Bibliographic record
Abstract
when to be free would cease to mean the ones in power shall gain delhi you will cease to be. —G. J. V. Prasad, Sati ‘I am amazed at how many times in its centuries long journey Dilli has been plundered and resettled,’ wrote Intizar Hussein in Once There Was a City Named Dilli (2016: 6). Delhi has witnessed the rise and fall of Indraprastha, of the Delhi Sultanate, an invasion by Tamerlane, the rise and fall of Shahjahanabad, and then the Rebellion of 1857, the rise of Lutyens’ Delhi, Partition, and its aftermath. With each rise and fall of empire, ‘a new Dilli is inhabited in the midst of the old Dillis’ (Hussein 2016: 36). Each leader of this new city claims that ‘this Dilli will have such vigour and brilliance that all the preceding Dillis and the Dillis to follow will fade before it’ (Hussein 2016: 36). However, ‘not one of these cities was loyal to its founder … whoever built a new city on the land of Dilli would very soon have to lose it’ (Hussein 2016: 46). Ahmed Ali, in the introduction to his novel Twilight in Delhi (1940), describes how after Partition, the new state of India, continuing in the British legacy, moved Delhi further away from its designation as the Mughal capital, Shahjahanabad, towards Indraprastha, the ancient seat of the Hindu empires rumoured to have been located in what is now called Delhi. Ali writes, ‘Seven Delhis have fallen, and the eighth has gone the way of its predecessors, yet to be demolished and built again. Life, like the Phoenix, must collect the spices for its nest and set fire to it, and arise resurrected out of the flames’ (1940: 20). The Emergency created yet another Delhi built by Indira Gandhi, and just two years later, another fallen Delhi with the election of the Janata Party in 1977. But what was resurrected from the flames this time? Delhi has been the capital of several historical world-empires and states. It is a place where many political fortunes rose and fell. Political change
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.509 | 0.355 |
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".