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Record W4285457376 · doi:10.22373/ijihc.v2i1.793

REVISITING A FRAGMENT OF THE EARLY HISTORY OF ISLAM: THE MYTH OF THE ORDER TO ASSASSINATE ENEMIES BY THE PROPHET

2021· article· en· W4285457376 on OpenAlexaff
Javad Fakhkhar Toosi

Bibliographic record

VenueIndonesian Journal of Islamic History and Culture · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Islamic Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsIslamTerrorismOrder (exchange)History of IslamLawMythologyHistorySociologyPhilosophyPolitical scienceClassicsTheology

Abstract

fetched live from OpenAlex

This article studies a part of early Islam's history that seems ambiguous due to some reports. According to these reports, Prophet Muhammad issued decrees ordering of his opponents and enemies' assassination. The qualitative method has been used in the article. The article shows that there are only 4 cases that appear to have been terrorist operations. Another achievement of the article is that among these 4 cases, only one seems to be valid, and the other three are all rejected because of their chain of narrators. Also, these 4 cases, have all occurred on the battlefield and warzone, and none are indicative of terrorist operations. The article also argues that in the life-history studies of the Prophet, the basic principles and general teachings of the Prophet must be our foundations. The article refers to a general principle in the teachings of the Prophet, according to which He proclaimed that a Muslim must never assassinate. In conclusion, neither the authenticity of the reports, nor their texts are acceptable; they are contrary to the general policy of Islam in the fight against terrorism. The article suggests that the general principles and central teachings of the Prophet should be of interest to researchers in the study of early Islam history, which sometimes contain inconsistent and ambiguous reports.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.599
Threshold uncertainty score0.341

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.013
GPT teacher head0.244
Teacher spread0.231 · 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 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
Published2021
Admission routes1
Has abstractyes

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