Goal Programming Model for Sustainability and Circular Economy Evaluation
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
This study investigates into the sustainability landscape of the United Arab Emirates (UAE) through the Circular Economy (CE) principles, emphasizing four conflicting multi-objectives: economic, environmental, energy, and circularity development. Over recent years, CE has witnessed substantial growth, offering compelling opportunities for sustainable development. This expansion enables businesses and industry sectors to integrate CE into their overarching strategies, positioning it as an appealing alternative for manufacturing companies aiming to enhance performance through optimized resource efficiency. The study quantifies these objectives by maximizing GDP, minimizing GHG emissions, electricity consumption, and waste generation, respectively and optimizing number of employees. Two models are formulated based on these objectives, with the second model incorporating waste recycling. Utilizing a goal programming approach, the models are applied to assess eight economic sectors in the UAE. This research seeks to make a substantial contribution to both researchers and practitioners, enhancing sustainable theory and offering practical guidance for those aiming to promote their enterprise’s sustainable development. The findings emphasize the significance of waste minimization and recycling in attaining the country’s sustainability goals, highlighting their impact on energy conservation and the reduction of greenhouse gas emissions.
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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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