Between acculturation and self-assertion: individualisation in the German-Jewish context of the German Empire and the Weimar Republic and its contribution to the development of modern sociology
Bibliographic record
Abstract
Using the example of four German-Jewish scholars of the 19th and 20th centuries – Moritz Lazarus (1824–1903), Hermann Cohen (1842–1918), Georg Simmel (1858–1918) and Alfred Schütz (1899–1959), who all maintained intense connections to their Jewish backgrounds – this article aims to illustrate that Jewish traditions held favourable conditions for processes of religious and social individualisation. The focus of the analysis is placed on the figure of the stranger, a theme all four authors dealt with in their work. On the one hand they investigated the stranger as a biblical figure with social-ethical implications (Lazarus and Cohen); on the other, they developed a sociological approach by analysing the role of the stranger in the construction of society (Schütz and Simmel). This article strives to illustrate how a particular religious ideal – the commandment of love for one's neighbour and the recognition of the stranger as a fellowman – has been transformed into a sociological concept for the promotion of individuality. Reconstructing this context also means exploring the history of sociology as a scientific discipline in Germany and to look into the attempts of sociologists to understand otherness in the multicultural societies of the 21st century.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.039 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".