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Record W2922346536 · doi:10.1017/s0021911818002620

Virtual Earthquakes and Real-World Survival in Japan's<i>Disaster Report</i>Video Game

2019· article· en· W2922346536 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

VenueThe Journal of Asian Studies · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicNarrative Theory and Analysis
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsRhetoricNarrativeVideo gameNatural disasterOperationalizationPhotographyQuake (natural phenomenon)Rhetorical questionMedia studiesSociologyHistoryVisual artsMultimediaComputer scienceArtLiteratureGeographyEpistemologyLinguistics

Abstract

fetched live from OpenAlex

This article analyzes the first video game in the Zettai Zetsumei Toshi (2002, Disaster Report) series for Sony's PlayStation 2 console against the backdrop of the 2011 Tōhoku earthquake and tsunami. In the game, players must use limited resources to escape from an earthquake-stricken city while rescuing other survivors. The article argues that the game makes visible the marginal victims and narratives of survival often erased under the collective rhetoric of national trauma. This is explored in relation to disaster photography and artistic representations of 3.11. The article suggests that the game's narrative rejects governmental rhetoric about nuclear energy and that the gameplay mechanisms utilize “limited engagement” or a form of operationalized weakness in order to communicate victimhood to players. The article concludes with an examination of how the in-game disaster photography inscribes players’ actions, making it more difficult to subsume these images into a generalized account of natural disaster trauma.

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)0.001
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.165
Threshold uncertainty score0.417

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.034
GPT teacher head0.278
Teacher spread0.244 · 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