Presence in time: watching live and recorded sports in VR increases spatial, interpersonal, and temporal presence
Bibliographic record
Abstract
Introduction Little research has explored the experience of viewing sporting events in three-dimensional (3D) virtual reality (VR), whether at the time the sporting events are happening or at a later date. Materials and Methods Participants (n = 148) were university students who watched brief segments of a 360° live stream of collegiate volleyball and basketball games, either live, at the time the games were happening, or approximately 1 week later. Participants watched segments of gameplay both while wearing and not wearing a 3D-VR headset, and provided spatial, interpersonal, and temporal presence ratings immediately afterward, as well as ratings of satisfaction with each viewing format. Results Viewing the games in 3D-VR, as compared to watching the games on a standard two-dimensional (2D) tablet computer, was associated with greater spatial, interpersonal, and temporal presence, and watching games live was associated with greater temporal presence. Although no differences were seen in overall satisfaction between the 3D-VR and standard 2D-tablet viewing formats, the more participants experienced a sense of presence while watching the games, the more they were satisfied with their sports viewing experience. Discussion Sports spectatorship in 3D-VR is associated with a heightening of the feeling of spatial presence (“being there”), interpersonal (i.e., social) presence (“being together”), and temporal presence (“this is happening now”), regardless of whether the games that one is watching are actually occurring in the present, or are instead camera recordings that were captured sometime in the past. Researching the experience of temporal presence in response to recordings of other kinds of public (e.g., music concert) and private events (e.g., family memory) is recommended.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 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 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".