Jalāl al-Dīn al-Dawānī (d. 908/1502), Glosses on ʿAlāʾ al-Dīn al-Qūshjī’s Commentary on Naṣīr al-Dīn al-Ṭūsī’s
Bibliographic record
Abstract
Jalāl al-Dīn al-Dawānī (d. 908/1502), a distinguished scholar of Shiraz in the late fifteenth century, composed many works in logic, theology, philosophy, and ethics. Moreover, he had several written and oral disputes with another outstanding scholar of Shiraz, Ṣadr al-Dīn al-Dashtakī (d. 903/1498). These heated debates, which stretched over a period of more than two decades, significantly influenced Dawānī’s and his intellectual competitor’s thought. It also became widely disputed for centuries throughout the Islamic world—in Iran, the Ottoman lands, central Asia, and the Indian subcontinent. The controversy between Dawānī and Dashtakī animates a number of their respective writings, especially their glosses on ʿAlāʾ al-Dīn al-Qūshjī’s commentary on Naṣīr al-Dīn al-Ṭūsī’s Tajrīd al-iʿtiqād. This chapter focuses on major metaphysical disputes presented in these glosses.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 0.006 |
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".