Joining the Circle: Human Entry Behavior in a Mixed Reality F-Formation with Agent, Avatar, and Human Partners
Bibliographic record
Abstract
According to Hall’s theory, the space individuals maintain between one another depends on relational closeness and situational context. Prior research suggests that interpersonal distance (IPD) varies not only between virtual and real humans, but also among virtual humans depending on their perceived agency. However, little is known about how people spatially negotiate entry into mixed groups comprising different types of agents in extended reality (XR) settings. In this study, we examine participants’ entry behavior as they join a circular F-formation composed of three distinct entities: an agent, an avatar, and a real human. Specifically, we investigate how participants position themselves relative to each entity, analyzing their preferences and behaviors in terms of IPD and entry dynamics. Our findings reveal that participants maintained the greatest IPD from the real human, followed by the avatar and the agent, suggesting nuanced social distinctions among these three entities. Furthermore, when the real human was absent, participants tended to maintain a greater distance from the avatar compared to the agent. These results offer valuable insights for the design of XR collaboration environments and for understanding social dynamics in multi-agent interactions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 teacher head, 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".