MétaCan
Menu
Back to cohort
Record W2074766527 · doi:10.11113/jt.v70.2378

A Comparative Study on EIA process in Malaysia, West Australia, New Zealand and Canada

2014· article· en· W2074766527 on OpenAlexaboutno aff
Maisarah Makmor, Zulhabri Ismail

Bibliographic record

VenueJurnal Teknologi · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental and Social Impact Assessments
Canadian institutionsnot available
Fundersnot available
KeywordsProcess (computing)Environmental impact assessmentEnvironmental planningSustainable developmentPolitical scienceDeveloping countryEnvironmental resource managementBusinessRegional scienceEnvironmental protectionGeographyEconomic growthComputer scienceLawEnvironmental scienceEconomics

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.269
Threshold uncertainty score0.622

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.029
GPT teacher head0.313
Teacher spread0.284 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations8
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueJurnal TeknologiSame topicEnvironmental and Social Impact AssessmentsFrench-language works237,207