Bibliographic record
Abstract
Relying on a quixotic blend of catchy tunes, frenetic dances, colourful costumes, and comically elaborate plot narratives, Indian films attract large audiences from across South Asia and around the world. Important in the appeal of this cinematic “masala” has been an idealized depiction of India and an overall disparaging representation of the West. Recently, film-makers, in their pursuit of creating ever more dazzling spectacles, have also become increasingly interested in portraying other world cultures, with non-Indian Asian societies being especially favoured. Using film music as a focal point, this article explores the emergent constructs and depictions of Asia vis-à-vis India and the West. It focuses specifically on representations of Islamic West Asia, especially Turkey, and industrialized East and Southeast Asian urban centres like Bangkok, Hong Kong, Shanghai, and Tokyo. Analyses of songs in such films as Mission Istaanbul, Bombay to Bangkok, and Chandni Chowk to China reveal not only how India sees itself with respect to the rest of the continent, but also the extent to which the way it sees itself is and is not premised on Western Orientalist paradigms.
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 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 | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 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".