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Record W4385582738 · doi:10.1163/1878464x-01401006

A Corpus of Illuminated Qurʾāns from Coastal East Africa

2023· article· en· W4385582738 on OpenAlexaff
Zulfikar A. Hirji

Bibliographic record

VenueJournal of Islamic Manuscripts · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicAfrican history and culture analysis
Canadian institutionsYork University
Fundersnot available
KeywordsSwahiliArchipelagoArabicIslamScholarshipTanzaniaMateriality (auditing)GeographyHistoryAncient historyArchaeologyEthnologyArtLinguisticsPolitical scienceLaw

Abstract

fetched live from OpenAlex

Abstract This article examines a little-known corpus of illuminated Qurʾān manuscripts that were produced between ca. 1750–ca. 1850 in the Swahili city-states of Pate, Siyu, and Faza on Pate Island in the Lamu archipelago (Kenya). Now dispersed in collections in Kenya, Tanzania, Oman, the UK, and the USA, the manuscripts have many distinctive features: decorative frontispieces, sūra titles, basmalas, and division and prostration markers; locally developed Arabic script styles; colophons containing names of copyists and completion dates; endowment dedications; northern Italian-made paper; and, blind-stamped, leather covers. The list of known manuscripts presented in the appendix is aimed at encouraging the identification, digitization, and study of other manuscripts in the corpus. The study of their content, materiality, and contexts of production can advance scholarship on the histories of Islamic manuscript production in coastal East Africa and provide comparative material for manuscript studies in other regions of Eastern Africa and the Indian Ocean.

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)0.002
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0090.016
Science and technology studies0.0070.004
Scholarly communication0.0050.002
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.037
GPT teacher head0.258
Teacher spread0.222 · 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 designObservational
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

Citations2
Published2023
Admission routes1
Has abstractyes

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