Green Sukuk As A Mechanism For Enhancing Green Islamic Finance -An Analytical Study Of The Green Sukuk Market During The Period (2017 - Third Quarter Of 2023)-
Bibliographic record
Abstract
This research aims to identify the green sukuk and their role in green Islamic finance, then highlighting of the green sukuk market, based on the descriptive analytical approach. We concluded that this market has demonstrated remarkable growth, propelled by a rising interest from investors seeking sustainable and eco-friendly financial solutions. Despite a temporary downturn in 2020 and 2021, primarily due to the impacts of the COVID-19 pandemic on financial markets, the market exhibited a robust recovery, evidenced by a substantial uptick in activity from 2022 onwards. This resurgence underlines the pressing need for reforms within Islamic financial, which will further catalyze the advancement of green sukuk. Keywords: Green finance, Islamic finance, green Islamic finance, green sukuk
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How this classification was reachedexpand
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".