Bibliographic record
Abstract
In this paper,we study the relations among industrial structure,carbon dioxide emissions and economic growth using panel data of eight typical examples of developed countries-the U. S.,Canada,the U. K.,France,Germany,Australia,Japan and Korea-and four typical examples of developing countries-China,India,Brazil and South Africa between 1980 and 2010. The econometric results indicate that there exists long-run integration relations among industrial structure,carbon dioxide emissions and GDP growth in these sample countries; carbon dioxide emissions and GDP growth in the developed countries are negatively correlated; carbon dioxide emissions and GDP growth in the developing countries are positively correlated; manufacturing and GDP growth are positively correlated in all the sample countries. The Granger causality test that focuses on China shows that the change in industrial structure or carbon dioxide emissions is not one cause of the change in the GDP growth rate,which makes it clear that the Chinese policies to readjust industrial structure or to restrict carbon dioxide emissions aiming to transforming the GDP growth model will not necessarily negatively influence China's economic growth rate. The government maintains high GDP growth rate,especially through the local government' GDP target tier upon tie assignment,which aggravate the deviation of the Chinese industrial structure. The deviation to the second industry,the industry and the heavy or large-scale industry's industrial structure and relying on the coal consumptions structure leads to excessive carbon dioxide emissions. The carbon dioxide emissions of per capita GDP in china are so much high than the developing and developed countries. In 2010,the carbon dioxide emissions from the coal consumption to the total carbon dioxide emissions in china is 82 percent,in United States is 35 percent,in German is 38 percent.The key way to Chinese government transforming the economy development pattern is adjusting the industrial structure. The key point to industrial structure adjustment is reduce the industry added value to GDP,especially reduce the high pollution,high energy consumption,high carbon dioxide emission of heavy or large-scale industry added value to GDP,improve the research and development ability,and change the disadvantageous positions of the lower margin in manufacture chains,properly raise the wholesale,retail trade,restaurants and hotels,transport,storage and communication,and other service activities' s added value to GDP. The second point is adjusting the energy consumption structure,reduce the coal consumption. All of these are the key roads to decrease the greenhouse gases and haze gases.In short-term,mandatory energy conservation and decrease the carbon dioxide emissions maybe influence the GDP growth rate,but from the long-term experiences of the developed countries,energy conservation and carbon dioxide emissions reduction may not influence the GDP growth rate,on the contrary it may boost the GDP growth. The higher GDP growth rate in China especially the local government pursuing the GDP growth rate distorts the industry structure,which leads to the higher carbon dioxide emissions level. Although china acquires outstanding economy growth rate,every year the GDP growth rate above 10 percent,the environment costs are very high. It should not sacrifice the environment for the GDP. This development pattern should be corrected as soon as possible. The government pursuing higher GDP growth rate worsen the industrial structure,exacerbate the Chinese environment and ecology civilization. The Chinese government should not worry about the slower GDP growth rate,because it favors to the industry structure adjustment and favors to carbon dioxide emissions reduction. The experiences of energy conservation and carbon dioxide emission reduction are worth learning to China.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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; both teacher heads agree on what is shown here.
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".