Reducing age-related Memory Deficits: The Roles of Environmental Support and self-initiated Processing Activities
Bibliographic record
Abstract
BACKGROUND: The notion that memory performance in older adults can be boosted by information provided by the environment was proposed by Craik (1983). The suggestion was that age-related memory deficits can be attenuated and sometimes even eliminated by a complementary combination of environmental support and consciously controlled self-initiated activities. OBJECTIVE: The objective of the present article was to review the subsequent empirical and theoretical work on the topics of environmental support and self-initiated ativities as they relate to the effects of aging on human memory. DISCUSSION: The notion of schematic support from the person's knowledge base is introduced and its relevance discussed. In addition, the effects of various types of support on encoding and retrieval processes in older adults are desribed, and the increasing theoretical importance of executive processes in reducing age-related memory deficits is discussed. CONCLUSION: As one main conclusion, it is suggested that self-initiated control processes interact with both information provided by the environment and by the person's knowledge base to improve the effectiveness of encoding and retrieval processing in 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 | 0.000 | 0.001 |
| 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 | 0.000 |
| 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".