A Framework for Implementation of Eco-Industrial Town (EIT) in Thailand
Bibliographic record
Abstract
Eco-Industrial Town (EIT) is one of the important policies of Thailand since 2011 aiming at developing operations of related parties in the target EITs.With emerging concepts, threats and challenges to Thailand, EIT framework and indicators need to be developed to be able to cope with them.This study aims to develop a framework and indicators for monitoring and evaluating progress of EIT implementation in the target EITs in Thailand.Methodology used in the study are the documentary research, two rounds of questionnaires distributed to 30 experts to gather feedback and recommendations and focus group discussion with 52 stakeholders from 6 target EITs in Thailand to gather feedback and recommendations.The results provided an EIT framework which contains of 6 perspectives, 32 dimensions, and 54 indicators which appropriate to EIT implementation in the Thailand context.Implication of the study is that the EIT framework, indicators and recommendations are useful for the future EITs in Thailand and EITs in other countries where under developing the project by selecting perspectives, dimensions, indicators, and recommendations that appropriate to their context.
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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 | 0.027 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.005 | 0.012 |
| Scholarly communication | 0.013 | 0.011 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".