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Record W3133445492 · doi:10.7202/1075260ar

The Museum and the Killing Jar

2021· article· en· W3133445492 on OpenAlex
Andrew Bailey

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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueLoading · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsYork University
Fundersnot available
KeywordsExhibitionArgument (complex analysis)MuseologyVitalityVisual artsArtAestheticsHistoryComputer sciencePhilosophyBiology

Abstract

fetched live from OpenAlex

Within the Animal Crossing series, players have always had the ability to collect insects and then donate them to a museum where they can then be permanently exhibited. This paper makes the argument that this collecting and exhibiting of game objects works to reflect many of the ways that videogames have begun to take up an increasingly prominent place within real world institutional exhibitions, archives, and collections. Through a conjoined lens that is equally informed by games preservation, etymology, and art history this essay works to unpack the intricacies of how the museum and collecting function with the Animal Crossing series. This examination of Animal Crossing will then be applied more broadly to two museums (the MoMA and the V&A) exhibition case studies, making the comparative argument that overtly taxonomic methods of display and archiving can work to deaden videogames’ inherently mutable vitality. By speculatively thinking of videogames as things akin to the bugs of Animal Crossing, to be kept alive throughout the archival process rather than dead objects to be preserved, a new, more productive lens of videogame curation can be gleaned.

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: none
Teacher disagreement score0.981
Threshold uncertainty score0.249

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 head0.015
GPT teacher head0.271
Teacher spread0.256 · 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