Bibliographic record
Abstract
The term Islamic Finance (IF) can generally be defined as the provision of financial services and products on the principles of Islamic shariah (law). Some basic principles of Islamic Finance are prohibition of riba (interest), gharar (uncertainty), and gambling. Another defining characteristic of Islamic Finance is that it is supposed to link financial transactions with activities in real economy and arrange for sharing of entrepreneurial risk. It is predicted by the International Organization of Securities Commission that by 2015, investments undertaken according to these principles will account for half of the savings of the world’s estimated 1.2-1.6 billion Muslims. Yet, we have very little insight into economic preferences of Muslim populations living in Western societies when it comes to shariah compliant investment opportunities. A 2010 report on Islamic Housing Finance in Canada commissioned by the Canada Mortgage and Housing Company notes that without such information it is impossible to understand how market demand would respond to an ever growing array of Islamic Finance products and services. This paper documents some stylzed facts about housing choices of immigrants in Italy as well as providing some comparison of the UK and the Canadian context. This is intended as a first step in uncovering household preferences for various investment alternatives among Muslim population in selected Western economies.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".