Bibliographic record
Abstract
Abstract Modern logicians hold that traditional logic makes a serious error by accepting the subalternation thesis , the thesis that universal affirmatives imply matching particular affirmatives. But some traditional logicians (e.g., Al-Fārābī, Abelard, Ockham) presented doctrines of existential import of categorical propositions that include subalternation, and some modern studies of Aristotle’s logic take him to assume one of the doctrines. This article argues that such interpretations have serious problems and proposes a radically different interpretation. On the new interpretation, called the no-import interpretation , Aristotle takes both singular and general categorical propositions (including singular and particular affirmatives) not to have existential import. In proposing and defending this interpretation, the article gives a close examination of two influential interpretations of his views on existential import: (a) the affirmative–negative interpretation , which takes him to hold that affirmative categorical propositions have existential import while negative ones do not, and (b) the non-vacuity interpretation , which takes his system of logic to presuppose or require that empty terms do not figure in general categorical propositions the system deals with. The article argues that Aristotle holds theses about singular and general categorical propositions that conflict with these interpretations, and that examination of the theses leads to the no-import interpretation.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.034 |
| Scholarly communication | 0.005 | 0.012 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".