Population Size,Economics Growth and Carbon Emission:Based on the Empirical Analysis and International Comparison
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
According to the data of CO2 Emissions from International Energy Agency from 1971 to 2008,this paper discusses the differences of population size,economics growth and Carbon emissions among G8+5 countries in the world.The Results show that the Carbon emission per capital of China has exceeded the average level of the world.The Carbon emission per GDP of China keeps on reducing at present,but it still surpasses the average level of the world.Analyzing the rank coherent coefficient of Carbon emission per capital and Carbon emission per GDP,this paper indicates most of developed countries present declining tendency.In the developing countries,China and South Africa present declining tendency,at the same time,other developing countries presents rising tendency,such as Brazil India and Mexico.Analyzing the rank coherent coefficient of GDP per capital and Carbon emission per capital,this paper indicates most of developing countries present rising tendency of Carbon emission per capital.In the developed countries,America,France,German and UK present declining tendency obviously,at the same time,Canada does not present rising tendency obviously,Japan and Italy present rising tendency obviously.Finally,there are three types of model about population growth,economics growth and Carbon emission to be generalized of the most of developed and developing countries in the world.
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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 | 0.000 |
| 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 it