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Record W3001475165 · doi:10.13169/reorient.5.1.0006

Ordinary Matters in Islamic Studies: Notes from the Field

2019· article· en· W3001475165 on OpenAlexaboutno aff
Setrag Manoukian

Bibliographic record

VenueReOrient · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicIslamic Studies and History
Canadian institutionsnot available
Fundersnot available
KeywordsIslamOrientalismContext (archaeology)EpistemologySociologyEveryday lifeField (mathematics)PoliticsModalitiesAestheticsHistorySocial scienceLiteraturePhilosophyPolitical scienceLawArt

Abstract

fetched live from OpenAlex

This essay is a reflection on the everyday conceptual matters that inform the workings of the academic field of Islamic Studies and constitute its conditions of possibility. The research is based on observations I made while working at the Institute of Islamic Studies at McGill University. The everyday of the Institute is marked by arguments that reject orientalism but also foreshadow its return in different guises. In this context, historical and linguistic approaches, with their own tensions and limits, appear as safeguards, but they are inevitably caught up in a binary that juxtaposes theory to the archive as two opposing but equally necessary modalities of knowledge. While several ideas about what constitutes Islam seem to cohabit without much friction, a quite fixed and stable notion of politics overdetermines the possibility to think otherwise. The essay is primarily descriptive, but it contains a few personal and “extra-territorial” notes on how to inhabit these matters differently and follow desire.

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)0.013
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.025
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.005
Science and technology studies0.0250.061
Scholarly communication0.0130.009
Open science0.0010.008
Research integrity0.0040.007
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 head0.018
GPT teacher head0.306
Teacher spread0.288 · 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 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

Citations0
Published2019
Admission routes1
Has abstractyes

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