Experiential disparities in social VR: uncovering power dynamics and inequality
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
Social Virtual Reality (SVR) offers new forms of social interaction, identity expression, and embodied experiences, but it has also revealed significant issues related to social inequalities and unequal power dynamics within virtual worlds. Employing a critical, intersectional approach, we investigate how existing power dynamics and inequalities shape individual experiences and interactions in SVR, shedding light on the differences between the ways that dominant groups and marginalized groups (in relation to race and gender specifically) experience SVR. Analyzing qualitative survey data, we discuss the complex relationship between power dynamics and key SVR affordances, including expectations around perceived anonymity, limited options for avatar customization, practices for self-representation, and actions relating to embodied social interactions. Identifying the specific ways that power and privilege are reenacted in virtual environments, our work calls for deeper engagements with the ways that non-dominant identities and experiences continue to be marginalized in SVR.
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 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 | 0.001 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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