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Record W3176825044 · doi:10.1080/00330124.2021.1922294

The Characteristics and Geographic Origins of King Harold Godwineson’s Army at the Battle of Hastings

2021· article· en· W3176825044 on OpenAlex
Christopher Macdonald Hewitt

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Professional Geographer · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicPhilippine History and Culture
Canadian institutionsBrock University
Fundersnot available
KeywordsBattleHistoryPower (physics)Geographic information systemOperations researchLawGeographyArchaeologyCartographyPolitical scienceEngineering

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.660
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.016
GPT teacher head0.276
Teacher spread0.260 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it