Bibliographic record
Abstract
Digital games are among the most popular media on the planet, and billions of people inhabit such virtual worlds daily. Most of these worlds are made of virtual buildings, roads, and cities that players travel through. This dissertation aims to fill a gap in the game studies literature regarding the architecture of digital games, in terms of both its aesthetic aspect and its symbolic role as they relate to gameplay. It strives to answer the following questions: how does the design of virtual architecture influence gameplay and storytelling through its communicative aspect? How does digital architecture relate to real architecture? Where does the inspiration for digital games architecture come from? In order to answer these questions, this dissertation examines how architecture is used in digital games, how players interact with it, and what it communicates. The dissertation thus analyses the architecture of digital games through the lenses of semiotics and architecture theory, mainly the research pursued by Umberto Eco as regards the semiotics of architecture and by Brian Upton with his theory of “anticipatory play.” It presents case studies of digital games grouped in three categories: reconstructive, fantastic, and visionary. Reconstructive virtual architecture, as evidenced in Assassin’s Creed II (2009), aims to recreate existing locales, be they from the present or the past, with the intent to immerse the player in a simulated environment that is as close as possible to reality. Fantastic virtual architecture, represented by the Japanese game Final Fantasy XV (2016), is the category that arguably encompasses the vastest number of digital games, as it comprises the type of architecture designed to appear, if not realistic, at least plausible, and bears resemblance to real-world architecture. Finally, the category of visionary virtual architecture, as found in the independent game NaissanceE (2014), while still representing plausible and not completely abstract features, is meant to be perceived as an “impossible” construct. Through these case studies, the dissertation outlines how architecture plays a central role in digital games design, and proposes a semiotic framework for the analysis of virtual architecture that can be applied to the vast majority of digital games.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.027 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".