Development of public participation framework for environmental impact assessment
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Public participation is essential in an environmental impact assessment (EIA) that protects and manages the environment. Current studies have shown that the application of effective public participation remains scant, especially in Malaysia. This paper aims to develop a framework for public participation in the EIA process using partial least squares (PLS). A comparative study was conducted on public participation in EIA administered in New Zealand, Canada, Hong Kong and Malaysia. Quantitative data were collected via questionnaire surveys. Analyses were administered using PLS-SEM. Three constructs form the framework: the inadequacies of the requirements for, and legislation on, public participation in EIA; barriers to public participation in EIA; and recommendations to further improve public participation in EIA. The development of the framework is expected to improve the current application of public participation in the EIA process. The framework provided in this research contributes to the further improvement of public participation in EIA.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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 it