The Effects of Scene Inversion on Change Blindness
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
In two experiments, participants searched for a difference between two views of a scene. In Experiment 1, the authors extended the change-blindness findings from previous work by R. A. Rensink, J. K. O'Regan, and J. J. Clark (1997), which used an experimenter-induced global transient, to a less artificial situation in which participants searched for a difference in a pair of photographic images presented simultaneously. To examine the idea that meaning-driven endogenous orienting was responsible for the previously observed advantage for changes in center-of-interest items, the authors inverted half of the image pairs. The advantage for center-of-interest items was replicated with upright displays, but it was completely eliminated by inversion, strongly supporting the role of meaning-driven endogenous orienting in this task. With flickering displays (Experiment 2), the center-of-interest effect was completely unaffected by inversion. The authors suggest that when change blindness is induced via flicker, scene modifications are typically found by stimulus-driven rather than by meaning-driven processes.
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 | 0.001 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it