COMPARATIVE ANALYSIS OF SEA LEGAL REQUIREMENTS AND INSTITUTIONAL STRUCTURE IN CHINA (MAINLAND), CANADA AND THE UK (ENGLAND)
Bibliographic record
Abstract
After the Law of the People's Republic of China on Environmental Impact Assessment (the EIA Law) came into effect in China (mainland) in September 2003, and notably in 2006, the Chinese government released a series of laws and regulations to strengthen strategic environmental assessment (SEA) application in China. SEA is acknowledged by the Chinese central government as a tool to help achieve sustainable development, and it is employed as an instrument to emphasise environmental protection and "scientific outlook of development" during the course of the current rapid industrial and urban development, to build a "harmonious society", and ultimately to achieve sustainable development. This paper compares the Chinese (mainland) SEA system, its legal requirements, institutional structure and procedural framework with the UK and the Canadian systems, to provide a comprehensive overview of the current status of the institutional and governance arrangements of the Chinese SEA system. The conclusions point to some possible explanations for less than optimum implementation of SEA in China, and suggestions for ways to improve the Chinese SEA system in the future.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".