system, how can the ideal be realized?
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".