Barriers to Practice of Non-Hazardous Solid Waste Minimization by Industries in Malaysia
Bibliographic record
Abstract
The Practice of waste minimization plays a significant role in sustainable development as the most acceptable method in the waste management hierarchy. This paper is a case study research on industrial non-hazardous wastes generated from different industrial activities in one of the major Malaysian industrial areas. This study is aimed at identifying the barriers of waste minimization practices in Malaysian industries. The combination of quantitative and qualitative methods were applied in the study through the use of a structured questionnaire prepared on Likert scale and semi-structured interviews with respondents across thirty (30) factories. Data collected through the questionnaire was analyzed using software and severity index tool. Findings reveal the barriers faced in practicing waste minimization by industries include the lack of time for separation of waste, absence of guidelines, regulations and limited accurate knowledge with severity index range of 62.5<=SI< 87.5, which were considered to be serious issues. Through the application of suitable educational and awareness programs for industrial stakeholders, an effective waste minimization practice can be achieved.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".