Picture Theory, Tacit Knowledge or Vividness-Core? Three Hypotheses on the Mind's Eye and Its Elusive Size
Bibliographic record
Abstract
In this study, we compared hypotheses derived from our interpretation of three imagery theories -picture theory, tacit knowledge and vividness-core.Participants were asked to generate "small" (1.2 o ), "medium" (11 o or 16 o ), or "large" (91 o ) images of concrete, everyday objects.Image size varied between subjects in Experiment 1, and within subjects in Experiment 2. Vividness ratings and image latency were measured.According to picture theory, vividness should increase directly with latency, and both should increase continuously with size, in both Experiments.According to tacit knowledge theory, such a continuous increase will occur only in Experiment 2 when the full range of sizes is known to the subjects.According to vividness-core theory, latency and vividness should be inversely related in both experiments, and latency should increase with size in Experiment 1 but not in Experiment 2. Results support vividness-core.Images, we conclude, are primarily derived from memories whose latent activation is reflected in reported vividness, as specified by vividness-core theory.
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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 | 0.005 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.006 |
| Scholarly communication | 0.002 | 0.008 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".