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Record W2327539988 · doi:10.1525/rh.2010.28.4.408

Hélisenne de Crenne et l'infinie variété de la lettre invective

2010· article· fr· W2327539988 on OpenAlexaff
Claude La Charité

Bibliographic record

VenueRhetorica · 2010
Typearticle
Languagefr
FieldArts and Humanities
TopicRenaissance Literature and Culture
Canadian institutionsUniversité du Québec à Rimouski
Fundersnot available
KeywordsHumanitiesInvectivePhilosophyPolitical science

Abstract

fetched live from OpenAlex

La lettre invective a joui d'une grande fortune à la Renaissance, comme en témoignent Les Epistres familieres et invectives (1539) d'Hélisenne de Crenne. Une relecture de ce recueil à la lumière de la théorie épistolaire permet de nuancer nos a priori défavorables à cette pratique épistolaire que l'on aurait tort de réduire à une «bordée d'injures» aussi gratuites que disgracieuses. Ces épîtres invectives donnent à voir que le recours à l'insulte n'est jamais une fin en soi, mais un moyen de persuasion au service de la déconstruction de l'ethos de l'adversaire et du renforcement de la crédibilité de l'épistolier.

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)0.003
metaresearch head score (Gemma)0.005
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 score0.010
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.022
Scholarly communication0.0050.005
Open science0.0010.003
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0100.001

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 head0.009
GPT teacher head0.259
Teacher spread0.251 · 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
Published2010
Admission routes1
Has abstractyes

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