The bivalency effect in task switching: General and enduring.
Bibliographic record
Abstract
The purpose of this study was to investigate the generality and temporal endurance of the bivalency effect in task switching. This effect refers to the slowing on univalent stimuli that occurs when bivalent stimuli appear occasionally. We used a paradigm involving predictable switches between 3 simple tasks, with bivalent stimuli occasionally occurring on one of the tasks. The generality of the bivalency effect was investigated by using different tasks and different types of bivalent stimuli, and the endurance of this effect was investigated across different intertrial intervals (ITIs) and across the univalent trials that followed trials with bivalent stimuli. In 3 experiments, the results showed a general, robust, and enduring bivalency effect for all ITI conditions. Although the effect declined across trials, it remained significant for about 4 trials following one with a bivalent stimulus. Our findings emphasise the importance of top-down processes in task-switching performance.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".