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Record W2418603491 · doi:10.7202/1035937ar

La parole inversée ? Marine Le Pen et son identité-ressource langagière

2016· article· fr· W2418603491 on OpenAlexvenueno aff
Fabienne Baider

Bibliographic record

VenueNouvelles perspectives en sciences sociales · 2016
Typearticle
Languagefr
FieldArts and Humanities
TopicLinguistics and Discourse Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

Cette étude fait le point sur des recherches informatisées d’analyse de discours politique, et en particulier du discours populiste. La perspective adoptée est celle de l’étude de la construction de l’identité empathique de Marine Le Pen, conformément à des stéréotypes féminins, et ayant pour objectif des positionnements politiques précis et conformes aux fondamentaux du Front national. Des outils informatiques permettent de détecter des tendances discursives par le repérage de mots-clefs tels que solidarité, souffrances , tendances qui peuvent ensuite être affinées par des études qualitatives. D’une part, ce travail confirme la performativité politique des émotions lorsqu’elles sont conformes à des stéréotypes sexués. D’autre part, il atteste la présence de particularités rhétoriques d’un parti anti-système (avec des notions-clefs restant présentes au fil des années) qui sont adaptées aux nouvelles donnes politiques (le point de vue et la focalisation sont retravaillés). Ainsi le style d’intervention de Marine le Pen ferait-il basculer rhétoriquement un discours focalisé sur le ressentiment, le mépris et la nostalgie (celui de Jean-Marie Le Pen) en un discours que nous analysons comme jouant sur des émotions positives, notamment, ici, l’empathie plus conforme à un ethos féminin.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.793
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.007
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.043
GPT teacher head0.326
Teacher spread0.283 · 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; both teacher heads agree on what is shown here.

Study designTheoretical or conceptual
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

Citations6
Published2016
Admission routes1
Has abstractyes

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