Virtual Embodiment or:: When I Enter Cyberspace, What Body Will I Inhabit?
Bibliographic record
Abstract
The following paper attempts to look at virtual reality technologies—and the (dis)embodiment affected by them—through a phenomenological lens. Specifically, augmenting traditional discussions of virtual reality as a purely technical problem, this paper seeks to bring Maurice Merleau-Ponty’s embodied phenomenology into the discussion to try to make sense of both what body we leave behind and what body we gain as we enter virtual worlds. To do this, I look both at historical examples of virtual reality technologies and their methods of (dis)integrating the body and speculative future examples of virtual reality where the corporeal body is fully sidelined through the lens of Merleau-Ponty’s account of the body schema, noting that habituation is an ever present factor that must be considered in virtual environments. Ultimately, I conclude that even in a scenario of one-to-one mind-computer transference, the virtual world will, like the physical world we currently inhabit, solicit a ‘phantom body’ thus forcing us to act and live in accordance with a mutual interplay between self and virtual world.
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.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.019 |
| Scholarly communication | 0.007 | 0.010 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".