A Best-Fit Framework and Systematic Review of Asymmetric Gameplay in Multiplayer Virtual Reality Games
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Increasingly, virtual reality (VR) design and research leverages gameplay asymmetries, flattening discrepancies of interface, abilities, information or other aspects between players. A common goal is to induce social interactions that draw players without head-mounted displays into a shared game world. Exploring these asymmetries resulted in many artifacts, creating an innovative yet disparate research landscape that showcases points for improvement in coverage of the field and theoretical underpinnings. In this article, we present a literature review of asymmetry in multiplayer VR games, using a framework synthesis method to assess the field through a lens of existing literature on asymmetries in gameplay. We provide an overview of this emerging subfield and identify gaps and opportunities for future research. Moreover, we discuss how research artifacts address prior theoretical work and present a “best fit” framework of asymmetric multiplayer VR games for the community to build upon.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it