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Spiritual and Material Rewards on the Christian-Muslim Frontier: Norman Crusaders in the Valley of the Ebro in the First Half of the Twelfth Century

2017· article· en· W2775787999 on OpenAlexaff
Lucas Villegas-Aristizábal

Bibliographic record

VenueMedievalismo · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicMedieval History and Crusades
Canadian institutionsQueen's University
Fundersnot available
KeywordsNobilityFrontierReligiosityPeninsulaPeriod (music)HistoryReligious studiesSociologyAncient historyPolitical scienceArchaeologyLawArtPhilosophyAesthetics

Abstract

fetched live from OpenAlex

This article explores the involvement of the Norman nobility in the wars between Christians and Muslims in the Ebro Valley in the first half of the 12th Century. The work recognises how the participation of the this particular ethno-cultural group in the peninsula was renovated to a certain degree by the deeds and religious transformation that took place as result of the preaching and success of the crusade. Furthermore, by exploring the careers of Rotrou of Perche, Robert Burdet and Walter Guidvilla this piece demonstrates how their religiosity as well as the filial relations and traditional desire for wealth that characterise this group of warriors, made the Iberian theatre of conflict so attractive at this particular period. Also, this article, tries to show how their Iberians lay and clerical coreligionists perceived the usefulness of these Norman contingents in their conflict with the Almoravids.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.009
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0090.007
Scholarly communication0.0020.001
Open science0.0000.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.030
GPT teacher head0.227
Teacher spread0.196 · 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 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

Citations1
Published2017
Admission routes1
Has abstractyes

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