Associative memory with value-directed learning in younger and older adults
Bibliographic record
Abstract
According to the associative deficit hypothesis, older adults experience greater difficulty remembering associations between pieces of information (i.e., associative memory) than younger adults, despite their relatively intact memory for individual items (i.e., item memory). Recent studies showed that value-directed learning might have the potential to enhance older adults' associative memory and reduce their associative deficit, but the results are mixed with previous designs relying largely on recall. To fill the gap, this study aims to assess younger and older adults' associative memory with a classical associative memory recognition task in a value-directed remembering paradigm. In this task, participants studied high- and low-value word pairs and were then tested with item and associative recognition tasks. The two age groups performed the same in both item and associative memory, and high-value items/pairs were better remembered than low-value items/pairs for both age groups. These results raised a possibility that older adults' associative deficit and overall memory could be alleviated with value-directed processing at encoding and retrieval. The results shed light on the mechanisms underlying aging-related memory declines and inform memory intervention practice for 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 | 0.003 |
| 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 | 0.001 | 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".