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Record W2902709299 · doi:10.1386/host.9.2.213_1

8-bit nostalgia and the uncanny: Horror as critique in Twine games

2018· article· en· W2902709299 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

VenueHorror Studies · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsUncannyDefamiliarizationCommodificationArtAestheticsVideo gameBalladMovie theaterAppealLiteratureSociologyVisual artsComputer scienceMultimediaLaw

Abstract

fetched live from OpenAlex

Abstract As the video game medium has matured, nostalgia for earlier games and systems has grown, including through commodification of nostalgia by video game companies. Nostalgia contrasts a constructed ideal past in tension with an inadequate present. This doubled structure echoes how the uncanny distorts familiar spaces with unfamiliar dread. I explore how three indie Twine games create horror through their rhetorical and mechanical appeal to nostalgia. Tom McHenry’s Horse Master (2013) problematizes players’ empathy in resource sims; Michael Lutz’s the uncle who works for nintendo (2014a) examines the dangers of over-immersion in video games; and Christine Love’s Even Cowgirls Bleed (2013) critiques violent gameplay mechanics by taking them to their horrific extreme. These games’ aesthetic, mechanical, and thematic appeal to players’ nostalgia leads to a defamiliarization and ironization of the familiar, resulting in an uncanny horror. As a result, these games use the horror genre to critique unproblematized and commodified nostalgia in the video game community.

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)0.002
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: Empirical
Teacher disagreement score0.803
Threshold uncertainty score0.901

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
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 head0.028
GPT teacher head0.373
Teacher spread0.346 · 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