Toward a Metacognitive Account of Cognitive Offloading
Bibliographic record
Abstract
Individuals frequently make use of the body and environment when engaged in a cognitive task. For example, individuals will often spontaneously physically rotate when faced with rotated objects, such as an array of words, to putatively offload the performance costs associated with stimulus rotation. We looked to further examine this idea by independently manipulating the costs associated with both word rotation and array frame rotation. Surprisingly, we found that individuals' patterns of spontaneous physical rotations did not follow patterns of performance costs or benefits associated with being physically rotated, findings difficult to reconcile with existing theories of strategy selection involving external resources. Individuals' subjective ratings of perceived benefits, rather, provided an excellent match to the patterns of physical rotations, suggesting that the critical variable when deciding on-the-fly whether to incorporate an external resource is the participant's metacognitive beliefs regarding expected performance or the effort required for each approach (i.e., internal vs. internal + external). Implications for metacognition's future in theories of cognitive offloading are discussed.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".