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Record W1998962279 · doi:10.1558/jasr.v21i3.366

Orientalism in Outer-space

2009· article· en· W1998962279 on OpenAlexaff
Scott Dunbar

Bibliographic record

VenueJournal for the Academic Study of Religion · 2009
Typearticle
Languageen
FieldArts and Humanities
TopicSouth Asian Cinema and Culture
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsSanskritHollywoodHinduismOrientalismLiteraturePopular cultureAppropriationModernityHistoryArtAestheticsPhilosophyArt historyReligious studies

Abstract

fetched live from OpenAlex

Several Hollywood science fiction films have recently appropriated Sanskrit mantras as a prominent feature in their musical soundtracks. Notably, Hollywood’s use of ‘SF Sanskrit’ tends to evoke a sense of militancy and war rather than tranquillity and peace, which has resounding Orientalist connotations. Nevertheless, it will be shown that the correlation between mantras and warfare actually has historical precursors within the Hindu tradition. To advance this thesis, two case studies are examined: (1) The Matrix Revolutions and (2) Star Wars Episode I—The Phantom Menace. It will be shown that each of these films presents mantras in cinematic contexts evoking militancy and war. Such positioning of Sanskrit in belligerent film space, however, raises interesting questions about evolving Orientalist stereotypes in popular culture: Why is Sanskrit associated with war in the SF industry? Is Hollywood’s appropriation of Hindu mantras a new ‘fad’ to market SF in ‘exotic’ Indian packaging or an effort to ‘spiritualise’ the genre? What does Hollywood’s use of Sanskrit tell us about emerging views of Hinduism in modern SF films, and about shifting views of the ‘Orient’ in popular culture?

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.330
Threshold uncertainty score0.215

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.031
GPT teacher head0.296
Teacher spread0.265 · 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 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

Citations1
Published2009
Admission routes1
Has abstractyes

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