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Record W2942934929 · doi:10.3138/cras.49.1.003

The East Is Least: The Stereotypical Imagining of Essos in <i>Game of Thrones</i>

2019· article· en· W2942934929 on OpenAlexvenueno aff
Mat Hardy

Bibliographic record

VenueCanadian Review of American Studies · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicThemes in Literature Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsFantasyEscapismOrientalismDepictionThe ImaginaryRepresentation (politics)RealmHistoryMiddle EastAestheticsSociologyLiteratureArtPhilosophyEpistemologyPolitical sciencePsychologyArchaeologyPoliticsPsychoanalysis

Abstract

fetched live from OpenAlex

While Game of Thrones may appear to offer an avenue of escape to an imaginary realm, in its representation of race and geography, this fantasy universe simply reinforces existing preoccupations of our actual world. An example of this is in the representation of the Eastern lands and cultures in the story. The link between Eastern cultures and depravity has been part of Western imagining of the “Orient” for centuries, and the peoples of the Middle East are generally depicted as “fallen” compared with the more honourable denizens of the West; this occurs in fantasy literature, as well. This article examines the dynamics of ethnic and geographic representation in Game of Thrones from the perspective of Edward Said’s Orientalism and the historical foundations of Western depictions of the Middle East. It argues that despite the reputation of the series as ground-breaking escapism, its depiction of Eastern peoples is anything but.

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)0.002
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 score0.017
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0050.019
Scholarly communication0.0060.006
Open science0.0000.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.020
GPT teacher head0.271
Teacher spread0.251 · 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

Citations4
Published2019
Admission routes1
Has abstractyes

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Same venueCanadian Review of American StudiesSame topicThemes in Literature AnalysisFrench-language works237,207