An experimental community: the East India Company in London, 1600–1800
Bibliographic record
Abstract
The early East India Company (EIC) had a profound effect on London, filling the British capital with new things, ideas and people; altering its streets; and introducing exotic plants and animals. Company commodities - from saltpetre to tea to opium - were natural products and the EIC sought throughout the period to understand how to produce and control them. In doing so, the company amassed information, designed experiments and drew on the expertise of people in the settlements and of individuals and institutions in London. Frequent collaborators in London included the Royal Society and the Society of Apothecaries. Seeking success in the settlements and patronage in London, company servants amassed large amounts of data concerning natural objects and artificial practices. Throughout the seventeenth and eighteenth centuries, company scholars and their supporters in London sought to counter critiques of the EIC by demonstrating the utility to the nation of the objects and ideas they brought home. The EIC transformed itself several times between 1600 and 1800. Nonetheless, throughout the seventeenth and eighteenth centuries, its knowledge culture was characterized by reliance on informal networks that linked the settlements with one another and with London.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.011 | 0.014 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 0.003 |
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".