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Record W3084964381 · doi:10.7202/1071451ar

Adaptations of Empire: Kipling's Kim, Novel and Game

2020· article· en· W3084964381 on OpenAlexaffvenue
Lindsay Meaning

Bibliographic record

VenueLoading · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsIdeologyColonialismNarrativeDepictionRhetoricVideo gameEmpireAdaptation (eye)Big gameSociologyHistoryMedia studiesAestheticsLiteratureArtComputer sciencePsychologyPolitical scienceMultimediaLawEnvironmental ethicsLinguisticsPhilosophyArchaeologyPolitics

Abstract

fetched live from OpenAlex

This paper addresses the depiction of colonialism and imperial ideologies in video games through an adaptation case study of the 2016 indie role-playing game Kim, adapted from the Rudyard Kipling novel of the same name. I explore the ways in which underlying colonial and imperial ideologies are replicated and reinforced in the process of adapting novel to game. In the process of adaptation, previously obscured practices of colonial violence are brought to the forefront of the narrative, where they are materialized by the game’s procedural rhetoric. However, the game fails to interrogate or critique these practices, ultimately reinforcing the imperial ideological framework in which it was developed.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.008
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.011
Scholarly communication0.0060.004
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.069
GPT teacher head0.313
Teacher spread0.243 · 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 designQualitative
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

Citations0
Published2020
Admission routes2
Has abstractyes

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