Perceptual constancy and perceptual representation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Perceptual constancy has played a significant role in philosophy of perception. It figures in debates about direct realism, color ontology, and the minimal conditions for perceptual representation. Despite this, there is no general consensus about what constancy is . I argue that an adequate account of constancy must distinguish it from three distinct phenomena: mere sensory stability through proximal change, perceptual categorization of a distal dimension, and stability through irrelevant proximal change. Standard characterizations of constancy fall short in one or more of these respects. I develop an account of constancy that overcomes these problems. The account has two parts: an analysis of constancy mechanisms, and an analysis of the conditions under which a constancy capacity is exercised. I then employ this account to evaluate whether constancy is a necessary condition for perceptual representation, as some have conjectured. I argue that explanatory practice in perceptual psychology fails to support this view. Rather, it fits better with the weaker principle that representation requires specific tracking of a distal dimension.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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 it