Bibliographic record
Abstract
The present paper studies the argument from the sayings of the companions of the Prophet (ﷺ) in Qur’ānic exegesis in the light of Tafsīr Surah al-Baqarah by al-Qurtubī (1214-1273), a renowned Andalusian Islamic scholar and jurist. It finds that al-Qurtubī argues with the sayings of the Companions in various discussions related to Qur’ānic exegesis. According to the points mentioned with reference to Surah al-Baqarah, al-Qurtubī has explained various unfamiliar Qur’ānic words, the scenario of the revelation of different verses, the rules related to worship, the correct pronunciation of different Qur’ānic words and has resolved different variant readings of the Quran, etc. He has argued from the sayings of the Companions and has made a successful attempt to clarify the correct Islamic position in the relevant issues. This discussion also proves that among the verses whose interpretation is not known from Quran and Ḥadīth, the utmost importance should be given to the sayings of the Companions. If the Companions agree on the interpretation of a verse, then the commentators must adopt it, and it is not permissible to adopt the contrary. However, if there is a difference of opinion among the Companions in the relevant issue, then the opinion of those who are closer to Islamic point of view can be adopted
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.967 | 0.968 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".