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Record W7035899090

Analyse rhétorique des Femmes illustres de Madeleine et Georges de Scudéry

2001· other· en· W7035899090 on OpenAlexvenueno aff

Bibliographic record

VenueLibrary and Archives Canada (Government of Canada) · 2001
Typeother
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMechanisms of cancer metastasis
Canadian institutionsnot available
Fundersnot available
KeywordsEthosIntellectVisionPrideOriginalityRhetoricObject (grammar)
DOInot available

Abstract

fetched live from OpenAlex

In this master's paper, the author studies the written construction of the ethos of the female characters in the essay from Madeleine and Georges de Scudery that was published in 1642 in Paris, Les Femmes illustres ou les harangues heroiques. She demonstrates how the authors refused the usual accepted practices in literature at that time to claim a right for women to develop their intellect in the way men could develop theirs. Therefore, she compares the contents of the essay with two important visions of women in literature: one of a strong women, as exposed in the literature linked to the "Querelle des femmes", and one of a weeping mistress screaming out all of her pain and sorrow, inspired from the Heroides d'Ovide. She shows how the text of the Scudery is different from the ones related to the "Querelle des femmes". She studies the formal characteristics of the harangue and she compares a rhetoric analysis of the scuderian texts with a quick study of the latin epistles. By doing so, the author wants to make the originality emerge out of the female characters of the Femmes illustres. She wants to emphasize the fact that the authors of that essay allowed women to become the subjects rather than the objects of the speeches. They gave them a chance to express their courage, their pride and their ambitions rather than confining them exclusively to family, love and religion matters, breaking out the traditional scope of the female speech.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.241
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.005
GPT teacher head0.182
Teacher spread0.177 · 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 teacher head, not a consensus.

Study designBench or experimental
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

Citations0
Published2001
Admission routes1
Has abstractyes

Explore more

Same venueLibrary and Archives Canada (Government of Canada)Same topicMechanisms of cancer metastasisFrench-language works237,207