Burhs, burghal territories and hundreds in the English central Midlands in the early tenth century. Part 1
Bibliographic record
Abstract
The strategic context of new burhs created by the West Saxon King Edward the Elder in the east and central Midlands, in part documented in the Anglo-Saxon Chronicle, is examined to determine the ways in which the foundation of these burhs as new fortified settlements was associated with the formation of new burghal territories to maintain their strategic functionality. These burghal territories typically comprised one or more units of around 300+ hides, here termed ‘proto-hundreds’. All of these are argued as constituting elements of a major reorganisation of the administrative landscape as part of the essential infrastructure of burghal formation. These new cadastral redevelopments demonstrate the organisational precocity of the West Saxon state at this period. These ‘proto-hundreds’ were subsequently divided into smaller units of around 100 hides in a new phase of reorganisation which was arguably concurrent with the creation of the shires, formed by amalgamation of the earlier burghal territories, in probably the third quarter of the tenth century. The first part of this paper examines the shires of Buckinghamshire and what is now western Northamptonshire; the second part extends this analysis to Bedfordshire, Hertfordshire, Middlesex, Huntingdonshire and Cambridgeshire.
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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 | 0.004 | 0.010 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".