When Gist and Familiarity Collide: Evidence From False Recognition in Younger and Older Adults
Bibliographic record
Abstract
OBJECTIVES: Aging is associated with decreased recollection required to offset misleading effects of familiarity, as well as an increased mnemonic reliance on gist-based over detail-based information. We tested the novel hypothesis that age-related decrements in overriding familiarity can be eliminated under conditions in which gist-based information facilitates retrieval. METHOD: Twenty-seven younger adults and 27 older adults viewed scenes from two categories in an incidental encoding phase. In a recognition phase, old scenes were intermixed with new scenes from the studied categories and an unstudied category, with each new scene reappearing after 4, 18, or 48 intervening scenes. Participants were to respond "yes" to old scenes, and "no" to new scenes, including their repetitions. RESULTS: Despite encoding the scenes similarly, older adults made more false endorsements of new and repeated new scenes from studied categories. Both groups, however, were equally unlikely to falsely recognize new and repeated new scenes from the unstudied category. DISCUSSION: When helpful gist and misleading familiarity collide, gist wins, and eliminates age-related increases in false recognition.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".