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Record W1986036195 · doi:10.3138/ctr.159.008

Outing Ourselves in Outer Space: Canadian Identity Performances in BioWare’s <i>Mass Effect</i> Trilogy

2014· article· en· W1986036195 on OpenAlexvenueaboutno aff
Peter Kuling

Bibliographic record

VenueCanadian Theatre Review · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsnot available
Fundersnot available
KeywordsTrilogyNarrativeIdentity (music)QueerMedia studiesSociologyAestheticsGender studiesArtLiterature

Abstract

fetched live from OpenAlex

Abstract: Throughout BioWare’s Mass Effect 3, players confront a vast array of unexpected Canadian content in narrative dialogue, settings, and identity development choices. This article examines the overall effects of Canadian content in this immersive video game series. Beginning in Vancouver and ending in London, England, Mass Effect 3 immerses players in world-ending conflicts linked with historical Canadian wartime experiences, which are creatively disguised through inventive science fiction. This game evokes ideas of colonial duty and personal self-sacrifice; players also confront cultural eugenics similar to social Darwinism during World War II. Canadian and queer identities develop in tandem as players consider humanitarian and inclusive possibilities, performing with outer space races in conflict. Players can even personalize their own Commander Shepard by customizing his/her gender, race, and sexuality. During the game, players may pursue intimate relationships with other men, women, or alien non-player characters; these choices are developed as moments of “coming out” that parallel the Canadian content revelations in the game. All of these contemporary identity negotiations create a vastly complex system of video game user-generated performances as players help their Canadian Commander Shepard reshape the universe.

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)0.002
metaresearch head score (Gemma)0.000
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: none
Teacher disagreement score0.990
Threshold uncertainty score0.631

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.013
GPT teacher head0.284
Teacher spread0.271 · 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.

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

Citations4
Published2014
Admission routes2
Has abstractyes

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