U can't touch this: Does the opportunity to physically interact with a target stimulus moderate between-person inhibition of return?
Bibliographic record
Abstract
Mounting evidence suggests that Inhibition of Return (IOR) can be elicited when one person is required to move to a target location recently acquired by a second person. These effects occur even when vision of the onset of that target is occluded, suggesting that observation of a second person's movement is sufficient to elicit the effect. One explanation for this effect (Welsh et.al, 2005, 2007) involves the activation of the mirror-neuron system during between-person trials serving to trigger the same inhibitory processes active during within-person trials. This study further explored this explanation by manipulating, not only vision of the between-person target location, but also the ability to physically interact with that location. It was hypothesized that if the mirror neuron system subserved between-person IOR, results would be consistent with Welsh et al (2005) when both vision of, and the ability to physically interact with, the second person's target is blocked. If, on the other hand, inhibition depends upon one's ability to physically interact with a target, between-person IOR effects would be eliminated when vision of the target location is available but the opportunity to physically interact with it is blocked (i.e., a see-through screen). Results suggest that while the opportunity to interact with a second person's target does not appreciably moderate between-person IOR, neither does the observation of another person's movement toward a specific location elicit it if the target is never in view. These findings are inconsistent with a strong mirror neuron explanation for between-person IOR.Acknowledgments: NSERC
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 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) | 0.006 | 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".