Islamicity Indices: A Moral Compass for Reform and Effective Institutions
Bibliographic record
Abstract
“Islamicity Indices” are based on the Islamic teachings of the holy Qur’an and the Hadiths. Islam’s foundational teachings are summarized; the rules that follow are deduced; and then the important institutions that these teachings and rules indicate are identified.These rules and institutions are in turn then used to construct indices for measuring the degree of Islamicity—the reflection and manifestation of these teachings in a community or a country.The purpose of “Islamicity Indices” is to provide a compass for fundamental economic, social and legal reforms—a compass that embodies quantifiable goals and targets that can be negotiated, results that can be monitored and assessed and policies that can be modified to achieve the set targets. Importantly, these indices can open up a debate among Muslims about the deeper meaning of their religion and going well beyond its more mechanical requirements andsuch a debate, based on quantified Islamic teachings, cannot be easily dismissed by those in power.When non-Muslim and Muslim countries are compared, the indices indicate that New Zealand, Australia, Canada and the countries of Northern Europe occupy the top ten positions in adopting Islamic rules for their foundation. These are countries that are generally regarded as the most successful socio-economic countries. Thus the problem is not with Islam but with Muslims as they do not uphold the rules, which translate into institutions, recommended in Islam. The results of these indices since 2000 show the failure of most Muslim countries and the urgent need for sustained reform.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".