MétaCan
Menu
Back to cohort
Record W2327256356 · doi:10.1177/1555412013478687

Hacking Public Memory

2013· article· en· W2327256356 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

VenueGames and Culture · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsHackerComputer scienceEmulationVideo gamePerspective (graphical)Game studiesGame designCode (set theory)SociologyMultimediaComputer securityArtificial intelligencePsychologySocial psychology

Abstract

fetched live from OpenAlex

This article uses a case study of the multiple arcade machine emulator (MAME) to insist that emulation is an important aspect of digital game culture that should not be dismissed due to copyright concerns. The author argues that emulators should be understood as ludic technologies produced by hacking practices that helped spawn and continue to permeate video game culture. Furthermore, while it may be tempting to describe the MAME as a “counter archive” that challenges institutional models of preservation, by drawing on the work of Coleman the author insists the project is better understood as a hacking practice committed to reordering “technologies and infrastructures” (p. 515). From this perspective, instead of rejecting institutional archival perspectives that view documents as truth-telling entities, the project hacks the traditional notion of the archive by treating platforms as contingent entities and game code as authentic artifacts.

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: Other · Consensus signal: none
Teacher disagreement score0.925
Threshold uncertainty score0.554

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)0.0010.000

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 head0.255
Teacher spread0.238 · 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