Prime time news: The influence of primed positive and negative emotion on susceptibility to false memories
Bibliographic record
Abstract
We examined the relation between emotion and susceptibility to misinformation using a novel paradigm, the ambiguous stimuli affective priming (ASAP) paradigm. Participants (N = 88) viewed ambiguous neutral images primed either at encoding or retrieval to be interpreted as either highly positive or negative (or neutral/not primed). After viewing the images, they either were asked misleading or non-leading questions. Following a delay, memory accuracy for the original images was assessed. Results indicated that any emotional priming at encoding led to a higher susceptibility to misinformation relative to priming at recall. In particular, inducing a negative interpretation of the image at encoding led to an increased susceptibility of false memories for major misinformation (an entire object not actually present in the scene). In contrast, this pattern was reversed when priming was used at recall; a negative reinterpretation of the image decreased memory distortion relative to unprimed images. These findings suggest that, with precise experimental control, the experience of emotion at event encoding, in particular, is implicated in false memory susceptibility.
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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 | 0.013 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".