Dual-Task Interference Effects on Cross-Modal Numerical Order and Sound Intensity Judgments: The <i>More</i> the Louder?
Bibliographic record
Abstract
In the current study, cross-task interactions between number order and sound intensity judgments were assessed using a dual-task paradigm. Participants first categorized numerical sequences composed of Arabic digits as either ordered (ascending, descending) or non-ordered. Following each number sequence, participants then had to judge the intensity level of a target sound. Experiment 1 emphasized processing the two tasks independently (serial processing), while Experiments 2 and 3 emphasized processing the two tasks simultaneously (parallel processing). Cross-task interference occurred only when the task required parallel processing and was specific to ascending numerical sequences, which led to a higher proportion of louder sound intensity judgments. In Experiment 4 we examined whether this unidirectional interaction was the result of participants misattributing enhanced processing fluency experienced on ascending sequences as indicating a louder target sound. The unidirectional finding could not be entirely attributed to misattributed processing fluency, and may also be connected to experientially derived conceptual associations between ascending number sequences and greater magnitude, consistent with conceptual mapping theory.
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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 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| 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 | 0.001 | 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".