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Record W2154457055 · doi:10.1155/2010/897217

Time and Space in Digital Game Storytelling

2010· article· en· W2154457055 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Computer Games Technology · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsNarrativeStorytellingGame studiesGame designComputer scienceRepresentation (politics)Space (punctuation)Game mechanicsField (mathematics)Narrative criticismNarrative inquiryNarrative networkMultimediaArtificial intelligenceMathematicsPolitical scienceLiteratureArtPolitics

Abstract

fetched live from OpenAlex

The design and representation of time and space are important in any narrative form. Not surprisingly there is an extensive literature on specific considerations of space or time in game design. However, there is less attention to more systematic analyses that examine both of these key factors—including their dynamic interrelationship within game storytelling. This paper adapts critical frameworks of narrative space and narrative time drawn from other media and demonstrates their application in the understanding of game narratives. In order to do this we incorporate fundamental concepts from the field of game studies to build a game-specific framework for analyzing the design of narrative time and narrative space. The paper applies this framework against a case analysis in order to demonstrate its operation and utility. This process grounds the understanding of game narrative space and narrative time in broader traditions of narrative discourse and analysis.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.983
Threshold uncertainty score0.245

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.006
GPT teacher head0.260
Teacher spread0.255 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it