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Record W4392787396 · doi:10.3138/flor-2023-02-13

Roman Aspects of Romanesque Architecture in England and Wales

2024· article· en· W4392787396 on OpenAlexaffvenue
Malcolm Thurlby

Bibliographic record

VenueFlorilegium · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicClassical Antiquity Studies
Canadian institutionsYork University
Fundersnot available
KeywordsArchitectureHistoryArchaeologyGeography

Abstract

fetched live from OpenAlex

This article investigates late eleventh- and twelfth-century architecture in England and Wales from five interrelated points. First, it considers the appropriation of Roman sites for buildings of the post-1066 Norman administration. Second, it examines the creation of an architectural iconography in which there are associations with Imperial Rome. Third, there is the matter of scale, the desire to build big after many centuries of little or no tradition of constructing large edifices. Fourth, it explores the acquisition of a practical understanding of the building technology required for erecting large buildings. Fifth, it looks into the vocabulary of architectural articulation, the use of marble, and aspects of stone sculpture inherited from antiquity and appropriate to the monumentality of the new architecture. It references specific buildings, such as the Constantinian Basilica of Old St Peter’s in Rome, through the adaptation of triumphal arches down to details such as chip carving, marble, and the reuse and recreation of Roman bricks. Of the many large-scale buildings built by the Normans, a more detailed examination is devoted to the White Tower in London, castles at Colchester and Castle Rising, Winchester and Durham cathedrals, and the former abbey churches of Tewkesbury and Gloucester. It investigates the application of principles of the first-century BCE Roman architect and engineer, Vitruvius, the author of De architectura.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.942
Threshold uncertainty score0.952

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.281
Teacher spread0.265 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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
Published2024
Admission routes2
Has abstractyes

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