In the Book We have left out Nothing: The Ethical Problem of the Existence of Verse 4:34 in the Qur’an
Bibliographic record
Abstract
Kecia Ali writes in her book Sexual Ethics and Islam that studies on the history and forms of gender injustice in Islam have yet to adequately address concomitant theological challenges concerning the nature of the divine justice and will. In response to this need, I would like to explore the problem posed by the mere existence of verse 4:34, otherwise known as “the beating verse,” in the Qur’an. This article is intended to be a primary theological and ethical response to the problem, rather than a secular academic analysis of historical approaches to the verse. My approach is grounded in the thought of Ibn al-`Arabi (d. 1240), arguably the most influential, systematically comprehensive, and prolific mystic and thinker of medieval Islam. Ibn al-`Arabi’s ontology, ethics, and hermeneutics of the Qur’an provide a useful frame and a possible resolution to the problem.
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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 | 0.002 | 0.004 |
| 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 | 0.015 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 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".