SIMULATION OF ENVIRONMENT AND ECONOMY SECURITY OF CHINA UNDER GLOBAL CHANGES WITH COMPLEXITY
Bibliographic record
Abstract
The problem of economy security under the changes of global climate is paid more attention all over the world now. And its complexity and indeterminacy become a focus in research. The present paper discusses the problem of Chinese economy security under the changes of global climate in three steps. First, the complexity of changes of global climate is analyzed. Through the analysis a model could being used to evaluate the environment and economy security under the changes of global climate is obtained. This model is based on the model of Lave and Shevliakova. Second, a mathematic simulation about proportion of food demand and supply from 2025 to 2050 in China is given by SEI model. Through the simulation two conclusions are obtained. They are (1) in 2025, if food consumption level in China keeps the level of 1990 then there is no problem of food security. If food consumption level is improved then there is problem of food shortage. And the percentage of food shortage is about 7%～8%; (2) in 2050, if the population in China is in control then there is no problem of food security. Because now the population in some areas is not in control actually, in the future the proportion of food demand and supply will keep in 0.92～1.04. Third, the analysis of water problem in China based on the statistic data in 1985 is given. In the analysis a general equilibrium model is used. By the calculation and the analysis a conclusion that the affection of water under the changes of global climate could not lead to problems of economy security in China is gained.
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".