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Record W2013078815 · doi:10.3138/sim.4.4.004

Unsettling the Military Entertainment Complex: Video Games and a Pedagogy of Peace

2004· article· en· W2013078815 on OpenAlexvenueno aff
David J. Leonard

Bibliographic record

VenueSIMILE Studies In Media & Information Literacy Education · 2004
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsnot available
Fundersnot available
KeywordsEntertainmentMultimediaSociologyPsychologyPedagogyVisual artsComputer scienceArt

Abstract

fetched live from OpenAlex

Amid the cultural, political, and military shifts of post-9-11 American policy, the video game industry has responded with patriotic fervor and released a series of video war games. Virtual war games elicit support for the War on Terror and United States imperialism, providing space where Americans are able to play through their anxiety, anger, and racialized hatred. While commentators cite a post-September 11 th climate as the reason for increasing interest and support for the U.S. military, this article underscores the importance of video games as part of the militarization of everyday life and offers insight into the increasingly close-knit relationship between the U.S. military, universities, and the video game industry. Because video games form an important pedagogical project of U.S. war practices, they must be critically analyzed.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0030.006
Scholarly communication0.0060.006
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.029
GPT teacher head0.386
Teacher spread0.357 · 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 designTheoretical or conceptual
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

Citations62
Published2004
Admission routes1
Has abstractyes

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