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Record W4300281608 · doi:10.33137/rr.v29i1.11405

Milton 's Epics and the Book of Psalms

2009· article· en· W4300281608 on OpenAlexvenueno aff
Mary Anne Radzinowicz, Judith Scherer Herz

Bibliographic record

VenueRenaissance and Reformation · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicHistorical and Linguistic Studies
Canadian institutionsnot available
Fundersnot available
KeywordsArtLiteraturePhilosophyHistory

Abstract

fetched live from OpenAlex

Renaissance et Réforme / 85 Retz, f. 104r°, v. 9) devient "Mon esprit se repaît [...]; "de peurs me glaceans" {Amours, XXVI, v. 3) devient "de pleurs me glaçant" (p.52).Il y a de cela de très nombreux exemples.Mais qu'il nous soit permis de considérer comme plus grave l'introduction d'une syllabe au premier vers du célèbre "J'ayme, et je n'ayme, je me plais au servage" {Album de la Maréchale de Retz, f. 67v°), que Melançon modernise en "J'aime et je n'aime pas, je me plais au servage."Par contre, là où une intervention légitime corrige le "noeu gordien" du manuscrit {Album de la Maréchale de Retz, f. 106v°, v. 12) en "noeud gordien," c'est encore une fois le manque d'une signalation en note que nous ne pouvons pas partager, d'autant plus que cette même correction avait été déjà proposée par Ruggero Campagnoli dans une étude sur les sonnets d'amour de Jodelle.On aurait, bien sûr, aimé trouver dans un programme de diffusion de la poésie de Jodellelouable, opportun et bienvenuplus de respect pour le texte, et plus de respect également, pour ces non spécialistes, pour les lecteurs modernes "peu familiers" de la Renaissance à qui il s'adresse.Le programme, l'idée même de la collection, et le volume n'en perdent évidemment pas par là leur valeur.Car, bien sûr encore, ce ne sont que les spécialistesles lecteurs familiers de la Renaissance que gêne ce manque de respect.

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 score0.020
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.009
Scholarly communication0.0060.004
Open science0.0010.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0200.004

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 head0.014
GPT teacher head0.271
Teacher spread0.257 · 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
Published2009
Admission routes1
Has abstractyes

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