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Record W4410638566 · doi:10.1163/19585705-12341511

Is There a ‘Jury’ in Islamic Law? The Twelve-Witness Lafīfiyya Testimony and the Limits of Judicial Discretion

2025· article· en· W4410638566 on OpenAlexfundno aff
Ari Schriber

Bibliographic record

VenueStudia Islamica · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicLegal Education and Practice Innovations
Canadian institutionsnot available
FundersUniversity of Toronto
KeywordsJuryWitnessLawDiscretionIslamPolitical sciencePhilosophyTheology

Abstract

fetched live from OpenAlex

Abstract Legal historian John Makdisi provocatively argued that the “English jury” may originate in the so-called lafīfiyya : a testimony of twelve ordinary Muslims whose concurring statements are considered probative in Islamic law of the Maghrib. This article examines the juristic conception and judicial application of the lafīfiyya . It first demonstrates how jurists of the Mālikī school ( maḏhab ) of Islamic law elaborated the lafīfiyya as regional “judicial practice” ( ʿamal ) with stipulations that invoked well-established Islamic legal concepts like circumstantial evidence ( qarāʾin ) and quorum ( tawātur ) – concepts contingent on a qāḍī ’s assessment of them. The second part of the paper uses sharīʿa court case records from the first half of twentieth-century Morocco to examine judicial treatment of the lafīfiyya in practice. I argue that qāḍī s varyingly balanced their invocation of social discretion and textual stipulation to ensure that the lafīfiyya remained both socially reliable and doctrinally coherent. I focus especially on discretionary judicial assessment of social and/or logical “implausibility” of lafīfiyya testimonies through three overarching instances: urban vs. rural witnesses, testimonial identification and knowledge, and circumstances of bearing witness. In all cases, I show that Moroccan qāḍī s did not necessarily accept the witnesses’ statements as binding fact as a jury; rather, they preserved the lafīfiyya ’s normative validity by upholding the threshold of logical plausibility. Ultimately, I leverage this discussion to argue for a more contingent understanding of Islamic adjudicative practice inclusive of both textual discourse and social temporality.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.784
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.030
GPT teacher head0.371
Teacher spread0.341 · 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 designTheoretical or conceptual
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
Published2025
Admission routes1
Has abstractyes

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