Age-related decreases in global metacognition are independent of local metacognition and task performance
Bibliographic record
Abstract
Metacognition refers to a capacity to reflect on and control other cognitive processes, commonly quantified as the extent to which confidence tracks objective performance. There is conflicting evidence about how "local" metacognition (monitoring of individual judgments) and "global" metacognition (estimates of self-performance) change across the lifespan. Additionally, the degree to which metacognition generalises across cognitive domains may itself change with age due to increased experience with one's own abilities. Using a gamified suite of performance-controlled memory and visual perception tasks, we measured local and global metacognition in an age-stratified sample of 304 healthy volunteers (18-83 years; N = 50 in each of 6 age groups). We calculated both local and global metrics of metacognition and quantified how and whether domain-generality changes with age. First-order task performance was stable across the age range. People's global self-performance estimates and local metacognitive bias decreased with age, indicating overall lower confidence in performance. In contrast, local metacognitive efficiency was spared in older age and remained correlated across the two cognitive domains. A stability of local metacognition indicates distinct mechanisms contributing to local and global metacognition. Our study reveals how local and global metacognition change across the lifespan and provide a benchmark against which disease-related changes in metacognition can be compared.
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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".