The Discourse on the Praxis and Pragmatics of the Qur’an Retranslations in Turkish
Bibliographic record
Abstract
Retranslations of the Qur’an constitute an intriguing site of research with particular premises governing their production, dissemination and/or reception in Turkey. Its inherently religion-oriented context is accompanied by discussions on the sacred status of the source text, arguments on its untranslatability, translatorial human agency vis-à-vis the Holy creator, acknowledged Arabicity of the source text, etc. In this regard, each new translation of the Qur’an in Turkish is released with a motivation to justify its necessity amid abundant retranslations available in the target repertoire. Various approaches towards the conceptualization and instrumentalization of these Qur’anic translations create a meta-narrative on its own right. This study aims at exploring this particular discourse on the retranslations of the Qur’an with a bi-faceted study design composed of quantitative and qualitative analyses. The quantitative analysis focuses on the numeric changes of Qur’anic retranslations in respective decades, whereas the qualitative analysis concentrates on the statements of the translatorial agents on the motives behind their translational production. By shedding light on the discursive narrative postulated upon these retranslations, it is claimed that social, political, cultural and financial concerns have prevailingly governed the reproductions of this canonical work in Turkey. Keywords: Qur’an translation, religious-text translation, retranslation, discourse analysis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.017 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".