Bibliographic record
Abstract
I am grateful to the organisers of this symposium and particularly to the authors for their reflections on our book, European Constitutional Imaginaries: Between Ideology and Utopia. This is a very special occasion to have our ideas discussed by the new generation of scholars, who have started their academic careers 'on the hills of Fiesole?' where much of what we discuss today was born a few decades ago. It is therefore somewhat touching to read their personal reflections on their paths to academia, and what it is to be a European constitutional scholar today. I deeply appreciated Maciej Krogel's observation that our book has the 'ambition' to understand what has happened to the very capacity of imagining and narrating the constitutional tales in Europe. And I was saddened by his admirably honest observation about the very place he came to become a scholar.
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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 | 0.028 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.011 | 0.055 |
| Scholarly communication | 0.027 | 0.022 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.008 | 0.007 |
| 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".