Helping you and helping me: Facilitatory joint action behaviour is dependent on social context
Bibliographic record
Abstract
We constantly rely on others to achieve daily tasks and goals. Although sometimes we may not need another person’s help in completing simple daily activities, we often receive it. For example, most people are very capable of opening a door and walking through it, yet often one person will hold the door open for the following person. This is a clear demonstration of the human tendency to facilitate the actions and goals of another person. In the present study, we sought to determine if this facilitatory action behaviour could be influenced by the social context in which it occurs. Participants were asked to pass mugs to a partner seated across the table. The mugs were either owned by the initiating partner or the receiving partner. The receiving partner was to either act upon the object or remain stationary. Interestingly, ownership influenced the initiating partner’s facilitatory behaviour. When the receiving partner was required to act upon their own mug the handle of the mug was oriented by the initiator in a manner that required less effort to grasp. That is, the handle was tilted further away from the hand and the body so less perturbation of the movement was required. However, this difference between action and no action conditions was only observed when the mug was the receiving partner’s mug, there was no effort to facilitate the action of another person when the mug was owned by the initiator. Overall, this suggests that the level of affiliation the initiator or receiver has with an object influences joint action behaviour. Specifically, the affiliation the users have with the mugs influenced the likelihood that the initiator will incorporate the receiver’s action goals into their own action plans.
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".