THE RACIAL OPTION IN MODERN JEWISH THOUGHT: THE CASE OF THE HUNGARIAN JEWS
Bibliographic record
Abstract
The paper focuses on the influence of the modern ideologies of nationalism and race on the formation of Jewish identity within Central European Judaism at the turn of the twentieth century. I examine the attempts of Neolog Hungarian Jews to re-invent themselves in the racially infused language of Hungarian society by histories of the Orient that demonstrated a racial compatibility. The article argues that in order to provide a foundation for their acceptance into Hungarian society Neolog Hungarian Jews engaged in Oriental Studies to argue that a separate Jewish race did not exist. The paper analyses the writings of Neolog intellectuals, based on archival materials, such as correspondence, rare documents, and journal articles from the Országos Szécsényi Library and the Magyar Tudományos Akadémia Library in Budapest, Hungary (which have been translated into English for the first time). Jewish race theories based on Orientalism are particular to Hungary but were not discussed because the experience of Jews in Vienna and Prague was considered to be the norm throughout the Austro-Hungarian Empire. In order to have a fuller exposure to the Central European Jewish experience of the past we need to address the distinct Hungarian Jewish situation. This paper attempts to fill this void.
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 | 0.004 | 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 | 0.017 | 0.033 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| 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".