Bibliographic record
Abstract
Abstract In the philosophical literature, it is customary to think of perception as being assessable with respect to epistemic norms. For example, the whole discussion around disjunctivism, which is now often considered to be the dominant, if not the default, position in philosophy of perception, is framed and motivated by epistemological concerns about truth and falsity. This book argues that perception is normative in another, more fundamental, sense. Perception is governed by norms that I call perceptual, that is, immanent to its own structure. This does not mean that perceptual norms are cut off from external facts; rather, it means that they are constitutive moments of our experience of these facts. Perceptual norms are constitutive or enabling norms in that they establish what perception is. To articulate this, the book draws on the repertoire of the phenomenological tradition, in the work of Edmund Husserl and Maurice Merleau-Ponty in particular. For both phenomenologists, perception obtains when it unfolds concordantly or coherently, and when the perceptual progression corresponds to one’s goal or interest, perception can also be said to be optimal. From the phenomenological point of view, concordance and optimality are the basic perceptual norms governing perceptual experience, and the book clarifies their meaning and addresses the philosophical consequences that follow. The first two chapters outline Husserl’s and Merleau-Ponty’s account of perception, illusions, and hallucinations. The following five chapters put the author’s theory to test in the broader philosophical landscape by engaging in five ongoing debates in philosophy of mind and perception.
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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 | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.049 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| 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".