Hyper-Binding: Older Adults Form Too Many Associations, Not Too Few
Bibliographic record
Abstract
Associative memory declines with age, and this decline is thought to stem from a decreased ability to form new associations or bind information together. However, a growing body of work suggests that (a) the binding process itself remains relatively intact with age when tested implicitly and (b) older adults form excessive associations (or "hyper-bind") because of a decreased ability to control attention. In this article, we review evidence for the hyper-binding hypothesis. This work shows that older adults form more nontarget associations than younger adults, which leads to increased interference at retrieval and forgetting, an effect that may extend to others with poor attentional control, such as children and people with attention-deficit disorder. We discuss why hyper-binding is apparent only under implicit test conditions and how it affects memory for everyday events. Although hyper-binding likely contributes to forgetting, it may also confer certain advantages when seemingly irrelevant associations later become relevant.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".