Bibliographic record
Abstract
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?
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.017 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".