Bibliographic record
Abstract
This article considers the reception and genre of the Shāhnāmah in India. It takes as its starting-point comments made by the poet Mirza Asad Allah Khan Ghalib in 1866, moving on to look at a Mughal Shāhnāmah adaptation, the Tarikh-i dil-gusha-i Shamsher-Khani, and its Urdu translations, as well as other Persian, Urdu and Arabic texts. It investigates the (mis)identification of the Shāhnāmah’s genre, looking at cases in which it was understood as historiographical rather than as a romance, and seeking an explanation for this ‘contamination’ of the sincere genre of history by the mendacious romance genre. A methodological split in the historiographical corpus is proposed, between a rationalist (‘ aqli) and transmission-based ( naqli) method. The contest between these two methods is considered, and the prevalence of transmission-based history and its similarity to romance is brought forward as a possible reason for the porousness of the border between these ostensibly opposing genres.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 teacher head, 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".