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Record W1124080524 · doi:10.26503/dl.v2013i1.679

Memory of a Broken Dimension: a study in a politics of skill for experimental art games

2014· article· en· W1124080524 on OpenAlexfundno aff
W. C. Lockett

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicDigital Media and Philosophy
Canadian institutionsnot available
FundersMcGill University
KeywordsDimension (graph theory)Embodied cognitionPoliticsReading (process)Representation (politics)Key (lock)SculptureAestheticsCognitive scienceComputer scienceClose readingEpistemologyVisual artsSociologyPsychologyArtArtificial intelligenceLiteraturePolitical scienceLawMathematicsPhilosophy

Abstract

fetched live from OpenAlex

This paper outlines a political theory of digital games using conceptual resources drawn from the history of art. Beginning with a close reading of a single game—Memory of a Broken Dimension—the author develops his theoretical concerns through a contrast between Ian Bogost’s theory or procedural representation and a theoretical framework focused on the politics of skill acquisition process, embodied activities of information access and manipulation, and the historically determined forms of material objects. By revisiting key texts pertaining to minimalist sculpture—specifically those of art historian Michael Fried and artist Robert Morris—the author elucidates the connection between Memory of a Broken Dimension and the lager political stakes of his project.

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)0.004
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.024
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.018
Scholarly communication0.0090.009
Open science0.0020.005
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0080.000

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 head0.017
GPT teacher head0.269
Teacher spread0.252 · 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 designTheoretical or conceptual
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

Citations0
Published2014
Admission routes1
Has abstractyes

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