Effects of Reward and Punishment on Conflict Processing: Same or Different?
Bibliographic record
Abstract
While it is commonly known that reward and punishment are two effective motivators of behavior, little isknown about the underlying mechanisms of reward and punishment in conflict processing. Here, we examinedwhat roles reward and punishment played in this cognitive process by using a revised version of Stroop task.Confining to incongruent trials, explicit reward association in task-relevant dimension obstructed the processingof conflict information in Experiment 1, while the explicit punishment association in task-relevant dimensionenhanced the conflict processing relative to the no-punishment condition in Experiment 2, suggesting themechanisms of reward and punishment are different from each other with the possible involvement ofparticularly used strategy. Additionally, both reward associations and punishment associations to task-irrelevantdimension showed faster response time in conflict processing, which likely reflected the roles of reward andpunishment were the same when they were implicitly related to conflict processing. Such results document thatthe effects of reward and punishment on conflict processing are modulated by the involvement of consciousness,supporting the flexible roles of reward and punishment in conflict processing.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".