Industrial Waste Management and Urban Environments in Medieval England, 1300 - 1600
Bibliographic record
Abstract
This paper demonstrates how key industries impacted urban environments in late medieval England from 1300-1600CE through an examination of city laws, ordinances, and rulings. It focuses on the municipalities of Bristol, Coventry, Leicester, London, Northampton, and York, all of which had a considerable urban population in this time and sufficient primary sources to conduct this study. This paper contributes to the historiography by proposing a middle ground between previous economic and public health histories on urban industries. Though English municipalities understood and acted to mitigate the impact of industrial contaminants and resource depletion on people and urban spaces, they often did not have the ability to do so. Authorities pursued trades which produced the most waste and tried to exercise regulatory controls over how and where tradesmen operated, how artisans could dispose of waste, who could buy industrial by-products, and where a trade took place. \n \nA consideration of butchery, fishers and fishmongers, tanners and leather workers, and brewers reveals a struggle between artisans and authorities and artisans and themselves in pursuing a hospitable environment. Artisans and authorities had both societal and commercial and societal interests. Artisans also had their reputation to uphold as the informal market threatened their business. Despite a strong pull towards clean spaces, artisans often created waste in pursuit of profit, easier working conditions, and little ability to dispose of necessary by-products in any other way. These industries are inherently resource intensive and wasteful and their position in cities multiplied these unwanted consequences of industry.
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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 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".