Bibliografia essenziale in Appendice a Emilia Giancotti, "Baruch Spinoza", Mimesis (Spinoziana 40), Milano.
Bibliographic record
Abstract
Collana diretta da Mino Chamla, Roberto Diodato e Vittorio Morfino. Comitato scientifico Etienne Balibar (Université Paris X, Nanterre), Laurent Bove (Université d’Amiens), Riccardo Caporali (Università degli Studi ‘Alma Mater’, Bologna), Marilena Chaui (USP, São Paulo), Giuseppe D’Anna (Università Cattolica del Sacro Cuore, Milano), Filippo Del Lucchese (Alma Mater Studiorum – Università di Bologna), Giorgos Fortunios (Università Panteion, Atene), Augusto Illuminati (Università degli Studi di Urbino), Andrey Maidansky (Belgorod National Research University), Pierre-François Moreau (ENS, Lyon), Chantal Jaquet (Panthéon- Sorbonne, Paris), Warren Montag (Occidental College, Los Angeles), Aurelio Sainz Pezonaga (Universidad de Castilla-La Mancha), Hasana Sharp (McGill University, Montreal), Diego Tatian (Universidad San Martin), Stefano Visentin (Università degli Studi di Urbino), Manfred Walther (Leibniz Universität, Hannover).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.003 |
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 teacher head, 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".