Bibliographic record
Abstract
Abstract The aim of this chapter is to present the phenomenological notion of perceptual norms at work in the philosophy of Edmund Husserl. After having shown how his conception of intentionality departs from Brentano’s, the chapter zeroes in on his accounts of perception, illusion, and hallucination, and demonstrates the central role of coherence (Section 1.1) and optimality (Section 1.2), which are the two basic perceptual norms Husserl works with, in his phenomenological descriptions of these phenomena. The main argument of the chapter is that perception is best understood as conforming to norms of regular perceptual experiencing, whereas illusions and hallucinations are conceived as experiences of deviation therefrom (Section 1.3). Independently of the metaphysical implications one can draw from these claims (Section 1.4), the chapter argues that concordance and optimality have a constitutive function in Husserl’s framework: they constitute what perceptions, illusions, and hallucinations are.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.015 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".