AVICENNA AND THE PROBLEM OF INDIVIDUATION VALORIZING THE INDIVIDUALS
Bibliographic record
Abstract
Abstract This study tries to shed further light on Avicenna’s (d. 1037) philosophical and linguistic innovations as suggested in his various accounts of the problem of individuation. To better contextualize his discussions, a background is given from both Porphyry’s (d. 305) Isagoge and Fārābī’s (d. 950) remarks in his Isāġūǧī . I have also enumerated all the candidates for the principle of individuation in Avicenna’s œuvre. It is argued in this paper that the pre-Avicennian Peripatetic tradition hardly engaged, both epistemologically and ontologically, with individual per se as having its own unique identity. Instead, individual was ontologically treated as instantiation of universals and epistemologically it was inquired about to the extent that it could be only told apart. Introducing the notion of individuation as tašaḫḫuṣ , instead of the traditional individuation as tamayyuz , Avicenna offers a new way of looking at intra-species differences for a more complex understanding of the individual per se . According to this view, individual with its unique šaḫṣiyya must be understood on its own through sense perception. This approach appears to propose that the individual should not be deemed as subordinate to Aristotelian universals whose assemblage, in Peripatetic thought, was vainly expected to lead to the knowledge and definition of the individual.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.028 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".