Is the Spotlight an Obsolete Metaphor of “Seeing with the Mind's Eye“? A Constructive Naturalistic Approach to the Inspection of Visual Mental Images
Bibliographic record
Abstract
Does conscious aware inspection of visual mental images mimic a spotlight? To answer this, a constructive naturalistic approach was used to integrate image latency (time necessary to generate a visual image), image size (specified by the size of an external display), and vividness (verbal report, through rating, indicating activation strength of images). Participants were asked to form images at “small” and/or “large” sizes and immediately rate them on a 7-point vividness scale. In Experiment 1, sizes varied between participants, and images were “trial-unique.” In Experiment 2, the task required forming all images repeatedly at 4 varying sizes. In Experiment 1, larger images took longer than smaller images to reach same vividness level, with interaction between vividness and size. Size effects and interaction disappeared in Experiment 2; furthermore, images seemed to undergo gradual built-up and more uniformly-distributed inspection. Both imagery phenomenology and its behavioral correlates seem to support the spotlight metaphor.
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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 | 0.007 |
| 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 | 0.005 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".