A Comparative Study on EIA process in Malaysia, West Australia, New Zealand and Canada
Bibliographic record
Abstract
The Environmental Impact Assessment (EIA) has become an essential tool in promoting sustainable development and environmental protection since it was formally introduced by National Environmental Policy (NEPA) in 1969. The acceptance and application of EIA as a key tool in ensuring green development was overwhelming and has reflected positive feedbacks since its first introduction to the world community. The implementation of the EIA in various countries differs from one another as each country customised their own EIA process to cater their local development. This paper highlights the essentials of Environmental Impact Assessment and the EIA processes that have been adapted in four countries namely, Malaysia, West Australia, New Zealand and Canada. The three developed countries have been chosen because they share the same legal system as Malaysia which is the common law. The objective of this paper is to analyse the differences and the similarities between the EIA processes in the four chosen countries. The analysis was carried out by utilising a comparative study which was achieved via literature review. The comparative study reveals the similarities and differences of each EIA process implemented in the four countries. Conclusively, the four countries possessed few similarities such as each country has their own legal instrument, a governing body responsible in administering their local EIA process and incorporates public participation in the EIA process. However, the Canadian EIA process has a more notable EIA process between the four EIA processes, whereby, it possesses the most elaborate process which involves public participation at every level and takes up to 365 days for the EIA assessment.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.013 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".