Digital Dialogism: Space, Time, and Queerness in Video Games
Bibliographic record
Abstract
Video games are multimodal pieces of media; they communicate meaning through many layers of signification including aural, visual, narrative, mechanical, and more. To understand the ways that games communicate meaning and influence interpretation, it is crucial to not just examine the various layers of game modalities, but the ways that those layers communicate with each other as multimodal objects. By adapting Mikhail Bakhtin’s literary and language theory of dialogism (1981), this dissertation argues that because games are multimodal, they have layers of different “voices” that communicate ideas about the game to its players. These dialogic multimodalities “speak” different meanings to players, who then transform their interaction with these multimodalities into a narrative whole. \nJoining queer theory, narrative theory, and game studies, this dissertation examines one of the most successful video game titles to date, The Elder Scrolls V: Skyrim (2011), which in addition to its widespread popularity, has also been identified by white supremacist groups as a game that supports white nationalist causes. Through a dialogic analysis of the multimodalities of temporal and spatial representation within the game, this dissertation identifies narrative, genre, gameplay, and representational elements of Skyrim that support white nationalist play while also silencing potential anti-racist perspectives within the game. \nChapter 1, Chapter 2, and Chapter 3 work together towards a functional version of dialogism for the study of games, proving its relevance, formalizing the changes I make to the original theory, and indicating how important dialogic readings can be. Chapter 4 argues that the construction of timespace of Skyrim follows a chronotope of domination, where the player’s use of and engagement with the game are devoted to the control of time and space. Chapter 5 examines player self-narration and embodiment in queered space, looking at how spaces communicate to players, and Chapter 6 makes the case that player use and manipulation of queered time in the game encourages players to understand and interact with Skyrim in particular ways. Together, these chapters suggest that the ways players are oriented to play Skyrim, based on its spaces and temporalities, points players towards interpretations of the game that normalize and uphold instances of white supremacy based on narrative, interactive, and mechanical means.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.031 |
| Scholarly communication | 0.013 | 0.012 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| 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".