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Record W2809166137 · doi:10.1163/24682470-12340018

Was Muḥammad Amīn al-Astarabādī (d. 1036/1626-7) a Mujtahid?

2018· article· en· W2809166137 on OpenAlexaff
Rula Jurdi Abisaab

Bibliographic record

VenueShii Studies Review · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicIslamic Studies and History
Canadian institutionsMcGill University
Fundersnot available
KeywordsExtant taxonScholarshipPhilosophyJurisprudenceTheologyLawPolitical science

Abstract

fetched live from OpenAlex

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-Kh w ānsārī’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 ijāzā s (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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.319
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.002

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.

Opus teacher head0.085
GPT teacher head0.398
Teacher spread0.313 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations0
Published2018
Admission routes1
Has abstractyes

Explore more

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