Experience, 60 Frames Per Second: Virtual Embodiment and the Player/Avatar Relationship in Digital Games
Bibliographic record
Abstract
From the earliest days of video game studies as a field, and before - with discussions of virtual reality - a debate has endured over the nature of virtual embodiment. From Janet Murray’s Hamlet on the Holodeck in 1997, to Edward Castronova’s foundational examination of the phenomenon of MMOGs, to Valtin, Pietschmann, Liebold, and Ohler’s examination of online social immersion in 2014, the concern over how embodiment is configured in virtual spaces is ongoing. Further, questions of whether such embodiment is possible, and if the experience should be called ‘embodiment’, continue to be omnipresent. Several of the theories put forth about virtual embodiment are, at best, not fully explored or followed through to their logical conclusion. At worst, some of these theories paint a troubling, dehumanizing picture of the perception of virtual embodiment and the player/avatar relationship. The continued focus on the phenomenology of the experience is understandable, however, as the synthesis of player/user and in-game avatar is the locus of most, if not all, video game and virtual environment experiences. Engaging with theories of virtual identity, gender, the player/avatar relationship during gameplay, and the often embattled juxtaposition of narrative and gameplay in video games, this paper explores the ways in which avatars are both characters and embodied experiences. This examination addresses ideas of the avatar as vehicle, the avatar as narrative character, and the avatar as cybernetic embodiment, and strives to find a synthesis between them, in order to come to terms with the unique structure of the player’s interactions with the virtual experience.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".