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Record W7000700711

The function of hospitaller houses
\nin England, Ireland, Scotland and Wales

2016· dissertation· en· W7000700711 on OpenAlexfundno aff

Bibliographic record

VenueORCA Online Research @Cardiff (Cardiff University) · 2016
Typedissertation
Languageen
FieldArts and Humanities
TopicMedieval History and Crusades
Canadian institutionsnot available
FundersUniversity of TorontoUniversity of OxfordRoyal Historical Society
KeywordsPeriod (music)Middle AgesOrder (exchange)Function (biology)Craft
DOInot available

Abstract

fetched live from OpenAlex

During the medieval period the order of the Hospital of St John of Jerusalem was one of the oldest, wealthiest and farthest reaching of the crusading military orders. Granted official recognition by Pope Pascal II in 1113, the Order of the Hospital expanded its original vocation of caring for the sick to include a martial function within the Holy Land during the course of the twelfth century. In support of its various activities, the Hospitallers were given vast estates both in the east and in Western Europe from which it drew continual supplies of men, money, equipment and foodstuffs.. This dissertation seeks to expand the current understanding of the activities, nature and function of the military orders generally by providing a study on the estates of the Order of St John in Britain and Ireland, the regions physically farthest from the most active centre of traditional crusade activity, focusing on the period of time from the twelfth to the sixteenth century.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.194
Threshold uncertainty score0.386

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.006
Scholarly communication0.0040.002
Open science0.0010.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0080.001

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.

Opus teacher head0.039
GPT teacher head0.262
Teacher spread0.224 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2016
Admission routes1
Has abstractyes

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