Emmert's Law in the Dark: Active and Passive Proprioceptive Effects on Positive Visual Afterimages
Bibliographic record
Abstract
The relationship between apparent size and apparent distance is given by Emmert's law, which states that a retinal image is proportional in size to the distance of the surface it is projected upon. This principle also applies to retinal afterimages in that they, too, will change in apparent size if distance cues suggest that the location of the object onto the retinal image has been altered. It has also been known for some time that non-retinal cues can produce quantitative and qualitative effects on an afterimage when it is viewed in the dark. In the present two studies, positive afterimages of an observer's hand, as well as objects held by that hand, were used as targets to investigate the effects on size-constancy scaling of moving the hand to and fro along the line of sight for different distances in the dark. Results show that, when observers focus on a held object, the changes in size predicted by Emmert's law occur in response to both active and passive proprioceptive or haptic cues. The most intriguing result consisted of the finding that, when only the hand is the target, there appears to be a limit to the decrease in apparent hand size. It appears that the visual system 'refuses' to size-scale the hand below a limit it accepts as representative or acceptable of 'its' hand.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".