Remembering <i>Devdas</i>: Travels, Transformations and Persistence of Images, Bollywood-Style
Bibliographic record
Abstract
This essay studies different Hindi film adaptations of Sarat Chandra Chattopadhyay’s canonical Bengali novella Devdas, published in 1917. Briefly, the paper argues that the various iterations of Devdas produce a complex history of cinematic development in India, shaped as they are by significant moments: World War II; the 1947 Partition of British India into India and Pakistan and its resultant multiple displacements; the rural-urban transformations of the 1950s; postcolonial problems; and the cross-border migrations and circulation of people, audiences, films and capital in the post-globalization era. Thus, in my attempt to read the travels and transformation of cinematic codes through the various adaptations of Devdas, a larger historical trajectory of national and diasporic dislocation becomes evident, revealing a deeply complicated history of colonial and postcolonial India.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".