Bibliographic record
Abstract
Marriage A sanctified social and legal institution, marriage ( nikāḥ ) was seen in Islam as the cornerstone of social order and communal harmony, for as an institution it simultaneously regulated sexual, moral and familial relationships. In quasi-legal literature, its goals were said to have been preservation of pedigree and sexual fulfillment for both men and women. Since the only conceivable way of bringing children into this world and of raising them properly was through marriage, and since sexuality was equally inconceivable outside a lawful framework (which included lawful concubinage), the marriage institution thus became key to maintaining social harmony, the cornerstone of the entire Islamic order. Yet, in strictly legal terms, marriage as nikāḥ was a contract with a narrow scope, one that did not pretend to regulate the entirety of relationships that normally existed within marital life. Reduced to its essential contractual components – which make up the entirety of juristic formal discourse – the nikāḥ contract excluded what we might call the elements of companionate marriage (as widely defined), and limited itself to regulating, in strictly contractual ways, only those aspects of the matrimonial institution that pertained to the lease of services. Together with habitual infractions of the law and illicit violence, sexuality outside marriage ( zinā ) is regarded as the primary cause of social discord, to be avoided at virtually any cost.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.012 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.021 | 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".