Bivalency is Costly: Bivalent Stimuli Elicit Cautious Responding
Why this work is in the frame
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Bibliographic record
Abstract
When performing tasks in alternation, substantial slowing occurs when the stimuli have features relevant to both tasks (i.e., when stimuli are bivalent as opposed to univalent). One possible source of this slowing, herein called a bivalency cost, is that encountering bivalent stimuli leads to a more cautious response style. To investigate this, we employed a paradigm that required performing three simple tasks, with bivalent stimuli occasionally encountered on one task. The results show that regardless of the feature overlap among the stimuli used for the different tasks, the introduction of bivalent stimuli slowed responding on all tasks and it was accompanied by a decrease in response errors. Overall, it appears that bivalent stimuli recruit a more cautious approach to task-switching performance.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.004 |
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 it