Water, Energy, and Rooftops: Integrating Green Roof Systems into Building Policies in the Arab Region
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
Recent research claim that adopting green roof systems in building sectors in the Arab region is becoming necessary because of the current environmental, social, and economical challenges. Some Arab countries have already developed green building rating systems and recognized the importance of green roofs; however, they still do not fully benefit from such systems owing to limited supporting policies and financial incentives. The purpose of this article is to contribute to a better understanding of the potential role of green roof systems in effective planning and moving towards sustainable urban development in the Arab region. We argue that integrating green roof systems within governmental policies and green building strategies would potentially help in saving energy, enhancing water management, and coping with climate change. This paper presents a conceptual framework to help governments in the Arab region to adopt green roofs in their environmental policies. To present this framework; first, we studied the current international policies that adopt green roof systems and practices, then proposed a conceptual framework for adopting green roof systems in the Arab region. Second, we have chosen Cairo, Egypt, and Amman, Jordan from the Arab region to demonstrate the applicability of this framework at city level while considering the national and local context. This demonstration provides a novel perspective for the benefits of green roof systems in energy savings and water management in the Arab region.
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 | 0.001 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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