The Characteristics and Geographic Origins of King Harold Godwineson’s Army at the Battle of Hastings
Bibliographic record
Abstract
The Battle of Hastings is without question one of the more important conflicts in English history, representing the last time England was successfully invaded by a foreign power. Reflecting this fact, there are literally hundreds of accounts that seek to examine and explain precisely what happened when opposing English and Norman forces met in Sussex on 14 October 1066. Although much has been written about the men who actually fought there, surprisingly little has been written about where they originated from. To help address this anomaly, this article examines participation in the English army at the battle with the aid of geographic information systems (GIS) techniques. The analysis indicates that participation in the English army was spatially dependent and related to the amount of land per manor. It is also demonstrated that manors held by the local elites at the time (thegn) by and large did not participate in the battle. The article concludes with a discussion of the implications of these findings for the veracity of existing historical accounts of the Battle of Hastings, as well as options for and benefits of applying GIS analysis to other historical events.
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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 | 0.002 |
| 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 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".