Encoding Perceptual Features in the Deese–Roediger–McDermott Paradigm: Different Consequences for Studied Items and False Memories
Bibliographic record
Abstract
Abstract Previous studies have shown that the incidence of false memories in the Deese–Roediger–McDermott paradigm is reduced when studied words are accompanied by their pictures or images and also reduced when monitoring activities are enhanced at retrieval. In the present experiment, studied words were accompanied by perceptual features to be learned (word color and location on the screen), and monitoring at retrieval was enhanced by asking participants to recall word location, color, or both features for words identified as old in a recognition test. In contrast to our predictions, we found that recognition of studied words was impaired as more perceptual features to be learned were added, but the number of false memories was not reduced by these additions. We attribute this differential effect to the division of attention at encoding associated with learning perceptual features reducing the subsequent explicit recollection of list items while having no effect on the implicit conceptual representations supporting the false familiarity-based recognition of critical lures. Although the false recognition of critical lures was as high as the correct recognition of studied words in some conditions, vividness ratings were significantly lower for false memories, in line with previous findings.
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How this classification was reachedexpand
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 | 0.001 |
| 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 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".