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Record W4399159471 · doi:10.1515/9782760547735

Les défis du pluralisme à l'ère des sociétés complexes

2017· book· fr· W4399159471 on OpenAlexaboutno aff
Félix Mathieu

Bibliographic record

VenuePresses de l'Université du Québec eBooks · 2017
Typebook
Languagefr
FieldSocial Sciences
TopicSocial Sciences and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsPhilosophy

Abstract

fetched live from OpenAlex

Dans nos sociétés dites postfactuelles, il importe de comprendre et de simplifier la pensée des philosophes qui ont réfléchi au pluralisme pour développer un regard critique face aux sophismes ou aux raccourcis intellectuels véhiculés. Il faut mettre à l’épreuve des faits les multiples affirmations des dirigeants et des analystes politiques. Cela dit, alors qu’on célèbre en 2017 le 150e anniversaire de la fédération canadienne, l’heure est également au bilan de la coexistence des différents partenaires de l’association politique. Le présent ouvrage propose une analyse théorique, empirique et normative des débats qui portent sur l’aménagement de la diversité ethnoculturelle et sociétale dans les démocraties libérales contemporaines. Animé par un désir de clarification conceptuelle des outils permettant d’interpréter le langage complexe du multiculturalisme, de l’interculturalisme, du nationalisme et du fédéralisme, l’auteur s’adresse à la fois au monde universitaire et aux citoyens engagés. Adoptant une posture critique et normative, l’auteur veut repenser les fondements du fédéralisme canadien, de sorte que le Canada soit véritablement ouvert à la diversité issue de l’immigration, mais aussi à celles de la nation mino­ritaire québécoise, des nations autochtones, sans oublier celles de la minorité nationale anglophone du Québec et du groupe anglophone majoritaire au Canada.

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)0.011
metaresearch head score (Gemma)0.012
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: Other · Consensus signal: Other
Teacher disagreement score0.042
Threshold uncertainty score0.136

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0130.065
Scholarly communication0.0200.011
Open science0.0020.010
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0070.001

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 head0.048
GPT teacher head0.282
Teacher spread0.235 · 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
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

Citations1
Published2017
Admission routes1
Has abstractyes

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