From conquest to co-existence: Burhān al-Dīn al-Marghīnānī’s (d. 593/1197) re-interpretation of jihād
Bibliographic record
Abstract
Abstract Current scholarship on the legal doctrine of jihād presents classical Sunni jurists after the second/eighth century as uniformly championing continual imperial conquest. In this article, I suggest that this sweeping claim for a uniform doctrine neglects what is distinctive in the argumentation of individual juristic thinkers. I trace the genealogy of of Burhān al-Dīn al-Marghīnānī’s (d. 593/1197) theory of jihād in order to show how he radically reinterpreted the doctrine of Ḥanafī school. He introduced the novel approach that jihād need not to be equated with its outward, formal meaning (al-jihād ṣūratan) of military combat. Rather, beyond that outward sense, jihād also had a deeper meaning (al-jihād maʿnan) based on its purpose or function within international relations. For Marghīnānī, part of this function was the preservation of life, freedom, and property. He was thus able to argue that, so long as they secured these ends, peace treaties fulfilled the deeper meaning of jihad. Marghīnānī’s ideas enabled a shift in Ḥanafī thought whereby jurists after him associated jihād with the realization of benefit (maṣlaḥa) for Muslim society. Rather than advocate the obligation of continual conquest, these jurists accepted that decision-making about war and peace should be determined by pragmatic considerations of social interest.
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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 | 0.003 | 0.003 |
| 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 | 0.020 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.007 |
| 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".