Multiple levels of coding modulate action co-representation in a joint Simon task
Bibliographic record
Abstract
In a series of previous experiments, we have shown that the completion of social tasks may involve the representation of the actions of our partners. Motivated by the recent proposal that such action co-representation may only occur when a partner is in peri-personal space, participants in our present study performed a JSE task in three separate conditions: (1) Close: seated .2m apart with stimuli appearing on a 17 screen; (2) Far: seated 1.5m apart with stimuli appearing on a 17 screen; and, (3) Far-Projector: seated 1.5m apart with the stimuli appearing on a 1.5x2.5m white board. Of additional interest to us was the fact that examining the role of peri-personal space necessitated the introduction of separate response spaces. Thus, in a departure from our previous work, participants executed their responses on separate keyboards. The observed JSEs in the Far and Far-Projector conditions were consistent with our previous work. However, we did not observe a JSE in what could be considered the baseline condition (Close condition). We attribute this latter outcome to be related to the introduction of separate work spaces. We contend that perceptual-motor interactions occur at multiple, interactive levels and that the spatial relations between the partners, the stimulus environment, and the response locations are all potential modulators of action co-representation. Acknowledgments: This research was funded by NSERC and an Early Researcher Award from the Ontario Ministry of Research and Innovation.
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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 | 0.016 |
| 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 | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".