Economy and Society in North-Eastern Market Towns: Darlington and Northallerton in the Later Middle Ages
Bibliographic record
Abstract
The economic history of north-eastern England in the fifteenth and early sixteenth centuries is characterised by decline, with the region scarcely recovering from the economic and demographic ravages of the Black Death and subsequent outbreaks of plague before being plunged back into long-term recession. The main urban centres of the region, York and Newcastle-upon-Tyne, suffered considerable dislocation in the fifteenth century and remained in recession until well into the sixteenth. A major factor in the decline of York was the contraction of its cloth making industry, largely as a result of increased competition from the textile towns of the West Riding of Yorkshire, such as Leeds, Wakefield and Halifax. Smaller centres also suffered in this respect. John Leland's later description ( c. 1538) of Ripon as a town ‘where idleness is sore increased’ bore testimony to the fate of one such small town whose prosperity had once been founded upon the cloth trade. Another market town in decline was Richmond in the North Riding of Yorkshire. Its economy, too, was partially based upon the textile industry, although it was also an important marketing centre for corn and wool, being advantageously placed between the pastoral highlands of the Pennines and the lowland agricultural dales. However, the town suffered, apparently as a result of the great pestilence and agrarian crisis, which further undermined the north-eastern economy in the period 1438–40. By 1440, the burgesses of Richmond felt compelled to appeal to the crown for a reduction in the town's fee farm, citing a contracting population and competition from the numerous neighbouring markets (which were, undoubtedly, vying for the limited amount of trade) as the main reasons for the town's decline. Nevertheless, the region maintained the principal elements of its marketing structure, as this had developed during the two centuries before 1300. Margaret Bonney's study of Durham, for instance, illustrates how that city managed to maintain a reasonable level of economic stability because there was no significant export industry to suffer from native or foreign competition. Durham, indeed, functioned primarily as a service centre for the twin ecclesiastical administrations of the priory and the bishop, as well as providing marketing facilities for the rural hinterland. Other, less well-known urban communities which also managed to survive as viable marketing centres at this time were the small north-eastern market towns of Darlington and Northallerton.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.005 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".