The use of a shared task representation to select and plan movements during a sequential joint action task
Bibliographic record
Abstract
One cognitive theoretical approach to the study of joint action holds that co-actors form shared task representations that contain a shared goal and information related to the completion of the goal. The study of sequential joint actions (where one co-actors movement is the precursor for their partner’s movement) provides insight into how shared task representations could be used during joint actions. If co-actors use shared task representations to plan their movements, then the initial movement in a sequential joint action should be influenced by some feature of their co-actors subsequent movement. The purpose of the present study was to determine if co-actors plan their movements to accommodate the difficulty of their partners’ action. Further, we investigated whether motor experience influences response selection in a joint action task. To these ends, partners performed an aiming task that was divided between them. The participants were told to place a dowel on a line between two potential targets and that their partner would have to make a movement with the dowel to one of the targets from wherever they placed it on the line. The targets varied in relative size throughout the session and the targets were randomly chosen on each trial. Participants completed the partner task before and after completing an individual task. Consistent with the prediction, that co-actors take the difficulty of their partners’ actions into account, the dowel was placed closer to the smaller target of a pair. Further, in support of the prediction that motor experience influences dowel placement, there was a shift in dowel placement following the individual task. These results support the hypothesis that co-actors plan their movements based on features of their co-actors movements and that motor experience provides information that allows people to better plan movements for their partners. Acknowledgments: NSERC and the Ontario Ministry of Innovation and Research
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".