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Record W3009429895 · doi:10.1163/22131418-00801001

The Problem of the Islamic State

2020· article· en· W3009429895 on OpenAlexaff
Milad Dokhanchi

Bibliographic record

VenueSociology of Islam · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicIslamic Studies and History
Canadian institutionsQueen's University
Fundersnot available
KeywordsTribePoliticsState (computer science)IslamSociologySecularismPower (physics)ShariaLawPolitical sciencePhilosophyAnthropologyTheology

Abstract

fetched live from OpenAlex

This article proposes a theoretical model that contextualizes areas of contention and may even offer a resolution to a major debate in the Muslim world and the Western academy on the relation between Islam, secularism and the nation-state. Drawing on the works of scholars such as Ibn Khaldun, Kropotkin, Weber, Clastres, Barclay, Deleuze and Guattari, Crone and Foucault, this article theorizes an alternative organizational system to that of State-form. This organization, called Tribe-form, is politically comprehensive in its own accord and contains political rule, conceptions of power and social orders. Tribe-form and State-form are, therefore, names ascribed to two different modes of political governance. This article then explores the striking resonances between the Islamic political canon and Tribe-form and consequently problematizes the existence of something called “state” in the early Muslim political experience. This assertion rejects the secularist position on that Islam is silent on the on the question of politics, yet it radically questions superimposing a medieval political organization based on the model of Tribe onto the modern nation-state. In short, this article affirms the political qualities of sharia, yet it challenges the suitability of sharia to operate effectively as a basis for modern state governance.

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)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.006
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.025
Scholarly communication0.0050.004
Open science0.0010.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0050.001

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 head0.019
GPT teacher head0.265
Teacher spread0.246 · 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 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
Published2020
Admission routes1
Has abstractyes

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