Bibliographic record
Abstract
Vittorio Sainati wrote two books and several articles on Aristotle’s logical thought. In this paper I reconstruct Sainati’s intepretation of Aristotle’s logic. I show that Sainati anticipates some of the contributions by Michael Frede and Marko Malink. I focus on two aspects: 1) Sainati’s reconstruction of Aristotle’s doctrine of the categories and 2) Sainati’s claim that it is possible to make sense of Aristotle’s necessity syllogistic if we believe that the necessity operator is used to express the necessity of the per se predications. I show that Sainati’s idea that logical categories are nothing but predications has been further developed by M. Frede in a famous essay. Additionally, I show that Malink’s interpretation of modal syllogistic against the backdrop of Aristotle’s theory of predication echoes Sainati’s contributions. My paper aims at showing the depth of Sainati’s intepretation of Aristotle’s logic.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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; both teacher heads agree on what is shown here.
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".