China's industrial SO<sub>2</sub> emissions and its economic determinants: EKC's reduced vs. structural model and the role of international trade
Bibliographic record
Abstract
ABSTRACT This paper discusses the validity of the Environmental Kuznets Curve (EKC) hypothesis for the case of China's industrial SO2 emissions: both its reduced form and structural model are considered. The EKC curve for China's per capita industrial SO2 emissions predicts the turning point at 10,000 yuan (3,085 US$, Purchasing Power Parity (PPP)). However, given China's fast population expansion, the decreasing trend in per capita emissions may well not be enough to bring about an immediate reduction in terms of total industrial SO2 emissions and emissions density. Using the structural EKC model makes it possible to reveal how various factors contribute to the industrial SO2 emissions density – namely, the three commonly known structural determinants and the marginal impact of international trade. International trade proves to have a two-fold impact: a significantly negative direct one and an indirect one that is dependent on the current capital–labour abundance ratio and on the income level of each province.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".