The development of policy and legal framework for social impact assessment in Malaysia
Bibliographic record
Abstract
Social Impact Assessment (SIA) is an assessment tool that assess the social effects of infrastructure and major projects and is conducted in many countries, including the United States, Australia, Canada, India, South Africa, New Zealand, and Japan. Malaysia requires such form of assessment for projects deemed to have social implications prior to obtaining planning permission from the local planning authorities. The requirement of the submission of SIA report as part of planning permission requirement necessitates from section 20B (2) of the Town and Country Planning Act 1976. Based on several studies, there are several legal issues arises from the SIA approval process, affecting various stakeholders. As such, this research aims to analyse the implementation of SIA from the Malaysia’s policy and legal perspective using qualitative method of systematic literature review and content analysis. Analysis of literatures show that the SIA framework in Malaysia can be improved so as to make the process of SIA approval more effective.
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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 | 0.049 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.005 | 0.009 |
| Scholarly communication | 0.011 | 0.013 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".