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Arkham Epic

2016· book-chapter· en· W2497590637 on OpenAlexaffabout
Luke Arnott

Bibliographic record

VenueAdvances in multimedia and interactive technologies book series · 2016
Typebook-chapter
Languageen
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsWestern University
Fundersnot available
KeywordsEPICNarrativeComicsStudioDramaArtFranchiseLiteratureRepresentation (politics)Visual artsPolitical science

Abstract

fetched live from OpenAlex

This chapter presents a model that explains how the epic is a narrative genre that has become popular across a variety of new media. It demonstrates how the Arkham series of Batman video games – Batman: Arkham Asylum (Rocksteady Studios, 2009), Batman: Arkham City (Rocksteady Studios, 2011), Batman: Arkham Origins (Warner Bros. Games Montreal, 2013), and Batman: Arkham Knight (Rocksteady Studios, 2015) – is constructed as an epic narrative within the larger Batman media franchise. The Arkham series aspires to epic status by eclipsing competing Batman texts or by assimilating those texts into its continuity. The series is an example of how video games now influence the evolution and cross-adaptation of derivative and parallel works such as comics, movies, and other paratexts. The chapter concludes by observing how games like the Arkham series relate to representation and theories of postmodernism.

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 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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.925
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.003
Scholarly communication0.0000.003
Open science0.0000.000
Research integrity0.0010.001
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 head0.010
GPT teacher head0.288
Teacher spread0.278 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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

Citations2
Published2016
Admission routes2
Has abstractyes

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