Repetition lag training eliminates age-related recollection deficits (and gains are maintained after three months) but does not transfer: Implications for the fractionation of recollection.
Bibliographic record
Abstract
The objectives of this study were to replicate age-related decrements in recollection and source memory, and to determine if repetition lag training improves recollection and whether these effects maintain and transfer to other tasks. Sixteen young adults and 46 healthy older adults participated, the latter of whom comprised hi-old (n = 16) and lo-old (n = 30) based on neuropsychological memory tests. All participants completed memory tests and questionnaires at baseline, and then half of the lo-old underwent nine days of repetition lag training while the other half engaged in a 9-day active control program. The memory tests and questionnaires were repeated immediately after the training or control program, and again three months later. The baseline data replicated well-established age-related decrements in recollection. Repetition lag training improved objective measures of recollection, eliminated the age-related recollection decrement, and these improvements maintained over three months. However, training did not transfer to any other objective test of memory thought to rely on recollection, or to any subjective memory measure. The results demonstrate for the first time that repetition lag training improves objective measures of recollection, eliminates recollection differences between younger and older adults, and that these gains maintain over a 3-month period posttraining. The lack of transfer to other tasks, however, indicates that training one type of recollection (for the studied modality in this case) does not affect other types of recollection (e.g., of an item's recency). We suggest that recollection can be fractionated into many distinct types. (PsycINFO Database Record
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".