Remembering personal change for better or worse: Retrieval context matters
Bibliographic record
Abstract
Summary We investigated how focusing on the details (experience focus) versus self‐narrative significance (coherence focus) of valenced transitions informs appraisals and emotions at recall. Participants ( N = 302) selected a negative or positive transition and rated their emotion. Two weeks later, they described their event using an experience or coherence focus, then rated emotion, event impact, self‐relevance, and memory characteristics. A coherence (vs. experience) focus produced lower negative affect and greater psychological impact, particularly for negative transitions. The negative‐coherence group showed the largest decrease in negation emotion over time. A coherence (vs. experience) focus resulted in less perceptual detail, reactivity, and re‐experiencing. Positive (vs. negative) events were deemed more central to identity and connected to other events. Mental focus informed psychological impact and negative affect, while event valence influenced self‐relevance. These findings remained when event type (interpersonal) was matched across groups. Motives for framing autobiographical memories and implications for adaptive self‐reflection 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 | 0.000 |
| 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) | 0.011 | 0.003 |
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; both teacher heads agree on what is shown here.
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".