The Item-Specific Proportion Congruency Effect is Contaminated by Short-Term Repetition Priming
Bibliographic record
Abstract
The item-specific proportion congruency (ISPC) effect constitutes the phenomenon that Stroop effects are reduced when incongruent items belong to a mostly-incongruent (MI) than a mostly-congruent (MC) grouping. While the ISPC effect is purported to reflect associations formed in long-term memory, the assigned proportion manipulation entails that stimulus repetitions vary as a function of the MC and MI conditions, leaving open the possibility that a short-term repetition priming process may work to enlarge the Stroop effect in the MC relative to the MI group. In the present study we investigated whether the ISPC effect reflected contributions from separate long-term associative learning and short-term repetition priming processes. To do so, the magnitude of the ISPC effect was compared when stimulus repetitions were systematically present and absent across the experimental session. While we observed that the ISPC effect was robust across groups, it was revealed that removing stimulus repetitions significantly attenuated the effect. Additionally, it was revealed that stimulus repetitions had a profound impact on performance, and sequential congruency (i.e., congruent-to-congruent and incongruent-to-incongruent inter-trial repetitions) had none, suggesting that this repetition priming process depended on the repetition of stimulus features. Overall, the present study indicates the typical ISPC effect reflects contributions from both short and long-term memory processes.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".