Bibliographic record
Abstract
With the emergence of legal theory by the middle of the fourth/tenth century or thereabouts, Islamic law can be said to have become complete, save for one essential and fundamental feature which we have not yet discussed. This is the phenomenon of the legal schools, one of the most defining characteristics of Islamic law. In order to understand this complex phenomenon, it is perhaps best to begin with a survey of the meanings that are associated with the Arabic term “ madhhab ,” customarily translated into the English language as “school.” THE MEANINGS OF MADHHAB Derived from the Arabic verb dhahabal yadhhabu (lit. “went/to go”), the verbal noun madhhab generally means that which is followed and, more specifically, the opinion or idea that one chooses to adopt. It is almost never applied by a jurist to his own opinion, but rather used in the third person, e.g., the madhhab of so-and-so is such-and-such. The most basic meaning of the term is thus a particular opinion of a jurist. Historically, it is of early provenance, probably dating back to the end of the first/seventh century, but certainly to the middle of the second/eighth. By the early third/ninth century, its use had become frequent. The madhhabs and their history, however, are not associated with this basic usage to any meaningful extent, for it is conceivable that the usage might have persisted without there being any schools at all. In fact, it was already in circulation before any developed notion of “school” had come to exist.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.021 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.011 | 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".