MétaCan
Menu
Back to cohort
Record W4394999160 · doi:10.1163/19585705-12341482

Mullā Ḳābıż & the Question of Prophetic Superiority

2024· article· en· W4394999160 on OpenAlexaff
Noah H. Taj

Bibliographic record

VenueStudia Islamica · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicIslamic Studies and History
Canadian institutionsCarleton University
Fundersnot available
KeywordsPhilosophyKey (lock)IslamEmpireEpistemologyClassicsTheologyHistoryLawPolitical scienceComputer science

Abstract

fetched live from OpenAlex

Abstract Ibn Kamāl Pāshā (d. 940/1534) played a key role in defending key doctrinal positions in his capacity as Ottoman Shaykh al-Islām, the most famous of which is undoubtedly his refutation of Mullā Qābiḍ (d. 933/1527). Qābiḍ (tr. Kabız), whose credentials are as unknown as Ibn Kamāl’s are known, is said to have propagated the superiority of Jesus over Muhammad, an obscure notion rarely found in the intellectual history of Islam. His ideas were eventually brought to the attention of scholarly circles, leading to him being tried before the Imperial Council by Caliph Suleymān I (d. 973/1566). Noting the inability of some scholars to defend the orthodox position regarding the superiority of Muhammad, Suleymān I called upon Ibn Kamāl to provide a robust defence on behalf of the Empire. Although unable to respond to Ibn Kamāl’s reasoning, Qābiḍ nevertheless maintained his position and thus sealed his fate for good. Only a handful of studies have been carried out on Qābiḍ. This article intends to contribute to the discussion he and his trial have sparked by translating a key epistle written by Ibn Kamāl after the trial and entitled: Risāla fī ʾAfḍaliyyat Muḥammad . Knowing that the details of the controversy between him and Mullā Qābiḍ escape us, this treatise by Ibn Kamāl gives an insight into his thinking on prophetology and his implementation of scriptural, canonical and exegetical sources. It also provides a convenient overview of the exchange he probably had with Qābiḍ.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.962
Threshold uncertainty score0.531

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.022
GPT teacher head0.320
Teacher spread0.298 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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

Citations1
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueStudia IslamicaSame topicIslamic Studies and HistoryFrench-language works237,207