Domain Generality in Metacognitive Ability: A Confirmatory Study Across Visual Perception, Memory, and General Knowledge
Bibliographic record
Abstract
Metacognition is the ability to monitor and control one's own cognitive processes, with higher-order mechanisms assessing the performance of lower-level cognitive operations to determine subjective confidence. An open question is whether metacognitive capacity is domain-general, akin to a conductor overseeing various sections of an orchestra, or whether it is inherently coupled to each domain, resembling a collection of specialized musical directors for each instrument group. Previous studies attempting to address this question have suffered from methodological drawbacks, such as a lack of control over cognitive sensitivity and low statistical power. In this confirmatory, pre-registered study, we addressed this gap by testing metacognitive ability in visual perceptual, memory, and general knowledge domains using a newly developed adaptive 'trivia' task spanning judgments about nutrition and global economics. We found substantive correlations in metacognitive bias and efficiency across domains, even when controlling for cognitive ability, suggesting up to 15-20% shared variance in metacognition across different modalities. Surprisingly however, we found the lowest correlation in metacognition between the two general knowledge domains, despite these tasks being matched on performance and surface-level features. Our results broadly support the existence of a metacognitive "g-factor," excluding several important methodological confounds; while also highlighting the importance of further research into inter-individual differences in metacognitive priors which may explain the lower correlations between the different knowledge domains.
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How this classification was reachedexpand
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".