Me, Myself, and Interface: The Role of Affordances in Digital Visual Self-Representational Practices
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
A growing number of digital games and virtual worlds allow users to create a virtual self, commonly referred to as an ‘avatar.’ Essentially, the avatar is a digital entity which is controlled by the user to attain agency within the virtual world. Avatars are visually customized by users via interfaces, referred to within the body of this work as Character Creation Interfaces (CCIs). \n \nCCIs are often framed as tools that are utilized by players to create a desired avatar. In other words, the popular approach is one that is anthropocentric in nature and neglects to take into account the ways in which interface affordances - the action possibilities afforded by an artifact - potentially constrain our interactions with them. In my dissertation, I argue that CCIs co-construct avatars with players. I mobilize Actor-Network Theory in order to re-position these interfaces as actors, rather than benign tools in digital-visual self-representational practices. \n \nIn order to investigate the interface-as-actor I present an analytical framework: the Avatar Affordances Framework, and apply this framework to 20 CCIs in order to systematically study their affordances. In the second phase of this investigation, I present data on two user studies: the first, a within-subjects study investigating self-representational practices in the Massively-Multiplayer-Onlne-Game (MMOG) Rift (n = 39), the other, a between-subjects study of self-representational practices on the Nintendo WiiU console's MiiCreator (n = 24). Results of these two studies are presented alongside analytical data derived from both interfaces via the Avatar Affordances Framework in order to illustrate how interface affordances are negotiated by players. A final study, an autoethnographic chapter, situates myself within the dissertation as both a researcher and user of the technology, addressing how my own experiences with these games, and my own self-representational practices, have come to shape this research. \n \nData from the aforementioned studies was then utilized in order to generate a list of best practices for game developers. To date, such documentation is absent from game design literature. It is my hope that the practices outlined herein help developers make design choices that invite opportunities for identity play without simultaneously creating socially exclusive spaces.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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