A misleading feeling of happiness: metamemory for positive emotional and neutral pictures
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Emotional information is often remembered better than neutral information, but the emotional benefit for positive information is less consistently observed than the benefit for negative information. The current study examined whether positive emotional pictures are recognised better than neutral pictures, and further examined whether participants can predict how emotion affects picture recognition. In two experiments, participants studied a mixed list of positive and neutral pictures, and made immediate judgements of learning (JOLs). JOLs for positive pictures were consistently higher than for neutral pictures. However, recognition performance displayed an inconsistent pattern. In Experiment 1, neutral pictures were more discriminable than positive pictures, but Experiment 2 found no difference in recognition based on emotional content. Despite participants' beliefs, positive emotional content does not appear to consistently benefit picture memory.
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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 | 0.001 |
| 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) | 0.000 | 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 it