Some Sunni Ḥadīth on the Qurʾānic Term Kalāla: An Attempt at Historical Reconstruction
Bibliographic record
Abstract
Abstract Since the 1980s the Qurʾānic term kalāla has been studied comprehensively, using Islamic literary sources, by David Powers and Agostino Cilardo. Cilardo, who deploys J. Schacht’s Ḥadīth -analytical criteria to date the kalāla traditions, points to the first half of the 2nd century AH and, occasionally, to the end of the 1st century AH as the period in which most of these traditions were circulated. Powers, who combines the literary evidence with the documentary evidence of BNF 328a, concludes that kalāla traditions evolved during the second half of the first and the first quarter of the second century AH. In the present essay I employ the isnād -cum- matn methodology to date several kalāla traditions discussed by Powers and Cilardo.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".