Avicenna on Equivocity and Modulation: A Reconsideration of the asmāʾ mushakkika (and tashkīk al-wujūd)
Bibliographic record
Abstract
Abstract This study investigates Avicenna’s conception of philosophical terminology through an analysis of the relation between equivocity ( ishtirāk ) and modulation ( tashkīk ) and by drawing evidence from a broad array of logical, physical, and metaphysical texts. In so doing, it also re-examines the notion of the modulation of existence ( tashkīk al-wujūd ). Although the intrinsic definitional ambiguity of tashkīk makes it possible to approach it alternatively through the lens of univocity and equivocity, there are strong textual and philosophical reasons to believe that Avicenna preferred to regard tashkīk as a kind of moderate equivocity, as opposed to both univocity and a kind of pure or absolute equivocity. As a corollary, it is preferable to construe tashkīk al-wujūd as a “modulated equivocity of being” rather than as a “modulated univocity of being.” On the one hand, this underscores the continuity with Aristotle’s theory of pros hen predication and its late-antique Greek and early Arabic reception, which Avicenna, as heir to a long commentatorial tradition, reinterprets in his own way. On the other hand, the reading of the asmāʾ mushakkika and tashkīk al-wujūd proposed here may explain some of the origins of the ontological debates on the construal of existence that developed from the post-classical reception of Avicenna’s works.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.020 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".