Bibliographic record
Abstract
This paper proposes to study the influence of cinema and media on the built environment in contemporary India. Following the reorganisation of the states since the new millennium there has been a demand to build cities, either as ‘new’ capital cities for the bifurcated states or as globally inflected cities for trade, commerce, and employment. This city-making effort, often environmentally unsustainable, has developed peculiar and unique association with cinema and the new media. This can be witnessed in the example of the proposed capital city of Amaravati for the Telugu-language state of Andhra Pradesh, after its separation from Telangana. The then Chief Minister of the state, Mr. Nara Chandra Babu Naidu (CBN) in 2017, inducted a well-known Telugu film director, S.S. Rajamouli (SSR), as the government’s representative to advise architects, Norman Foster + Partners. SSR who was enjoying the success of Baahubali, a two-part fantasy Telugu film across India, had begun to develop a pan-India base for his films. SSR’s rendition of a fiction city, ‘Mahishmati’ in Bahubali had reportedly brought him on-board to envision a real city for his people in its real time and space. The larger-than-life visuals of the fictional city and the grandeur of the sets of Bahubali took the country by storm, making the film the largest grossing film of the times. The revised designs emerged as a confluence of the global architectural trends and a contrived notion of the cultural symbolism of the region. Despite all these efforts, Naidu failed to impress the public. His eventual defeat in the following elections left Amaravati in a state of limbo, of perennial uncertainty. The purposed paper examines these links-- the significance of image-based aesthetics inspired by cinema that dictate the planning and development of cities, and the eventual deadlock towards sustainable cities in contemporary society.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.015 |
| Scholarly communication | 0.016 | 0.010 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.041 | 0.006 |
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".