Emily Gottreich.<i>The Mellah of Marrakesh: Jewish and Muslim Space in Morocco's Red City</i>.:The Mellah of Marrakesh: Jewish and Muslim Space in Morocco's Red City.<i>(Indiana Series in Middle East Studies.)</i>
Bibliographic record
Abstract
The Jewish Quarter of Marrakesh, known as the mellah, was founded around 1557 under the Sa'dian dynasty (1511–1659), following the first walled and gated Jewish quarter in Fez (1438) and preceding the mellah in Meknes (1679). In the nineteenth century similar neighborhoods were established in other Moroccan cities. While Jewish neighborhoods and streets are found throughout the Middle East, to my knowledge these are the only such quarters mandated and regulated by an Islamic state. From wide reading and from Moroccan, French, British, and Jewish community archives, Emily Gottreich has recreated the geographic, demographic, economic, political, and social situations of Moroccan Jews. Why were mellahs founded and what does their existence tell us about the place of Jews in Moroccan society? The answer in this solidly researched, vividly descriptive, and deeply understanding book, does not conform to conventional expectations. First, the mellah was not an expression of Muslim ideologies. The first three Moroccan mellahs were founded by new dynasties who showed their Muslim credentials by segregating Muslims from foreign influences and by asserting authority over the dhimmis (non-Muslim subjects in a state governed by Sharia law). Adjacent to the kasbah, or royal city, the mellah of Marrakesh also facilitated taxation and control.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.004 |
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".