Physical-Digital Privacy Interfaces for Mixed Reality Collaboration
Bibliographic record
Abstract
We present a study exploring privacy behaviours in mixed reality collaborative environments. We consider two scenarios involving hiding and sharing blended physical-virtual documents around a tabletop, under two vertical display conditions: a solo display showing the remote collaborator as an avatar, and circumambient displays showing the rest of the connected virtual environment. We explore four types of cues (interactive, communication-based, ambient, and infrastructure) and their impact on how collaborators hide and share blended physical-virtual documents. Many participants did not obviously develop a sense that the physical and virtual surroundings were fused; as a result, certain physical privacy behaviours (e.g., orienting one's body to shield documents from the remote collaborator) were less apparent in the study. However, the circumambient displays generated curiosity about how the spaces were connected, and episodes where breaches were enacted or the spatial correlation was otherwise suggested led some participants to trust the environment less. On the table, the presence of fiducial markers and digital document "shadows" served to cue participants about the impact of hiding and sharing physical documents, however accidental breaches usually went unnoticed.
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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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".