Greening Small and Medium-Sized Enterprises: Evaluating Environmental Policy in Vietnam
Bibliographic record
Abstract
Small and Medium-sized Enterprises (SMEs) contribute considerably to the economic and social development of bothViet Namand Ho Chi Minh City (HCMC). But at the same time this sector causes severe environmental problems. Up till now, no systematic review and assessment has been carried out on the City's environmental pollution control programmes towards SMEs. Given that, the research applied the concepts of Political Modernization and developed a suitable environmental policy evaluation methodology in order to analyze three cases of prominent pollution control measures: Relocation of polluting enterprises programme, end-of-pipe treatment solutions and the cleaner production approach.Based on those results and experiences drawn from literature, this research aimed to contribute to the improvement of existing environmental policies towards SMEs in HCMC and the development of new feasible, effective and suitable environmental policies for greening the SME sector.
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How this classification was reachedexpand
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".