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Record W4406361740 · doi:10.24135/ijcmr.2023.10

Ghastly Graphics: Tool Fandom, Bad Cinema, and the Haunted PS1 Game Development Community

2023· article· en· W4406361740 on OpenAlexaff
Pat Dolan, Andrew Bailey

Bibliographic record

VenueInternational Journal of Creative Media Research · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsYork University
Fundersnot available
KeywordsMovie theaterFandomComputer scienceSociologyAestheticsMedia studiesMultimediaArtArt history

Abstract

fetched live from OpenAlex

Throughout the late 2010s, a community of independent game developers has come together under the moniker “Haunted PS1” to produce an annual anthology of game demos and an accompanying livestreamed event showcasing these works celebrating a mode of game-making often referred to as “low-poly horror.” This emerging genre nostalgically celebrates the aesthetics of older generations of computer and console games, especially those made for the original PlayStation (PS1) during the mid-to-late 1990s. Over time, this has resulted in an increasingly large group of new indie games that have all been deliberately made to recreate the awkward control schemes, disorienting texturing warping, and jittery polygons inherent to PS1-era game development. To achieve these outdated effects using contemporary game engines, the Haunted PS1 community has produced and openly shared its own custom tools and plugins. This article uses one such tool called “The Haunted PSX Render Pipeline” as a prompt to investigate the relationship between independent game development and other nostalgic and DIY modes of creative practice, namely zine-making and underground horror film. Furthermore, we work to reveal why games and tools released within the Haunted PS1 community are so often distributed for free and how this is partially related to the distinctly obsolete, ugly, and non-commercial aspects of the PS1 aesthetic within contemporary videogame capitalism and fandoms for so-called “bad” media.

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)0.003
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.013
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.001
Science and technology studies0.0100.013
Scholarly communication0.0130.006
Open science0.0020.008
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0110.001

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 head0.124
GPT teacher head0.446
Teacher spread0.322 · 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 designNot applicable
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

Citations1
Published2023
Admission routes1
Has abstractyes

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Same venueInternational Journal of Creative Media ResearchSame topicDigital Games and MediaFrench-language works237,207