Combating Rising Energy Poverty with Sunnah-Compliant Orthodox Sukuk Finance
Bibliographic record
Abstract
There is a growing number of published peer-reviewed articles, government reports and investigations from civil societies reporting the poor performance of Public Private Partnerships (PPP)-provided utilities services. The purpose of this desk study is to explore the unreported connection between the source of financing for Public Private Partnerships (PPP) projects in the energy sector and the growing energy poverty across the globe. Energy poverty has become a growing threat to households in both developing and developed countries. Studies have shown that energy poverty results in poor health outcomes, discomfort, and poor economic and intellectual development. The causes of energy poverty have been attributed to rising energy prices, stagnated household incomes and poorly energy-efficient buildings. In response, there are growing calls in many countries for the re-nationalisation of energy companies. However, there is a dearth of studies exploring the connection between conventional interest-based debt finance used in financing PPPs which require tariffs to be designed to achieve cost recovery and overcome the growing energy poverty. Our intention is to show that beyond the private vs. public provision debate, there exists an unexplored third approach that mainstream experts seem to ignore or are oblivious about. We argue that the highly leveraged interest-based financing model currently used by PPP sponsors exacerbates energy poverty because of interest costs built into consumer tariffs. We argue that adopting orthodox non-interest equity-based sukuks as a medium of financing for energy PPPs will lead to a reduction in energy tariffs, and will enhance affordability, sustainability, value-for-money and reduce energy poverty. The emphasis on orthodoxy is derived from the fact that most of the current sukuks in the market violate the core concept of Islamic finance by promising a fixed return to investors.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".