Between “Germans” and “Jews” : how individuals navigated the language of categorization in Nazi Germany, 1933–1941.
Bibliographic record
Abstract
This thesis examines requests for exemption submitted by German citizens, whom the Nazi regime categorized as “Jews” or “Mixed breeds,” between 1933 and 1941. The petitioners’ vocabulary developed alongside Nazi propaganda; they adopted the regime’s definitions of categories, increasingly defining themselves and their fellow German citizens in racial terms. This thesis seeks to understand and explain how the Nazis defined and enforced racial categories; how petitioners responded to the imposed categorization through legal means; how they used the Nazis’ racial categories as tools to assure their survival; and how their use of the state’s rhetoric impacted the Nazis’ system of racial categorization. \n \nPetitioners not only attempted to contest the categories imposed upon them, but they were also able to strategically use the state’s rhetoric to their advantage. Their objectives were not to question or transform the system-over which they had no power-but rather to maneuver within its constraints. However, to engage the state in a dialogue, they had to pretend to adhere to the Nazis’ “Aryan” state and work within its logic. In their attempts to circumvent state-led persecution by resisting and negotiating their status using the state’s rhetoric, the petitioners might have contributed to the crystallization of categories and the system of racial classification, and they might have unintentionally enabled the authorities to redefine the population along certain categorical lines. This sheds light on how categories are created and maintained in an interactive process between “top” and “bottom” and how and why state-imposed categories can gain traction on the ground.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.018 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".