Destination memory impairment in older people.
Bibliographic record
Abstract
Older adults are assumed to have poor destination memory-knowing to whom they tell particular information-and anecdotes about them repeating stories to the same people are cited as informal evidence for this claim. Experiment 1 assessed young and older adults' destination memory by having participants tell facts (e.g., "A dime has 118 ridges around its edge") to pictures of famous people (e.g., Oprah Winfrey). Surprise recognition memory tests, which also assessed confidence, revealed that older adults, compared to young adults, were disproportionately impaired on destination memory relative to spared memory for the individual components (i.e., facts, faces) of the episode. Older adults also were more confident that they had not told a fact to a particular person when they actually had (i.e., a miss); this presumably causes them to repeat information more often than young adults. When the direction of information transfer was reversed in Experiment 2, such that the famous people shared information with the participants (i.e., a source memory experiment), age-related memory differences disappeared. In contrast to the destination memory experiment, older adults in the source memory experiment were more confident than young adults that someone had shared a fact with them when a different person actually had shared the fact (i.e., a false alarm). Overall, accuracy and confidence jointly influence age-related changes to destination memory, a fundamental component of successful communication.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".