Proactive and reactive cognitive control in the absence of learning and memory confounds: Evidence from a cross-modal trial-unique Stroop task
Bibliographic record
Abstract
Goal-directed behaviour is typically conceptualized as striking a balance between two antagonistic cognitive control states such as proactive and reactive control, as demonstrated by conflict phenomena such as the list-wide proportion congruency and congruency sequence effects. However, control-based explanations for these phenomena have come under criticism due to low-level associative regularities that are frequently confounded with conflict manipulations within these experimental designs. In the current study, a novel Stroop paradigm referred to as the ‘trial-unique Stroop task’ was developed to examine whether these effects could be observed in the absence of low-level associative regularities. On each trial, participants typed a word they heard spoken aloud while ignoring a word visually displayed on the screen. Importantly, each word only appeared in a single trial throughout the experiment, and because stimuli and responses were never repeated, there were no low-level associative regularities across trials. Using this paradigm, I observed both congruency sequence (Experiment 1) and list-wide proportion congruency (Experiment 2) effects, providing the strongest evidence to date for control-based explanations of these phenomena. Split-half analyses revealed much higher reliability than traditional colour-word Stroop tasks for the congruency effect (rSB = .98), the congruency sequence effect (rSB = .42) and list-wide proportion congruency effect (rSB = .85). Moreover, the methodological advantages of the trial-unique Stroop task allow for the independent manipulation of task features related to control, learning, and memory processes. The promising results of this study support the application of the trial-unique Stroop task in this context and opens new avenues for future research.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| 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 | 0.002 |
| Research integrity | 0.001 | 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".