Waqf Development in Marawi City via Issuance of Perpetual Waqf Sukuk
Bibliographic record
Abstract
Since 2017, the city of Marawi was left in ruins after five months of aerial bombardments and close-quarter fighting between Islamic State of Iraq and al-Sham (ISIS) and government forces. Many buildings were destroyed; mosques and schools are no exceptions. While rebuilding efforts have begun in the city, the government has limited resources to fund city reconstruction and Waqf properties (e.g. mosques and schools) are not constitutionally considered as part of the government assets. Fortunately, the government seeks to channel funding for city reconstruction, including Islamic finance schemes. Therefore, this paper aims to assess the opportunities and challenges to rebuild Waqf properties through the issuance of Sukuk, Islamic bond. This paper adopts a qualitative research approach where secondary sources such as books, journals, articles and websites related to Waqf are reviewed. The paper also examines the successful examples of Sukuk-Waqf as part of the analysis.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".