Evidence for a visual bias when recalling complex narratives
Bibliographic record
Abstract
Although it is understood that episodic memories of everyday events involve encoding a wide array of perceptual and non-perceptual information, it is unclear how these distinct types of information are recalled. To address this knowledge gap, we examine how perceptual (visual versus auditory) and non-perceptual details described within a narrative, a proxy for everyday event memories, were retrieved. Based on previous work indicating a bias for visual content, we hypothesized that participants would be most accurate at recalling visually described details and would tend to falsely recall non-visual details with visual descriptors. In Study 1, participants watched videos of a protagonist telling narratives of everyday events under three conditions: with visual, auditory, or audiovisual details. All narratives contained the same non-perceptual content. Participants' free recall of these narratives under each condition were scored for the type of details recalled (perceptual, non-perceptual) and whether the detail was recalled with gist or verbatim memory. We found that participants were more accurate at gist and verbatim recall for visual perceptual details. This visual bias was also evident when we examined the errors made during recall such that participants tended to incorrectly recall details with visual information, but not with auditory information. Study 2 tested for this pattern of results when the narratives were presented in auditory only format. Results conceptually replicated Study 1 in that there was still a persistent visual bias in what was recollected from the complex narratives. Together, these findings indicate a bias for recruiting visualizable content to construct complex multi-detail memories.
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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 | 0.000 | 0.005 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".