Tafsir Application in the Customs and Rules and Social Behavior of the Various Society
Bibliographic record
Abstract
This paper is a description of one of the essential methods used in Qur’anic exegetics: the thematic tafsir method. The authors give a definition of thematic tafsir, trace the history of the origin and development of this method, and also highlight the most critical areas of application of the thematic tafsir. Besides, the paper describes the thematic tafsir as a sensual and rational experience of a believing interpreter of the Qur'an, describes the motivations of a person who decided to resort to this method. The rationale for the thematic tafsir method is also given in terms of Islamic doctrine. In addition, the authors distinguish and describe the three main sections of the thematic tafsir: tafsir of the Qur’anic terms, tafsir of the Qur’anic themes, tafsir of the Qur’anic suras. The authors also write about the developing and expanding areas of application of the thematic tafsir method. Attention is paid to the linguistic direction of the thematic tafsir. The paper also indicates the leading Islamic ulama theologians who successfully apply the method under consideration used in the research. In addition, the contribution to the thematic tafsir of the French scientist Jules La Bohm is emphasized. Among the most popular topics for thematic tafsir, the authors distinguish the following: peace, science, nation, justice, hypocrisy. In conclusion, the authors emphasize the importance of the thematic tafsir for secular and Islamic science and the Islamic community.
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 | 0.008 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.030 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| 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".