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Record W1571446079

Mouvement fasciste : des discours politiques aux idéologies antisémites

2015· article· fr· W1571446079 on OpenAlexaff
Étienne Bélanger

Bibliographic record

VenueÉrudit (Université de Montréal) · 2015
Typearticle
Languagefr
FieldSocial Sciences
TopicCommunism, Protests, Social Movements
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsPolitical science
DOInot available

Abstract

fetched live from OpenAlex

Comme nous l'avons vu, les photographies de l'époque montrent bien tout ce qu'implique le fait d'être membre du Parti national social chrétien (PNSC) d'Arcand dans les années 1930, particulièrement en 1938.Avant la création du parti, le mouvement des Goglus Dans cet article, nous analyserons les idéologies du parti et les différents discours politiques prononcés dans les années 1933 et 1934.Faisons ainsi un bond en arrière jusqu'à cette époque.En 1933, le PNSC n'existe pas encore.Le mouvement fasciste, appelé à ce moment-là « le mouvement des Goglus » 1 , est mené par Adrien Arcand.Celui-ci publie alors son premier ouvrage d'importance, intitulé Fascisme ou socialisme?.Ce livre illustre une première vague d'idéologie antijuive du mouvement des Goglus, qui deviendra le PNSC en 1934.« Le Juif, le responsable de tous les malheurs du peuple » En effet, l'extrait ici (fi gure 1) montre leproduitdel'infl uenceallemandeen ce qui concerne le Québec des années 1930.Arcand tente de convaincre le lecteur chrétien de race blanche de s'allier à lui dans un combat qu'il souhaite livrer contre les Juifs, qui selon lui sont les « seuls responsables

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)0.004
metaresearch head score (Gemma)0.008
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 score0.470
Threshold uncertainty score0.935

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0130.012
Scholarly communication0.0070.002
Open science0.0010.003
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0100.000

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 head0.054
GPT teacher head0.275
Teacher spread0.220 · 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
Published2015
Admission routes1
Has abstractno

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