On the prevalence of directly retrieved autobiographical memories.
Bibliographic record
Abstract
In this study, we used process measures to understand how people recall autobiographical memories in response to different word cues. In Experiment 1, participants provided verbal protocols when cued by object and emotion words. Participants also reported whether memories had come directly to mind. The self-reports and independent ratings of the verbal protocols indicated that directly recalled memories are much faster and more frequent than generated memories and are more prevalent when cued by objects than emotions. Experiment 2 replicated these results without protocols to eliminate any demand characteristics or output interference associated with the protocol method. In Experiment 3, we obtained converging results using a different method for assessing retrieval strategies by asking participants to assess the amount of information required to retrieve memories. The greater proportion of fast direct retrievals when memories are cued by objects accounts for reaction time differences between object and emotion cues, and not the commonly accepted explanation based on ease of retrieval. We argue for a dual-strategies approach that disputes generation as the canonical form of autobiographical memory retrieval and discuss the implication of these findings for the representation of personal events in autobiographical memory.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".