Control processes in voluntary and explicitly cued task switching
Bibliographic record
Abstract
Explicitly cued task switching slows performance relative to performing the same task on consecutive trials. This effect appears to be due partly to more efficient encoding of the task cue when the same cue is used on consecutive trials and partly to an additional task-switching process. These components were examined by comparing explicitly cued and voluntary task switching groups, with external cues presented to both groups. Cue-switch effects varied in predictable ways to dissociate explicitly cued and voluntary task switching, whereas task-switch effects had similar characteristics for both instructional groups. The data were well fitted by a mathematical model of task switching that included a cue-encoding mechanism (whereby cue repetition improves performance) and an additional process that was invoked on task-switch trials. Analyses of response-time distributions suggest that this additional process involves task-set reconfiguration that may or may not be engaged before the target stimulus is presented.
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".