Bibliographic record
Abstract
While the textual flow of the Qur'an is notoriously challenging and complex, it is also the case that in the process of reading or listening the centre of narrative gravity is never lost. This powerful focus may be termed the epic journey, a struggle from a state of barbarousness to one of civilisation, from ignorance to enlightenment. The hero of this ‘epic’ is, of course, the prophet or messenger, for whom history, as told in the Qur'an, provides many examples. In this paper we will examine basic, sometimes disputed, features of the epic as they may be recognised in a series of such works (for example, The Odyssey, ‘Gilgamesh’, The Shah-nameh, The Divine Comedy, and Paradise Lost). Such reflection is useful for scholarship in a world where the Qur'an is so obviously a part of the shared, if not always recognised, literary heritage of humanity. Among the subsidiary themes to be tested against the notion of ‘epic’ are: humanity, community, apocalypse, and the path or road. In addition to such thematic questions, other compositional and stylistic features of the epic will be studied: orality, rhetoric, figure, metonymy, metre, rhyme, and voice. Finally, the question of audience and performance will be broached to further delineate similarities and differences amongst various theories of the epic, as they can or cannot be applied to the Qur'an.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.021 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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".