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Record W4391964011 · doi:10.58513/arabist.2008.28-29.2

Ascending to Heaven: Fourteenth-century Illustrations of the Prophet’s miʽrāǧ

2008· article· en· W4391964011 on OpenAlexfundno aff
Sheila S. Blair

Bibliographic record

VenueThe Arabist Budapest Studies in Arabic · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicHistorical and Linguistic Studies
Canadian institutionsnot available
FundersYork UniversityHarvard UniversityUniversity of Pennsylvania
KeywordsHeavenArtHistoryPhilosophyAncient historyLiterature

Abstract

fetched live from OpenAlex

Scenes illustrating the Prophet’s ascension to heaven, are some of the most glorious in Persian painting. Single scenes illustrating the subject are found in various types of literature, ranging from such Persian classics as Nizami’s Hamsa to popular devotional works about the Prophet’s life such as the Qisas al-anbiya’ (Tales of the Prophet) and biographies of his life such as the Siyar an-nabi. In all these cases, the ascension is merely one of many illustrations, but in addition there were at least two illustrated manuscripts devoted entirely to the subject of the Prophet’s ascension. Called Book of Ascension, these works have multiple paintings illustrating several incidents of the journey. The more famous of the two manuscripts, transcribed in Uighur script, was made in the Timurid period. The other illustrated manuscript was made a century earlier under the Ilkhanids, Mongol rulers of Iran from 1256 to 1353. This essay surveys the illustrations from the Ilkhanid copy and shows how the topic of the Prophet’s ascension to Heaven developed in the fourteenth century from a single incident in the Prophet’s life to an independent hagiography with multiple, large illustrations that served as models for the next several centuries.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.003
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0100.002

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 head0.148
GPT teacher head0.375
Teacher spread0.227 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations0
Published2008
Admission routes1
Has abstractyes

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