Europe's Darker Legacies; Notes on Mirror Reflections, the Constitution as Fetish, and Other Such Linkages between the Past and the Future Darker Legacies of Law in Europe; The Shadow of National Socialism and Fascism over Europe and Its Legal Traditions Edited, by Christian Joerges and Navraj Singh Ghaleigh (eds); European Constitutionalism beyond the State, by J. H. H. Weiler and Marlene Wind (eds)
Bibliographic record
Abstract
Europe's Darker Legacies; Notes on Mirror Reflections, the Europe's Darker Legacies; Notes on Mirror Reflections, the Constitution as Fetish, and Other Such Linkages between the Past Constitution as Fetish, and Other Such Linkages between the Past Europe's Darker Legacies; Notes on Mirror Reflections, the Constitution as Fetish, Europe's Darker Legacies; Notes on Mirror Reflections, the Constitution as Fetish, and Other Such Linkages between the Past and the Future Darker Legacies of and Other Such Linkages between the Past and the Future Darker Legacies of Law in Europe; The Shadow of National Socialism and Fascism over Europe and Law in Europe; The Shadow of National Socialism and Fascism over Europe and Its Legal Traditions Edited, by Christian Joerges and Navraj Singh Ghaleigh (eds); Its Legal Traditions Edited, by Christian Joerges and Navraj Singh Ghaleigh (eds); European Constitutionalism beyond the State, by J. H. H. Weiler and Marlene European Constitutionalism beyond the State, by J. H. H.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.015 |
| Scholarly communication | 0.013 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".