Interfaith Dialogue between Ethics and Necessity – A Study from the Qur’anic Guidelines
Bibliographic record
Abstract
Muslim theology admits on diversity of faiths followed by mankind. The existence of religious diversity is aimed at, among other things, seeking a common ground in disseminating goodness and eradicating evil practices in the community. The study attempts to reveal the guidelines on religious dialogue from the passages of the Qur’an. The Qur’an emphasizes on the importance of communication and dialogue especially with the People of the Book. The Prophetic tradition also indicates on presence of other religious adherents. They are expected to work together in promoting goodness and establishing justice on the basis of divine precepts. Moreover, it highlights the importance of dialogue with different religious groups, as well as the prospect to wipe off misunderstandings that can lead into communal tension and crisis. The study will also shed light on the obstacles faced by religious leaders in conducting the dialogue and to contributing to the promotion of peace and justice. The most important part is that it attempts to expose the ethical guidelines as stated in the Qur’an which could be adopted as principles of dialogue. It is not aimed at condemning other faiths; rather it is aimed at exposing awareness on the differences and similarities which, in the long run, can give chance to restoring misconceptions.
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 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 | 0.012 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.012 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".