A comparative analysis of Islamic home mortgage models in U.S. and Canada: a case for improvement of the Canadian model
Bibliographic record
Abstract
Shari'a compliant home mortgage replacement products (SCHMRP) are not a choice but compulsion for a large number of Muslims in North America, based on dictates of their faith. An equitable and affordable access to home mortgages necessitates, in their case, access and supply of SCHMRPs at competitive rates. This is a comparative study of two SCHMRP regimes in North America_US and Canada. The study explores the financial regulatory framework, ancillary laws and housing policies and identifies different stages of growth in both jurisdictions. The study reveals a general similarity and accommodation in treatment of SCHMRPs in the financial regulatory regimes of both jurisdictions but significant variation in reinvestment and disclosure laws which indirectly help SCHMRPs in the US attracting a significantly higher level of investments than Canada. Finally, the study makes a host of recommendations both on equitable grounds and economic specificity of the product in transactional cost theory terms ranging from allowing a standalone Islamic Bank to some regulation of the too self-regulated financial sector of Canada with significant transparency concerns related to its mortgage lending sector. The study surveys the North American SCHMRP market and sees evidence of recent progress and future potential in the Canadian market which is on the threshold of a real take off if certain bottlenecks are removed.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".