Negative Emotion Enhances Memory for the Sequential Unfolding of a Naturalistic Experience
Bibliographic record
Abstract
The events of our lives unfold across time. When remembering these events, we often reference information about when they occurred and their sequential unfolding. How does negative emotion affect our ability to reconstruct the elements of an event in the correct temporal order? This study explored this question using naturalistic film stimuli. Human participants (N = 276) saw video clips varying in emotion (high versus low). Later, participants were asked to reconstruct the events in the encoded order. Participants’ temporal-order memory was better in the high- versus low-emotion condition. Free-recall data showed that participants remembered the high-emotion video with greater vividness, though consistency of details did not differ, nor did spontaneous ordering of clips. Our findings shed light on the multifaceted effects of negative emotion on memory, suggesting that highly negative events are reconstructed with greater temporal fidelity when order is a task demand. Theoretical and practical implications are discussed.
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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 | 0.002 |
| 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 | 0.001 | 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".