Perceptual comparisons are necessary and sufficient for the persistence of memory biases across time
Bibliographic record
Abstract
Interactions between visual memories and percepts have been shown to induce systematic biases in observers’ memory reports. When memories are explicitly compared with percepts, the resulting biases are potent enough to persist long after they are initially reported. However, it remains unclear whether bias persistence is attributable to processes that occur during perceptual comparisons themselves or those that occur when the bias is read out during initial memory reporting. To test this, we asked observers to encode colored object silhouettes into their long-term memory in anticipation of memory testing that occurred immediately after the encoding phase and 24 hours later. At each test, observers were cued to recall a target object from memory by presenting the uncolored target silhouette. Following recognition, the probe silhouette was then re-presented in a color that was sampled proximal to the encoded target color and observers were instructed to either ignore this colored probe or to judge its similarity to the remembered target. Observers then completed the trial by either reporting the remembered target color from a continuous wheel or by completing a search for an uncolored letter. Critically, all objects tested during the immediate test were tested again during the delayed test in a report condition where colored probes were omitted. Within each test, observers’ target reports showed attractive biases towards the colored probes, with larger biases following comparisons than passive viewing. More importantly, comparison-induced biases persisted into the delayed test with comparable magnitude across reported and unreported targets, while biases induced by passively viewing the probe dissipated by the delayed test, even for targets that were initially reported. These findings suggest that processes tied to perceptual comparisons are both necessary and sufficient for the formation of report biases that carry over from one retrieval episode to the next.
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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 | 0.002 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".