‘No’ing That You Don’t Know: Ibn Sīnā on Meno’s Paradox and Its Implications for the Sciences
Bibliographic record
Abstract
Abstract In “Avicenna on Meno’s Paradox,” Michael Marmura provides a translation with comments on Ibn Sīnā’s chapter from The Book of Demonstration where Ibn Sīnā resolves Meno’s paradox. Marmura, however, does not consider in detail the chapters leading up to his resolution. There Ibn Sīnā outlines his unique understanding of how to undertake a scientific inquiry, which not only underlies his solution to Meno’s paradox, but also informs his approach throughout his monumental summa of philosophy, the Shifāʾ. The present study considers this broader context for his solution to the paradox and concludes with a case study from Ibn Sīnā’s Physics, where one sees his scientific method in practice.
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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 | 0.011 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.012 | 0.045 |
| Scholarly communication | 0.007 | 0.013 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.006 | 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".