Similarity is Associated With Where Repeated Event Memories Fall on the Semantic-Episodic Continuum
Bibliographic record
Abstract
Memories of repeated events are one form of memory thought to be intermediate on a proposed semantic-episodic continuum. However, it is not yet understood where repeated event memories fall on this continuum, and which factors may be associated with greater or lesser reliance on episodic and semantic memory during recall. We investigated similarity amongst instances of repeated events as one factor which may be associated with where repeated events fall on the semantic-episodic continuum. In two preregistered studies we asked participants to recall three repeated event memories from their own lives (N1 = 97 participants, 291 memories; N2 = 419 participants, 1257 memories) and report on the similarity amongst instances as well as the degree to which they relied on semantic memory, a single episode, and a mix of episodes in their recall of each event. In line with our predictions, similarity was positively correlated with reliance on semantic memory in both studies. In Study 2, similarity was negatively correlated with reliance on a single episode. We also conducted exploratory latent profile analyses using our three memory reliance variables, revealing three types of repeated event memories. In both studies, similarity of place and emotional arousal were each associated with different memory profiles. Our findings highlight the importance of considering similarity in basic and applied repeated event memory research, as different conditions of similarity (e.g., low versus high) can manifest in different patterns of reliance on episodic and semantic memory.
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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 | 0.001 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| 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".