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Record W2053411104 · doi:10.3917/rma.193.0649

La réinvention des Béatitudes dans le Manuel pour mon fils de Dhuoda

2014· article· fr· W2053411104 on OpenAlexaff
Brenda Dunn‐Lardeau

Bibliographic record

VenueLe Moyen Age · 2014
Typearticle
Languagefr
FieldArts and Humanities
TopicReformation and Early Modern Christianity
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsPhilosophyPoliticsThe RenaissanceArtTheologyArt historyPolitical scienceLaw

Abstract

fetched live from OpenAlex

The aim of this article is to highlight the original way in which Dhuoda uses Christ’s Sermo in monte to express her moral teaching for the benefit of her son’s religious and political upbringing while hinting at politics of her day. In a section of her moral speculum dedicated to the ways of overcoming vices by remembering the 8 beatitudes and living by them, she boldly reinterprets Christ’s sermon while preferring Mathew’s version to Luke’s. Not only does she suppress two beatitudes and add three culled from other biblical sources but she rewrites others, using both the rhetoric of copia and brevitas, so that her son may fashion his aristocratic self according to Christ. Our duchess comments on Old and New Testament texts in private, thus avoiding Saint Paul’s admonishments against women preaching in public. In addition, in a period where earthly happiness is considered inferior to heavenly bliss according to the Augustinian concept of contemptus mundi and contemptus carnis, she appears as a forerunner of the Renaissance where there is room for both.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.046

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 studies0.0060.008
Scholarly communication0.0040.001
Open science0.0000.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.026
GPT teacher head0.230
Teacher spread0.204 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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