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French Literature

2013· reference-entry· en· W4242948436 on OpenAlexvenueno aff
Andrea Frisch

Bibliographic record

VenueRenaissance and Reformation · 2013
Typereference-entry
Languageen
FieldArts and Humanities
TopicRenaissance Literature and Culture
Canadian institutionsnot available
Fundersnot available
KeywordsVernacularHumanismLiteratureArtVernacular culturePoetryPeriod (music)SonnetHistoryThe RenaissanceOld FrenchFrench literatureClassicsMiddle AgesErasmus+Art historyAncient historyPhilosophyTheology

Abstract

fetched live from OpenAlex

The French Renaissance, which in literary studies is more or less taken to span the 16th century, is considered to be a privileged moment in the emergence of a vernacular poetic literature in France. Echoing cultural impulses previously articulated by Italian poets such as Dante and Petrarch, and drawing on the humanist movement of the quattrocento, French poets and scholars, supported by François I (r. 1515–1547), consolidated a program for the enrichment of French vernacular culture through revived study of the Ancients. At the same time, overt religious controversy colored the whole of the 16th century in France, from the Affaire des Placards of 1534, the same year François Rabelais published his second novel, Gargantua, to the bloody civil wars that spanned the reigns of five kings in the second half of the century, when Pierre de Ronsard published his Sonnets pour Hélène, Robert Garnier his tragedies, and Michel de Montaigne his Essais. These violent conflicts attenuated French involvement in overseas exploration and colonization in the period, and had a significant impact on France’s cultural relations with its European neighbors, as Protestants became a conduit for numerous French-to-English translations in the second half of the century.

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)0.004
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.080
Threshold uncertainty score0.269

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.006
Science and technology studies0.0070.003
Scholarly communication0.0100.003
Open science0.0010.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0800.020

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 head0.216
Teacher spread0.201 · 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
GenreOther

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
Published2013
Admission routes1
Has abstractyes

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