Visual Self-Motion Feedback Affects the Sense of Self in Virtual Reality
Bibliographic record
Abstract
We assessed how self-motion affects the visual representation of the self. We constructed a novel virtual-reality experiment that systematically varied an avatar's motion and also biological sex. Participants were presented with pairs of avatars that visually represented the participant ('self-avatar'), or another person ('opposite avatar'). Avatar motion either corresponded with the participant's motion, or was decoupled from the participant's motion. The results show that participants identified with (i) 'self-avatars' over 'opposite-avatars', (ii) avatars moving congruently with self-motion over incongruent motion, and importantly (iii) with the 'opposite avatar' over the 'self-avatar' when the opposite avatar's motion was congruent with self-motion. Our results suggest that both self-motion and biological sex are relevant to the body schema and body image and that congruent bottom-up visual feedback of self-motion is particularly important for the sense of self and capable of overriding top-down self-identification factors such as biological sex.
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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 | 0.001 | 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) | 0.002 | 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".