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Record W2120665871 · doi:10.1177/0008429813496101

The Shi‘ite Law of Migration

2013· article· en· W2120665871 on OpenAlexaffvenue
Linda Darwish

Bibliographic record

VenueStudies in Religion/Sciences Religieuses · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicIslamic Studies and History
Canadian institutionsSt. Francis Xavier University
Fundersnot available
KeywordsIslamShariaPeriod (music)Identity (music)Formative assessmentSubject (documents)PhenomenonState (computer science)SociologyPolitical scienceLawHistoryEpistemologyAestheticsPhilosophy

Abstract

fetched live from OpenAlex

This study surveys rulings on the subject of migration issued by Imami Shi‘ite legal scholars from the formative 10th – 14th centuries to contemporary times. Prefacing this survey with an examination of hijrah (migration) in the Qur’an and early Imami traditions, the study opens up reflection on an area of Islamic legal discourse that is largely ignored in the literature on Islam in the West. In examining the legal discourse on migration as an historical phenomenon central to the early construction of Muslim identity and not simply as an ad hoc response to modern contingencies, we are able to situate the rulings of traditional modern legal scholars within a long-standing discursive framework. The study demonstrates that while early jurists constructed a rationale for migration to Muslim-held territory that served the interests of the community or state and religion, jurists of the modern period re-employ the same theoretical models while adjusting them to respond to the historical circumstances of cultural and religious globalization.

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)0.001
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: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.004
Scholarly communication0.0020.002
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.056
GPT teacher head0.368
Teacher spread0.312 · 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

Citations2
Published2013
Admission routes2
Has abstractyes

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