Bibliographic record
Abstract
What does this history of Germany and the East, told through the biography of an agrarian economist, tell us about the larger questions of Modern German History? One of the most central of these questions centres upon the transformation of the German Right, from the Bismarckian 1870s to the Hitlerian 1930s. By following a character who was always amongst key conservative groups, but never wholly belonged to any of them, we see perhaps more clearly how it all transpired. In Sering, we encounter many tensions found in the conservatism of the era. His opinion of farmers combined an intractable contradiction: a desire for them to be free yeomen who were simultaneously restricted by the state in what they could do with their farms. This is an excellent illustration of the vexed relationship between German conservatives and the working, or farming, class. A version of “reactionary modernism” can be seen in (a) the Sering who had a deeply agrarian romantic idea of what small plot farmers breathing in fresh air could make of the Fatherland, and (b) the Sering who simultaneously served as a high-ranking member of the Navy League, demanding more money for steelworkers to weld ships in industrial ports, again, for a better Fatherland. The same man who saw endless work to be done within Germany was also in favour of a global colonial empire.
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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 | 0.002 | 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 | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.124 | 0.034 |
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".