Forging Global Networks in the Imperial Era: Atiya Fyzee in Edwardian London
Bibliographic record
Abstract
This chapter examines the global networks forged by South Asians in Edwardian Britain through the eyes of Atiya Fyzee, a Muslim woman from Bombay. 1 This era is perhaps the least well- served in existing literature on Indian travellers, students and settlers in Britain despite its depiction as the apogee of British imperialism before the First World War began the process of decline. The Edwardian era is often seen as the ‘apogee of Empire’, but actually it may not have been quite so as support for empire was ‘frothy rather than deepseated’. 2 Nevertheless Edwardian London remained a great imperial city at the heart of an equally great empire; the nexus of the empire’s political authority, financial power and commercial dominance over approximately one- quarter of the Earth’s population and one- quarter of its land mass. 3 London was thus the meeting point for an impressive slice of humanity from across the globe: not just native Britons local to the city or visiting from the provinces, but also colonial subjects lured to the imperial ‘centre’ from British territories in Asia, Africa and the Americas. As one Indian traveller, A. L. Roy, wrote: ‘London means the centre of a world- wide empirechrw… a repository of wealth and a reservoir of energychrw… a whirlpool of activity and a deep sea of thought, a point where the ends of the world may be said to meet.’ 4 Census figures for the period suggest that, at a time when Bombay, for instance, boasted less than a million people, the population of greater London was nearly seven million, making it the largest metropolis in the world. 5 These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.016 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".