London's Soap Industry and the Development of Global Ghost Acres in the Nineteenth Century
Bibliographic record
Abstract
Abstract John Knight and Sons soap company, like other successful soap manufacturers in Greater London, grew during the nineteenth century by combining technological innovation and marketing to sell increasing quantities of a product the British public increasingly saw as a symbol of their advanced civilisation. They did not struggle with the ecological limits of their regional hinterlands to provide the raw materials, as they relied on growing quantities of tallow, rosin and other commodities supplied from overseas ghost acres. John Knight and Sons linked consumers to environmental transformations and large-scale colonial dispossession in Europe, the Americas and Australasia. Millions of sheep and cattle were raised on the abundant grasslands found on the Eurasian steppe, the Pampas, the Great Plains and in Australasia, many of which were killed and processed only for their tallow, skins or hides. Economic and environmental factors created significant instability in the global tallow supply, but the end result was greater quantities of cheaper tallow shipped to market in London. These global ghost acres made the nineteenth century success of John Knight and Sons and other major soap producers in Greater London possible.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.000 |
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".