Memory selectivity of younger and older adults: The interactive effects of valence and subjective value.
Bibliographic record
Abstract
Whereas the ability to prioritize important information in memory remains preserved with age, it is still unclear how subjective value may interact with emotional valence to impact memory. The present study examined the interaction of value and valence in memory selectivity among younger and older adults. A sample of 24 younger (aged 17-29; 20.13 ± 2.54) and 24 older adults (aged 65-79, 70.13 ± 4.47) ranked valenced (positive and negative) and neutral words based on their subjectively perceived value/importance for memory. They then completed a value-directed remembering task, studying the same set of words paired with their assigned values, with a goal to maximize value points accrued in a subsequent word free recall task. Next, they completed a cued recall for values assigned to the words. Mixed-model analyses of variance were conducted on value assignment, word free recall, and cued value recall performance. Positive words were assigned a higher value/importance than negative or neutral words. Items assigned a higher value were better recalled and likely to be recalled first, an effect that tends to be larger for older than younger adults. Older adults generally face specific challenges recalling schema-inconsistent high values originally assigned to negative words, an effect absent in younger adults. The results suggested that valence can direct value assignment and, in turn, interact with the assigned value to guide memory selectivity. Relative to younger adults, older adults appear more likely to rely on a "positive is more valuable than negative" schema to guide value retrieval. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".