Impacts of Green Office Projects in Thailand: An Evaluation Consistent with Sustainable Development Goals (SDGs)
Bibliographic record
Abstract
This study aims to evaluate the environmental, economic, and social impacts of a green office project in Thailand, that is consistent with sustainable development goals (SDGs), to analyze and present the result of the study of the environmental, economic, and social impact of green office, and to evaluate satisfaction in the green office project operation. Evaluated the operating steps of green office projects, using new green office evaluation criteria, under Department of Environmental Quality Promotion (DEQP), by collecting preliminary data through questionnaires from 73 agencies, by monitoring and analyzing the project operation of participating organizations to certify as green office standard during 2015 to 2017. Besides, qualitative data were collected through the in-depth interview from 25 representative agencies, selected on the criteria of readiness to provide information and to evaluate their satisfaction in the green office project’s operation. The value of the green office project was 299 million Baht for all participant organizations equal to 1.4 million Baht/office/year. And this could be divided into economic compensation, (262.5 million Baht), social compensation (28.5 million Baht), and environmental compensation (7.55 million Baht). Evaluation of satisfaction found that most agencies (79.45%) have high satisfaction to certification on the evaluation result of national auditors, benefit on staffs’ knowledge, understanding, and observation of the importance of green office operation (86.63%), and the advantage of green office operation in their office (90.41%). The study further suggests that green office projects should be supported as a national policy to all agencies for continuous enhancement or development of the standard, to be an international level according to sustainable development goals (SDGs).
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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 | 0.021 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".