Introduction: Quarter Past Eleven, One Hundred Days, a Thousand Years
Bibliographic record
Abstract
This introductory chapter begins by describing Adolf Hitler's appointment as Germany's new chancellor on January 30, 1933. This appointment led to the greatest man-made disaster in twentieth-century history: the rise of Hitler, the establishment of the Third Reich, and the Nazis' war on the world. Why the sense of urgency to make a decision on January 30, 1933? And why the apparent sudden shift in national mood in favor of the Nazis in the one hundred days that followed? To begin to answer these questions one must step back in time, first to the crisis of the Great Depression and then further back to the end of World War I and the November Revolution that established the Weimar Republic in 1918. Ultimately, the drama of the first hundred days centers on an apparent seismic shift in public sympathies as Germans became Nazis. To this day, scholars argue about the degrees of deception and self-deception and the scales of desire, opportunism, and coercion that made up the phenomenon of National Socialism.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.150 | 0.065 |
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".