Orders of planning in object manipulation: An examination of children, young adults, and older adults
Bibliographic record
Abstract
Objects can be grasped in various different ways based on an actor's intended action. As such, the way in which an object is grasped can be used to infer how far in advance the movement was planned. In the current study, children ages 6 to 11, young adults, and two groups of older adults (ages 60 to 70, and ages 71+) manipulated two objects (1: glass, and 2: hammer) in two movement contexts (1: demonstration with a dowel as if it were the object, and 2: actual object use). Four actions (1: pick-up – first-order planning, 2: pick-up and use – second-order planning, 3: pick-up and pass – second-order planning, and 4: pick-up and pass for use – third-order planning) were executed to assess how the order of planning influences end-state comfort, functional grasping and beginning-state comfort in independent and joint action object manipulation. Findings support van Elk, van Schie, and Bekkering's (2014) framework for action semantics. Object manipulation involves the automatic perception and detection of affordances. With experience, the motor system is better able to anticipate the consequences of action, and thus integrate multisensory information from the environment into a movement plan. Taken in light of developmental factors, it can be argued that children shift from a reliance on previously successful movements, to consideration of affordances and task demands with improvements in multisensory integration. Likewise, with age and cognitive decline, older adults revert back to the habitual system and thus display stimulus-driven responses, as opposed to actions that reflect consideration of action demands. Acknowledgments: The authors would like to acknowledge the Natural Sciences and Engineering Research Council, the Ontario Ministry of Training, Colleges and Universities and the University of Waterloo for funding
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 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".