Micro-Segregation and the Jewish Ghetto: A Comparison of Ethnic Communities in Germany
Bibliographic record
Abstract
Abstract This study introduces the concept of micro-segregation as an alternative to ghettoization in order to understand residential patterns in historical Jewish communities. The process of ghetto formation is associated with the spatial separation of a minority group as a result of racial stigma and poverty. It operates at a large scale and posits that ghetto boundaries will be rigidly policed. By contrast, the process of micro-segregation is associated with the separation of a minority group as a result of marginalized legal status. It operates at a smaller scale and posits that the boundaries of ethnic communities are porous, offering sites of economic value. To assess the conceptual utility of micro-segregation, we apply it to four Jewish communities in the German states before the 20th century. Spatial analysis suggests that the communities varied in their degree of micro-segregation, but consistently offered economic opportunity at the boundaries of Christian and Jewish worlds.
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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 | 0.004 | 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 | 0.002 |
| 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".