Developing a memory representation: Do we visualize or do we “verbalize” objects?
Bibliographic record
Abstract
According to encoding specificity, participants perform better when testing conditions match learning conditions. It is interesting that recent findings in visuo-haptic object identification violate this principle: Participants who learned to recognise objects haptically performed just as well when asked to identify objects by sight and by touch. One possible explanation is that participants who explore objects haptically visualize the objects they explore, creating a multisensory memory trace equally accessible to vision and touch. We evaluated this possibility by asking undergraduate participants to learn to recognise novel objects either by sight or by touch. Participants completed sequences of learning trials where they explored each object and test trials where they recalled the name of each object. During learning trials, some participants were presented with a visual distractor (either verbal or nonverbal characters) that they had to recognise later, whereas other participants completed a distractorless control condition. Consistent with past findings, our results violated encoding specificity for participants who learned to recognise objects haptically-this was not modified by the addition of a secondary task. It is interesting, however, that only the verbal distractors interfered with learning. These results suggest that the creation of memory representations for novel objects involves a verbal code rather than visualization, independently of how objects are initially explored. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 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 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".