Use of Memory Compensation Strategies Is Related to Psychosocial and Health Indicators
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Research has shown that psychosocial and health characteristics may affect older adults' cognitive performance, self-referent beliefs, and general adaptive resilience. Are such characteristics related specifically to older adults' reported efforts to compensate for memory losses? The Memory Compensation Questionnaire (MCQ) measures 5 mechanisms of everyday memory compensation as well as 2 general aspects of compensatory motivation and awareness. Correlates were derived from indicators of specific health conditions, subjective health ratings, personality, well-being, and memory self-efficacy (MSE). All measures were administered to a cross-sectional sample of 528 healthy older adults between 55 and 94 years of age from the Victoria Longitudinal Study. Specific health composites (i.e., infirmities, respiratory illness), several personality dimensions (e.g., agreeableness, neuroticism), negative affect, and low MSE were associated with more frequent use of everyday memory compensation strategies. Linking healthy older adults' cognitive resilience with individual characteristics is an important contribution to emerging conceptions of adaptation and success in late life.
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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 | 0.002 | 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 | 0.000 | 0.001 |
| 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 it