The role of belief in occurrence within autobiographical memory.
Bibliographic record
Abstract
This article examines the idea that believing that events occurred in the past is a non-memorial decision that reflects underlying processes that are distinct from recollecting events. Research on autobiographical memory has often focused on events that are both believed to have occurred and remembered, thus tending to overlook the distinction between autobiographical belief and recollection. Studying event representations such as false memories, believed-not-remembered events, and non-believed memories shows the influence of non-memorial processes on evaluations of occurrence. Believing that an event occurred and recollecting an event may be more strongly dissociated than previously stated. The relative independence of these constructs was examined in 2 studies. In Study 1, multiple events were cued, and then each was rated on autobiographical belief, recollection, and other memory characteristics. In Study 2, participants described a nonbelieved memory, a believed memory, and a believed-not-remembered event, and they made similar ratings. In both studies, structural equation modeling techniques revealed distinct belief and recollection latent variables. Modeling the predictors of these factors revealed a double dissociation: Perceptual, re-experiencing, and emotional features predicted recollection and not belief, whereas event plausibility strongly predicted belief and weakly predicted recollection. The results show that judgments of autobiographical belief and recollection are distinct, that each is influenced by different sources of information and processes, and that the strength of their relationship varies depending on the type of event under study. The concept of autobiographical belief is elaborated, and implications of the findings are discussed in relation to decision making about events, social influence on memory, metacognition, and recognition processes.
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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 | 0.003 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".