Reasons for withdrawing belief in vivid autobiographical memories
Bibliographic record
Abstract
Previous studies have shown that many people hold personal memories for events that they no longer believe occurred. This study examines the reasons that people provide for choosing to reduce autobiographical belief in vividly recollected autobiographical memories. A body of non-believed memories provided by 374 individuals was reviewed to develop a qualitatively derived categorisation system. The final scheme consisted of 8 major categories (in descending order of mention): social feedback, event plausibility, alternative attributions, general memory beliefs, internal event features, consistency with external evidence, views of self/others, personal motivation and numerous sub-categories. Independent raters coded the reports and judged the primary reason that each person provided for withdrawing belief. The nature of each category, frequency of category endorsement, category overlap and phenomenological ratings are presented, following which links to related literature and implications are discussed. This study documents that a wide variety of recollective and non-recollective sources of information influence decision-making about the occurrence of autobiographical events.
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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 | 0.005 | 0.033 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".