Factors shaping vividness of memory episodes: Visitors’ long-term memories of the 1970 Japan World Exposition
Bibliographic record
Abstract
This study investigated how visitors' psychological and behavioural factors, identified in the literature, shaped their vivid long-term memories of their experiences of the Japan World Exposition, Osaka, 1970 (Expo '70) as a context. In this study, 112 memory episodes were identified from the long-term memories of 48 participants; they were rated in terms of their memory vividness and on a set of factors including affect, agenda fulfilment, intentionality, and rehearsal. The influence of these factors on the vividness of episodic and/or autobiographic memories of experiences that occurred 34 years ago was examined in two stages. First, the relationship between memory vividness and individual factors was investigated separately. Second, the relationship between memory vividness and all factors was examined through a multiple regression analysis, and the relative importance of these factors on memory vividness identified. Stage one analysis showed that all factors except intentionality were related to memory vividness in individual analyses, and curvilinear relationships between memory vividness and the factors found. Stage two analysis, in which all factors were included in a multiple regression analysis, found that rehearsal was positively related to memory vividness and all other factors not significant in the presence of rehearsal.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".