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Record W2809353388 · doi:10.1163/24682470-12340021

Alamūt, Ismailism and Khwāja Qāsim Tushtarī’s Recognizing God

2018· article· en· W2809353388 on OpenAlexaff
Shafique N. Virani

Bibliographic record

VenueShii Studies Review · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicIslamic Studies and History
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsExtant taxonScholarshipEleventhHistoryPeriod (music)State (computer science)LiteraturePoetryComposition (language)PhilosophyClassicsArtPolitical scienceAestheticsLawComputer science

Abstract

fetched live from OpenAlex

Abstract Drawing extensively on the testimony of the Persian historians of the seventh-eighth hijri centuries (corresponding to the thirteen-fourteenth centuries of the Christian era), this article sketches a detailed picture of several personalities involved in founding the nascent Ismaili state centred at Alamūt in the fifth/eleventh century. This background sets the stage for analyzing a new manuscript source documenting Ismaili history and thought of this period, Khwāja Qāsim Tushtarī’s Recognizing God ( Maʿrifat-i Khudāy taʿālā ). After outlining and amending previous scholarship on this author and surveying the text’s extant manuscript and lithographic sources, the article analyzes the historical references, focusing on the figure of Sharaf al-Dīn Muḥammad, and examining the evolution of the Ismaili leadership structure. It argues for a likely date of composition between 525/1131 and 533/1139, making Tushtarī’s Recognizing God one of the oldest Ismaili texts from Alamūt still in existence.

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
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.479
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
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.105
GPT teacher head0.392
Teacher spread0.287 · 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; a candidate call from one teacher head, not a consensus.

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

Citations5
Published2018
Admission routes1
Has abstractyes

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