The effects of social interaction on the kinematics of a reaching movement in children
Bibliographic record
Abstract
Specific kinematic patterns have been observed for adults when socially interacting in cooperative and competitive reaching tasks. Cooperative reaching tasks show longer movement times, decreased amplitude of peak velocity and a decreased maximum grip aperture compared to competitive reaching tasks. However, it is unknown when differences in the kinematic patterns emerge in children. The purpose of this study was to determine the effect of social interaction on the kinematics of a reaching movement in children. To date, right-handed participants between the ages of three and 13 (N = 16, 8 female), were tested. The task required the participant to move a block from a starting position located on desk in front of their right hand to the target location in the centre of the desk. The task was completed under four different conditions; 1) at a normal pace, 2) as fast as possible, 3) competitively against a confederate, and 4) cooperatively with a confederate. The confederate was a young adult female. Kinematic data (movement time, maximum grip aperture, resultant peak velocity) were recorded for each trial. Preliminary results showed that children had a significantly slower movement time, and a significant decrease in resultant peak velocity when completing the task in a cooperative setting compared to a competitive setting. Overall, these results support the hypothesis in showing that children, similar to adults, differ in their kinematic patterns depending of whether they are interacting cooperatively or competitively. Future directions aim to compare cross-sectionally children's performance as a function of age.Acknowledgments: NSERC, FOSSA
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".