Bibliographic record
Abstract
Abstract Islamic finance is an alternative source of financing to the conventional financing that emerged via institutionalization in the 1960s. It has gained popularity in the world irrespective of faith convictions due to the universal and ethical principles adhered in the practice of it. In this regard, North America is not an exception. In the United States and Canada, Islamic finance has been adopted, and there is an established regulatory environment for the operation of it with political support. There is also a wide range of innovative Islamic finance products structured and used in this part of the world that is conducive to the demand of the population and regulatory environment of Islamic finance found in the respective jurisdictions. These two countries are often described as competitors in the region, but the reality is despite the competitive relationship they are in by default, they are also collaborators in developing Islamic finance in the region. More than one million self-identified Muslims in Canada represents 3.2 percent of the total Canadian population. In comparison, the Muslim population in the United States represents 0.9 percent of the total population. Hence, Canada has been viewed as more suitable to become the hub of Islamic finance in the region simply because the number of Muslims in Canada is greater than that found in the United States in terms of religious representation in each nation’s total population. Furthermore, in terms of the regulatory environment, though the regulatory landscape applicable to financial institutions including Islamic financial institutions in the United States is much more sophisticated, the lack of a regulatory environment in Canada for Islamic finance is viewed as an opportunity for Canada as this provides flexibility required to develop and innovate unique Islamic finance products and increase the number of institutions dealing with Islamic finance. Sharia governance is the backbone of the Islamic finance industry in any jurisdiction. A common weakness found in both countries in the development of Islamic finance is on adopting a uniform Sharia governance framework applicable to all institutions offering Islamic finance products and services. In the early 21st century, the practice of Islamic financial institutions in the region indicates that there is no uniform yardstick to adopt in this regard, leading to confusion as well as lack of confidence—not only among “laypeople” but among Sharia scholars as well—in the Sharia-compliant products offered. In the absence of regulatory backing in this regard, an agreement among the industry stakeholders in the region would be sufficient to standardize this practice and implement procedural requirements that ought to be followed in offering Sharia-compliant products and services.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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".