The Experience of Coexistence and Love: A Critical Study of Al-Muqri’s The Handsome Jew
Bibliographic record
Abstract
This study aims at exploring issue of coexistence and love in Yemeni society in the seventeenth century represented in Al- Muqri’s The Handsome Jew by the prominent characters Fatima, a Muslim, and Salem, a Jew. The experience of coexistence is still controversial that has not received enough study in the light of the complexities that are involved in understanding the reasons of violence, social and religious conflicts in order to accept the culture and ideas of the other. The objective of the study is to show how this issue affects Muslim- Jewish women and men in a city that opens its doors for all people. Coexistence theory has often shed light on the language and practice of living together and love stories between Muslim women and Jewish boys and vice versa that stemmed from the social, cultural and religious coexistent in Yemeni society. Al-Muqri’s novel depicts Muslim-Jewish love relation in a way that counters religious and conventional ideas. It is concluded that Ali Al-Muqri addresses the issues of tolerant and peaceful love of human beings that transcends religion, sects and classes. In this sense, he tries hardly to consolidate not only his views, but also all views about the values of cultural, religious and social tolerance and coexistence away from stereotypes, intolerance, racial discrimination and ideological hatred that leave nothing, but destruction to all of humanity.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.041 | 0.034 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".