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Record W4213334993 · doi:10.30986/2021.155

Jacques Delaunay et les moines poètes Dampierre et Marconville dans les Epigrammata

2022· article· en· W4213334993 on OpenAlexaff
John Nassichuk

Bibliographic record

VenueHumanistica Lovaniensia · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical Studies and Socio-cultural Analysis
Canadian institutionsWestern University
Fundersnot available
KeywordsPoetryAnguishElegiacPhilosophyAdorationFriendshipLiteratureHumanismArtDignityElegySolidaritySociologyTheologyEpistemologyLaw

Abstract

fetched live from OpenAlex

In his little-known 1539 collection of epigrams, Jacques Delaunay (Jacobus Alnetus), a physician and canon of Saint-Étienne de Troyes, includes two important, and hitherto unnoticed, poetic exchanges between the monastic humanist poets Jean Dampierre and Nicolas de Marconville and himself. After a brief presentation of these two figures, the present article examines the principal themes and literary techniques characteristic of the poems that comprise the two poetic “correspondences” with Delaunay. Examination of these two separate sequences reveals several common, unifying themes. The relative (perceived) impoverishment of their poetic invention, and the deep anguish that it generates, constitutes a recurring motif, and a veritable preoccupation, for these poets, all of whom speak of the challenges posed by duties that distract them from cultivating the muse. Their collective meditation on these themes quietly elaborates a defense of the dignity of minor poetic genres such as the epigram in hendecasyllables or elegiac distichs, insofar as these genres often give voice to relations of friendship, love, and Christian solidarity.

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)0.002
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 score0.015
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0030.005
Scholarly communication0.0030.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.041
GPT teacher head0.245
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
Published2022
Admission routes1
Has abstractyes

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