Bibliographic record
Abstract
Abstract The prevalent view that Muḥammad Amīn al-Astarabādī (d. 1036/1626-7) studied with a prominent uṣūlī (rationalist) jurist, namely, Shaykh Ḥasan Ṣāḥib al-Maʿālim (d. 1011/1602), the son of al-Shahīd al-Thānī (d. 965/1558), and that he was a mujtahid for most of his life before he converted to akhbārism (traditionism) in Mecca, is largely unfounded. This view surfaced during the late nineteenth century, through Muḥammad Bāqir al-Khwānsārī’s Rawḍāt al-Jannāt, and was uncritically integrated into the major bio-bibliographical accounts on al-Astarabādī’s life and scholarship afterwards. Many modern scholars in turn adopted this view, producing inadequate conclusions about the nature of his akhbārī movement. Based on a close assessment of al-Astarabādī’s extant works and his references to his teachers and places where he studied, Shiraz rather than Mecca was decisive in shaping his early traditionist stance in Shīʿa kalām (rational theology), which resonated with his traditionist positions in jurisprudence and ḥadīth. As far as one can tell through his ijāzās (scholarly licenses), he sought to transmit ḥadīth from one mujtahid, namely, Shaykh Muḥammad Ṣāḥib al-Madārik (d. 1009/1600), but did not receive training in ijtihād (rational legal inference) with him. He appears to have been well-versed in the methods used by ūṣūlī jurists to evaluate ḥadīth and derive the law, prior to that time, through his studies in Shiraz. All these findings, lead us to question the background and nature of his akhbārī thought as they were presented in much of the secondary literature, and to bring attention to a distinct set of intellectual and sociopolitical forces that shaped it.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
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".