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Record W4400142512 · doi:10.1145/3643834.3661548

Disembodied, Asocial, and Unreal: How Users Reinterpret Designed Affordances of Social VR

2024· article· en· W4400142512 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueDesigning Interactive Systems Conference · 2024
Typearticle
Languageen
FieldComputer Science
TopicVirtual Reality Applications and Impacts
Canadian institutionsUniversity of Waterloo
FundersUniversity of Waterloo
KeywordsAffordanceHuman–computer interactionComputer scienceVirtual realityMultimedia

Abstract

fetched live from OpenAlex

Although Social Virtual Reality (SVR) affordances are designed to enable embodied social activities and interactions within virtual environments, the ways that users perceive and interpret these affordances can shape how SVR platforms are used and experienced. In this study, we examined the design and use of SVR affordances based on qualitative survey data from 100 SVR users. We observed that user practices diverge in important ways from intended designs, adding complexity to conventional interpretations of SVR platforms as embodied social environments. This research highlights dynamic user behaviour in which users interpret and reconfigure the affordances of SVR platforms, ranging from asocial use cases to actions that reflect the current limits of embodied communication. We contribute findings that may improve SVR design by revealing opportunities to foreground user needs and expectations, leveraging both the designed possibilities of SVR and the interpretations of those possibilities.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.989
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.035
GPT teacher head0.300
Teacher spread0.265 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it