MétaCan
Menu
Back to cohort
Record W7152965626 · doi:10.5206/cahiers.v16.21659

La ruse du nom, machination rhétorique dans Amphitryon de Molière

2015· article· W7152965626 on OpenAlexaff
Nathalie Freidel

Bibliographic record

VenueCahiers du dix-septième An Interdisciplinary Journal · 2015
Typearticle
Language
FieldArts and Humanities
TopicHistorical and Literary Analyses
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsContext (archaeology)Subject (documents)Set (abstract data type)Relation (database)Identification (biology)

Abstract

fetched live from OpenAlex

cite Daniel Mornet, « qui n'a pas craint d'écrire qu'Amphitryon était une "pièce-flagornerie, ou, si l'on songe à toutes les flagorneries du temps, une pièce de courtisan" (Molière, [Paris: Boivin, 1943], 145-146) ».La thèse de la pièce de courtisan a d'abord été avancée par Roederer, suivi par des critiques comme Jacques Truchet, René Jasinski, Antoine Adam, Georges Couton. « Le dossier rassemblé par George Couton prouve bien que Molière devait savoir queLouis XIV s'intéressait à Mme de Montespan et que, connaissant la cour, il devait savoir aussi qu'il pouvait faire allusion à cette intrigue sans créer de scandale.Mail il ne suffit pas de prouver qu'il pouvait le faire pour prouver qu'il l'a effectivement fait » (Pommier 214).3 La Lettre sur la comédie de l'imposteur paraît, sans nom d'auteur, sans lieu et sans nom d'imprimeur, quelques jours après l'interdiction, par les autorités civiles et religieuses, de la Comédie de l'imposteur, représentée le 4 août 1667.Ce texte, longtemps considéré comme une riposte de Molière, a été attribué par Robert Mc Bride à La Mothe Le Vayer

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.048
Threshold uncertainty score0.095

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 studies0.0120.009
Scholarly communication0.0060.004
Open science0.0010.002
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0090.001

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 head0.019
GPT teacher head0.275
Teacher spread0.256 · 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 designQualitative
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
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueCahiers du dix-septième An Interdisciplinary JournalSame topicHistorical and Literary AnalysesFrench-language works237,207