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Record W2323805732 · doi:10.1177/0270467612469071

Unraveling <i>Braid</i>

2012· article· en· W2323805732 on OpenAlexaff
Luke Arnott

Bibliographic record

VenueBulletin of Science Technology & Society · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsWestern University
Fundersnot available
KeywordsNarrativeMeaning (existential)BraidStorytellingRhetoricAestheticsRhetorical questionReading (process)SemioticsRepresentation (politics)Computer scienceEpistemologyLinguisticsLiteratureArtPoliticsPhilosophyHistoryLaw

Abstract

fetched live from OpenAlex

“Unraveling Braid” analyzes how unconventional, non-linear narrative fiction can help explain the ways in which video games signify. Specifically, this essay looks at the links between the semiotic features of Jonathan Blow’s 2008 puzzle-platform video game Braid and similar elements in Georges Perec’s 1978 novel Life A User’s Manual, as well as in other puzzle-themed literary precursors. Blow’s game design concepts “dynamical meaning” and “game play rhetoric” are explained in relation to a number of Braid levels; along side this analysis is a parallel examination of the relationship between puzzle-makers and puzzle-solvers in Life A User’s Manual, revealed from a close reading of textual and organizational elements of Perec’s novel. Ultimately, Braid and Life A User’s Manual are shown to draw upon the same signifying processes, which are understood by their authors to operate within an implicitly communicative model. “Unraveling Braid”develops this model by positing a theory of storytelling in the imperative mood, in which the representation and arrangement of objects in the visual/organizational space of the text or game world becomes a fundamental rhetorical technique and meaning-maker.This technique signal show the reader/player is meant to progress through the work and interpret it as narrative, telling the reader/player what to do (but not necessarily how to do it). An understanding of “imperative” storytelling, this essay concludes, allows for a discussion of games and other media that denies neither the importance of player interactivity nor that of authorial design.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.013
Scholarly communication0.0070.007
Open science0.0010.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0060.001

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.

Opus teacher head0.015
GPT teacher head0.280
Teacher spread0.265 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations10
Published2012
Admission routes1
Has abstractyes

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