Bibliographic record
Abstract
Years after a shocking news event many people confidently report details of their flashbulb memories (e.g., what they were doing). People's confidence is a defining feature of their flashbulb memories, but it is not well understood. We tested a model that predicted confidence in flashbulb memories. In particular we examined whether people's social bond with the target of a news event predicts confidence. At a first session shortly after the death of Michael Jackson participants reported their sense of attachment to Michael Jackson, as well as their flashbulb memories and emotional and other reactions to Jackson's death. At a second session approximately 18 months later they reported their flashbulb memories and confidence in those memories. Results supported our proposed model. A stronger sense of attachment to Jackson was related to reports of more initial surprise, emotion, and rehearsal during the first session. Participants' bond with Michael Jackson predicted their confidence but not the consistency of their flashbulb memories 18 months later. We also examined whether participants' initial forecasts regarding the persistence of their flashbulb memories predicted the durability of their memories. Participants' initial forecasts were more strongly related to participants' subsequent confidence than to the actual consistency of their memories.
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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 | 0.002 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".