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Humanistic Qurʼanic Studies of Fazlur Rahman

2020· article· en· W3044875178 on OpenAlexfundno aff
Д. В. Мухетдинов

Bibliographic record

VenueIslam in the modern world · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Islamic Studies
Canadian institutionsnot available
FundersYork UniversityUniversity of Chicago
KeywordsRevelationHistoricity (philosophy)EpistemologyHumanismMeaning (existential)IslamContext (archaeology)Interpretation (philosophy)PhilosophyHermeneuticsArticulation (sociology)Situational ethicsOrder (exchange)SociologyLawTheologyHistoryPolitical sciencePolitics

Abstract

fetched live from OpenAlex

The present article focuses on explaining F. Rahman’s humanist and historical approach to the Quran. Pakistani thinker criticizes the concept of Quran as “uncreated” as it was established in the Islamic world after the rejection of Mu‘tazila. He states that in this view Quran is separated from the actual history and lives of people and thus cannot become the spiritual guidance it is supposed to be. The author demonstrates that F. Rahman continues the Neomodernist tendency in Islam and creatively employs the ideas of his predecessors. In particular, he does not argue with the revelationist idea of the Quran, but he urges to analyze it in context of historical revelation and consider the situational nature of particular physical articulation of ayahs performed by the Prophet. Author also notes that in order to perform a novel interpretation of Quran F. Rahman has to rethink the traditionalist legalistic ordinances for believers as they are set to regulate life only externally. Rahman also criticizes atomistic method, which implies separation of the Quran and its meaning from all the other Quranic ideas, and strives for holistic method in hermeneutics of Quran. Historical critique applied to the Quran by F. Rahman serves to understand it in its historicity, and in doing so clarifies the embodiment of universal ethical concepts in particular instances.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.556
Threshold uncertainty score0.575

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 studies0.0000.000
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 head0.163
GPT teacher head0.402
Teacher spread0.240 · 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 designQualitative
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

Citations3
Published2020
Admission routes1
Has abstractyes

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