Preferential reaching and beginning-state comfort interactions: Implications for advanced motor planning
Bibliographic record
Abstract
To be successful, interpersonal coordination is dependent on the ability to predict another's action and adjust accordingly (Konvalinka, et al., 2010). In a joint-action task, Beginning State Comfort (BSC) is thus highlighted by the ability to plan motor actions in advance and "incur all the cost of the movement…to maximize the benefit to the other person" (Gonzalez, et al., 2011, p.348). This study aimed to determine how BSC, as well as hand preference, object location, object orientation and task interact in advanced motor planning. Wilfrid Laurier University students (N=18) participated in this study; where use of the Waterloo Handedness Questionnaire identified 3 left- and 15 right-handers. Using a preferential reaching paradigm, coffee mugs were arranged at 3 locations in peripersonal space, with handles oriented in 4 directions. Participants completed two tasks: pass the mug to the researcher and pour a glass and pass it to the researcher. BSC was deemed present if the mug was passed in a way that allowed the handle to be grasped comfortably. Participants completed the Empathy Quotient Questionnaire to assess differences in empathy levels, considering the task involved passing a mug containing a hot beverage. Results suggest that evidence of BSC is dependent on object orientation and task difficulty. Furthermore, an individual's level of empathy is directly related to facilitating another's BSC.Acknowledgments: Research Support: Natural Sciences and Engineering Research Council of Canada (P.J.B); Faculty of Science StudentsÔÇÖ Association (K.A.S)
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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 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".