Collaboration reduces the frequency of false memories in older and younger adults.
Bibliographic record
Abstract
Older (mean age = 74.23) and younger (mean age = 33.50) participants recalled items from 6 briefly exposed household scenes either alone or with their spouses. Collaborative recall was compared with the pooled, nonredundant recall of spouses remembering alone (nominal groups). The authors examined hits, self-generated false memories, and false memories produced by another person's (actually a computer program's) misleading recollections. Older adults reported fewer hits and more self-generated false memories than younger adults. Relative to nominal groups, older and younger collaborating groups reported fewer hits and fewer self-generated false memories. Collaboration also reduced older people's computer-initiated false memories. The memory conversations in the collaborative groups were analyzed for evidence that collaboration inhibits the production of errors and/or promotes quality control processes that detect and eliminate errors. Only older adults inhibited the production of wrong answers, but both age groups eliminated errors during their discussions. The partners played an important role in helping rememberers discard false memories in older and younger couples. The results support the use of collaboration to reduce false recall in both younger and older adults.
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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 | 0.009 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".