Women and education in the pre-modern Middle East : reconstructing the lives of two female jurists (faqÄ«hÄt)
Bibliographic record
Abstract
This thesis explores the education of women in the pre-modern Middle East, particularly in legal matters. The goal of the work is to show that women in the pre-modern Middle East not only had access to education but were also learned in jurisprudence (fiqh). The work begins with a detailed discussion of the pre-modern system of learning. The first chapter explores not only the educational institutions and methods of instruction, but also the avenues and opportunities for education available to and utilized by women. The second chapter concentrates on the lives of two female jurists (faqihat). The purpose of this chapter is to explore in detail the methods by which these women acquired a legal education and obtained their status as female jurists. This work is a rudimentary effort at investigating the role of women in the pre-modern system of learning and their access to and acquisition of a legal education.
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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 | 0.000 | 0.000 |
| 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".