Bibliographic record
Abstract
Sense experience, naïvely conceived, is a way of knowing perceptible properties: the colors, sounds, smells, flavors, and textures in our perceptual environment. So conceived, ordinary experience presents the perceiver with the essential nature of a property like Sky Blue or Middle C, such that how the property appears in experience is identical to how it essentially is. In antiquity, as today, it was controversial whether sense experience could meet the conditions for knowledge implicit in this naïve conception. Aristotle was a partisan in this debate, but his position is poorly understood. This dissertation examines how Aristotle’s perceptual psychology responds to ancient challenges to the naïve conception, and so articulates his defense of perceptual knowledge. Aristotle’s defense relies on an ontology of “perceptual qualities”—a core class of perceptible properties—according to which those qualities, despite having a perceiver-independent essence rooted in the physics of causation and affection, nevertheless can be present in experience as they essentially are. Chapter 1 defends this realist and objectivist reading against competing interpretations, which overlook a crucial distinction between perceptual qualities and perceptual objects. Chapter 2 presents Aristotle’s ontology as a physicalism that uncharacteristically allows for perceptual qualities to appear in experience as they essentially are. This ontology informs Aristotle’s account of the psychological conditions under which perceivers actually are presented with the essence of perceptual qualities. The locus of this account is an obscure passage where Aristotle purports to show that the senses “discriminate” perceptual qualities because the senses are “mean states” (An. 2.11, 424a5–7). Chapter 3 develops a comprehensive interpretation of the sensory mean state, which Chapter 4 uses to elucidate Aristotle’s argument for sensory discrimination. Sensory discrimination turns out to be a process in which the essence of a perceptual quality comes to be present in the affection it produces in a perceiver. For Aristotle, this shows that sense perception meets a condition for knowledge that his predecessors, including Plato, thought it could not meet. For in his view, but not in theirs, sense experience shares in both the truth and the essence of the qualities it perceives.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.044 |
| Scholarly communication | 0.009 | 0.014 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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".