Is That You or The Machine? Translating Sociocultural Norms Across Distributed Spaces in Blended Realities

Paper Title

Is That You or The Machine? Translating Sociocultural Norms Across Distributed Spaces in Blended Realities

Publication Info

• Topic area: Sociocultural norms and spatial interactions in mixed reality (MR) systems.
• Keywords: Mixed reality, blended realities, sociocultural norms, spatial heterogeneity, Expectancy Violations Theory, remote collaboration, embodiment, proxemics, interaction design, user experience.

Background and Problem

• Problem / challenge: Existing mixed reality (MR) systems focus on spatial accuracy but often neglect sociocultural norms, leading to unintentionally inappropriate or confusing interactions in distributed collaborative environments.
• Significance: Addressing sociocultural norms in MR systems is critical for creating socially attuned and effective collaborative experiences, especially as these systems become more prevalent.
• Motivation and related work: Prior research has explored spatial remapping in MR but has not adequately addressed the trade-offs between spatial accuracy and sociocultural norms. Expectancy Violations Theory (EVT) offers a framework for understanding social interactions but has not been applied to MR. This paper seeks to fill this gap by investigating how users navigate these trade-offs.

Solution

• Proposed approach: A taxonomy of three modes for transmitting embodied interactions in blended realities: (1) transcribe (unaltered actions), (2) transform (spatially adapted actions), and (3) translate (socioculturally adapted actions).
• Novelty:
  1. Identification of trade-offs between spatial accuracy and sociocultural norms in MR systems.
  2. Application and extension of Expectancy Violations Theory (EVT) to MR contexts.
  3. Development of a qualitative, scenario-based methodology to explore user preferences for interaction modes.
  4. Proposal of design considerations for future MR systems to balance spatial and sociocultural factors.
• Procedure and key techniques:
  1. Conducted a low-fidelity, counterfactual user study with 20 participants using scenario-based prompts.
  2. Presented participants with three scenarios (critical, assessment, game) to evaluate preferences for transformation or translation modes.
  3. Used semi-structured interviews and thematic analysis to identify key factors influencing user decisions.

Results

• Concrete findings:
  • Participants’ preferences shifted based on situational stakes, collaborator characteristics, and familiarity with MR technology.
  • High-stakes scenarios favored spatial accuracy (transformation), while interpersonal or formal settings prioritized sociocultural norms (translation).
  • Ambiguity in system-mediated actions and multiple realities created uncertainty in interpreting social interactions.
• Advantage over baselines: Unlike prior MR systems that prioritize spatial accuracy, this study highlights the importance of sociocultural norms and offers a framework to address them.
• Experiments / evaluation:
  • 20 participants evaluated interaction modes across three scenarios using counterfactual cards.
  • Scenarios varied in stakes, power dynamics, and personal relevance.
  • Data analyzed using Reflexive Thematic Analysis (RTA) to identify themes influencing user preferences.
• Limitations and future work:
  • Study relied on low-fidelity visualizations and hypothetical scenarios, limiting generalizability to real-world MR systems.
  • Did not account for cross-cultural variations in sociocultural norms.
  • Future work should include immersive, high-fidelity MR studies, cross-cultural comparisons, and exploration of long-term user adaptation to MR glitches.

Summary

This paper investigates the trade-offs between spatial accuracy and sociocultural norms in blended realities, proposing a taxonomy of interaction modes (transcribe, transform, translate) and extending Expectancy Violations Theory (EVT) to MR contexts. Through a qualitative study with 20 participants, the authors identify factors influencing user preferences, including situational stakes, collaborator characteristics, and familiarity with MR technology. The findings highlight the need for MR systems to balance spatial and sociocultural considerations, offering a foundation for future research and design in this emerging field.